ABSTRACT. Urban transport planning is characterized by the scarcity of space and several kinds of externalities such as congestion and emissions. This means that the cornerstones of urban transport planning are 1) space-efficient ways of transportation, e.g. attractive public transport, smart logistics etc. 2) ways to internalize externalities, e.g. congestion pricing, emission control zones etc. In principle, these strategic planning principles are well understood by transport planners and economists. The hitch is that such measures often meet resistance from politicians and the general public. There are several obstacles for implementing smart and efficient urban mobility solutions, including the inherent shortsightedness of politics (future citizens don’t vote in today’s elections), status quo bias, resistance against pricing as an allocation measure, failure by decision-makers to choose the most cost-efficient investments and many others. This talk discusses the nature of some of these obstacles, and provides ideas for how they can be overcome.

ABSTRACT. Intelligent transportation systems (ITS) enable the collection of data in real time. Average speed, travel time and delay at intersections are some of the most important measures, often used for monitoring the performance of transportation systems, and useful for system management and planning. 
In urban transportation planning, intersections are considered critical points, acting as bottlenecks and clog points for urban traffic. To improve the urban transport efficiency is necessary to detect the travel time at intersections in different turning directions.
Smartphones represent a low-cost technology, useful in obtaining information about traffic state. However, smartphone GPS data suffer for low precision, mainly in urban areas.
In this paper, we present a fuzzy set-based method for the car positioning within road lanes near intersections using GPS data coming from smartphones. We have introduced the fuzzy sets to take into account uncertainty embedded in GPS data when trying to identify the position of cars within the road lanes.
We applied the proposed model to three intersections in the urban road network of Bari (Italy). First results reveal the effectiveness of the proposed methodology when comparing the actual car positions and those determined by the model.
This paper represents a first work toward a new methodology to assess queues for each lane near intersections and to develop a novel traffic light control system, based on real-time data coming from travelers’ smartphones.

ABSTRACT. Many researchers and traffic engineers have been working on optimizing signal control with respect to its effects on traffic flow and
externalities like emissions. As large field studies for traffic management are not sustainable and actuated control strategy becomes complex, its evaluation is done with microscopic traffic simulation. However, their integrated signal control model often impedes implementing the custom control strategy in contrast to signal planning software. Making both types of software cooperate offers valuable perspectives to develop and evaluate a custom control strategy more efficiently. 
In this work, an overview of signal control and how it can be modeled in microscopic traffic simulation is given. Then, the signal planning software LISA+ and the microscopic traffic simulation Aimsun are connected to allow for external signal control. LISA+ offers a virtual signal controller to communicate with external applications via network. Aimsun sends information about the chosen signal program and the detected vehicles to the controller and receives back the signal states for the next simulation second. This concept is presented in detail taking into account the comunication protocol and the implementation on the Aimsun side. A case study with time-dependent actuated signal control is included as well.

ABSTRACT. In 2013, 2+1 roadways have become mandatory for newly constructed rural roadways in Germany.
The steady trend towards autonomous vehicles and vehicle-to-X (V2X) communication will enable new automated traffic coordination mechanisms. In our research, we study how traffic flow on 2+1 roadways can be improved by using such mechanisms for coordinating the usage of overtaking lanes.

Conflicts between vehicles on 2+1 roadways arise due to (1) differing capabilities (e.g. maximum speed), and (2) conflicting preferences of drivers (e.g. desired speed). These conflicts can lead to poor use of resources, and ultimately in time loss both from an individual vehicle and aggregated system perspective. To foster acceptance of coordination mechanisms, it is important to not only consider the system perspective but also to ensure some level of driver satisfaction and fairness, e.g. if vehicles are denied access to the overtaking lane in favour of faster vehicles, this raises questions regarding the acceptance of external coordination.

While there is some research studying microscopic optimisation of traffic flows on rural 2+1 roads and intersections, there has been only little research focusing on driver satisfaction and fairness of mechanisms.
In this work, we present the results of a pre-study on simulated 2+1 manoeuvres conducted using the Simulation of Urban MObility (SUMO) suite to estimate optimisation potentials of coordination. Preliminary results indicate potentials to reduce driver dissatisfaction while maintaining fairness.

We analyse optimisation potentials and propose a model which combines driver satisfaction and fairness of coordination, aiming at increasing acceptance of autonomous vehicle coordination.

ABSTRACT. Transportation in urban areas is highly complex because of the variety of possible facilities and routes, the multitude of origins and destinations, the increase of population density and traffic. Furthermore, people are willing to use more environmentally friendly transportation modes, such as cycling, to do short-distance trips in urban areas.
This paper develops a multi-objective model for passengers in urban transportation network for short trips where travel distance is less than 30 km. The main objective of this paper is to improve the urban network mobility in order to decrease traffic congestion, road conflicts between road users and pollution. Furthermore, optimization objectives could comprehensively reflect expectations of passengers from the dimension of traffic and emissions as a criteria and using a motor vehicle or a bicycle as an alternative. Survey data gathered by presential and online forms are used to prioritize the alternatives considering the criteria by Analytic Hierarchy Process (AHP). 
The methodology of this study was applied based on the real world case study in the city of Aveiro, Portugal. The present work uses a microscopic simulation platform of traffic (VISSIM), road safety (SSAM) and emissions (Vehicle Specific Power – VSP) to analyze traffic operations, road conflicts and to estimate carbon dioxide (CO2) and nitrogen oxide (NOx) emissions. Three dimensional Pareto Fronts, which were expressed through traffic performance, road conflicts between motor vehicles and bicycles and emissions, were optimized using the fast Non-Dominated Genetic Algorithm (NSGA-II).

ABSTRACT. Traffic noise is an important source of environmental stress that can damage human health. This phenomenon may be sensitive nearby roundabouts where noise levels may exceed exposure limits. However, the quantification about noise perceived by pedestrians at influence areas of roundabouts is lacking. This research assessed the characteristics of noise along an urban corridor with two roundabouts. A deeper understanding about the exposure to noise levels perceived by pedestrians is a contribution of the paper. The specific objectives are: 1) to characterize corridor-specific operations in terms of traffic and pedestrian performance, carbon dioxide and nitrogen oxide emissions, and noise; and 2) to explore the differences in the optimal crosswalk locations considering above-related criteria. Traffic and pedestrian volumes, vehicle dynamic and noise data were collected during morning and evening peak periods in the selected site. Traffic and pedestrian performance, and vehicular emissions were evaluated using VISSIM traffic model and Vehicle Specific Power (VSP), respectively. Traffic noise was estimated with a semi-dynamical model and an estimation of the corridor Source Power Level (SPL) was used as a distance-free parameter to be compared with other emissions. Finally, a Genetic Algorithm (GA) was applied to find optimal crosswalk locations. It was found that crosswalks nearby the present location (PC = 33 m) provided a good balance among traffic and pedestrian performance, emissions and noise, regardless of peak period. The inclusion of noise related-criteria resulted in some optimal locations next roundabout exit section (13-23 m) mostly due to low pedestrian volumes in the study locations.

ABSTRACT. Presence of pedestrian crosswalks and cyclists at innovative configurations of roundabouts may result in an impedance effect on the available vehicular capacity of the intersection. The degree of this impedance is related to the likelihood of driver yielding at the crosswalk or bicycle dedicated lanes perpendicular to the movements of motor vehicles. However, little is known about the impedance effect and increase in emissions regarding the presence of pedestrians and cyclists at different turbo-roundabout layouts. The main objective of this paper is to quantify pedestrian and cyclist impacts on a turbo-roundabout corridor level. The study has two major purposes: 1) to evaluate the impact of several pedestrian and cyclists demands on corridor traffic performance and pollutant emissions; 2) to examine the effect of different driver yielding behaviour rates on both cyclist and pedestrian delay. Vehicle dynamics along with traffic, pedestrian and bicycle volumes data were collected from two turbo-roundabout corridors in the Netherlands. Microscopic modelling platforms of traffic (VISSIM) and emissions (Vehicle Specific Power and EMEP/EEA) were used to reproduce sites operations. Next, 70 combined pedestrian and cyclist demand scenarios according the corridor-specific characteristics were defined. Each volume scenario was then applied to scenarios with yielding rates of 100%, 80%, 60% and 40%.

ABSTRACT. The environmental impact of road intersection operations, and in particular of alternative types of traffic control, has received increasing attention in recent years as a factor to be considered in addition to efficiency and safety. The purpose of this study is to provide experimental evidence about this issue based on direct measurement of CO2 emissions produced by a vehicle under traffic signal versus roundabout control. Carbon Dioxide was chosen as specific target of the analysis because of its important contribution to the “greenhouse effect”. Using data collected with a Portable Emission Measurement System (PEMS) installed on a test car, a before-and-after analysis was conducted on an intersection where a roundabout has replaced a traffic signal. A total of 396 trips were carried out by two drivers in different traffic conditions and in opposite directions along a designated route. Using statistical methods, the existence of significant differences in CO2 emissions in relation to the type of intersection control was investigated based on the collected data, also considering the effect of other explanatory variables and focusing in particular on peak traffic conditions. More precisely, the effect of the type of control has been characterized using descriptive statistics and permutation tests applied to the entire data set, while an analysis based on binary logistic regression has been performed with specific reference to trips carried out under peak traffic conditions. The results of these analyses support the conclusion that converting a signal-controlled intersection to a roundabout may lead to a decrease in CO2 emissions.

ABSTRACT. Electric vehicles promise to contribute to the achievement of a more sustainable transport system, e.g. through reducing energy consumption and CO2 emissions. For the assessment of electric vehicles’ environmental impact and for decisions on their operational deployment, information about their factors of energy consumption compared to conventional vehicles is needed. This paper investigates the differences between one battery electric and one internal combustion passenger car in terms of their energy consumption in various driving situations. The vehicles were equipped with multiple devices for measuring and recording energy data during operation. On a 42-km test route within and around the city of Erfurt, in Germany, test drives were conducted by a group of drivers in December 2016. Each driver drove both vehicles consecutively as to obtain comparable data. Through specific driving scenarios, the effects of driving style and peak hour traffic on energy consumption are examined as well. Different road types in particular show varying effects on the BEV and the ICV. Our results affirm that the energy consumption of electric vehicles is less sensitive to speed dynamics in urban areas than are conventional vehicles. While the relative efficiency advantage of electric vehicles is at 68 percent in the baseline scenario, it is at 77 percent for urban driving. We could not find significant differences in the BEV’s relative consumption advantages during the peak hours or for aggressive or calm driving.

ABSTRACT. In this paper, we deal with an important real problem relative to logistics in the fuel oil distribution. This problem is known in the literature as PSRP (Petrol Station Replenishment Problem). it consists, under suitable assumptions and subject to certain operational constraints, to define what are the procurement plans of the service stations and especially the deployment plans of petroleum products at refueling stations along a certain planning horizon. The problem to which we refer is known as Vendor Managed Inventory (VMI) and belongs to a class of more general problems called Inventory Routing Problem (IRP), of which it is a particularization. In particular, the aim of this work is to consider a particular variant of the problem, known in the literature as PPSRP (Periodic Petrol Station Replenishment Problem), which draws its concepts from two different classes of distribution problems, the Periodic vehicle routing problem (PVRP) and the Periodic Petrol Station Replenishment Problem (PSRP). To solve this problem we applied different approaches based on heuristics, in order to compare the results and especially assess the effects / benefits that the application of them would lead to the entire supply chain. To compare the heuristics implemented, we used some test cases located on the Italian territory.

ABSTRACT. The capacitated vehicle routing problem with time windows (cVRPTW) is concerned with finding optimal tours for vehicles that deliver goods to customers within a specific time slot (or window), respecting the maximal capacity of each vehicle. The on-line variant of the cVRPTW arises for instance in online shopping services of supermarket chains: customers choose a delivery time slot for their order online, and the fleet's tours are updated accordingly in real time, where the vehicles' tours are incrementally filled with orders.

In this paper, we consider a challenge arising in the on-line cVRPTW that has not been considered in detail in the literature so far. When placing a new order, the customer receives a selection of available time slots that depends on his address and the current (optimized) schedule. The customer chooses his preferred time slot, and his order is scheduled. The larger the selection, the more likely the customer finds a suitable time slot, leading to higher customer satisfaction and a higher overall number of placed orders. We denote the problem of determining the maximal number of feasible time slots for a new order as the Slot Optimization Problem.

We propose several heuristics for both determining feasible and infeasible slots. Our approaches combine local search techniques with strategies to overcome local minima and integer linear programs for selected sub-problems. In an experimental evaluation, we demonstrate the efficiency of our approaches on a variety of benchmark sets and for different time restrictions that are motivated by varying customer request rates.

ABSTRACT. The aim of this paper is to evaluate the quality, perceived by users, of different transport modes in a metropolitan city. To this aim, we have found a framework to aggregate data and information coming from multiple information sources, often characterized by a high level of uncertainty. The proposed method is a hybrid approach based on two different theories: the Analytical Hierarchy Process (Saaty, 1980) and the Evidence- or Dempster-Shafer-Theory(Dempster 1967; 1968; Shafer, 1976).
First, we have carried out a survey to investigate the users’ point of view about the quality of transport, expressed through fifteen criteria, representative of the transport quality. Within the survey, the users were asked to rank the chosen criteria.
Due to the complexity of the transport problem, we have used the Analytical Hierarchy Process to decompose the problem in different levels. Because of the decomposition, we have obtained priority vectors, which we have taken as basic probability assignments for application of the Dempster-Shafer Theory (DST). The DST is used to fuse different users’ opinions and to take into account Uncertainty embedded in human judgment. The results show which alternatives users consider the best in relation to analyzed criteria.

ABSTRACT. Stakeholder engagement is a necessary prerequisite for the success of a transport decision-making process. Besides, complex transport decisions requiring the evaluation of multiple and heterogeneous aspects (e.g. environmental, social, economic) need to be tackled with a multicriteria approach. This paper presents a procedure for the structuring of a decision-making problem and evaluation of the solutions proposed from a multi-stakeholder multi-criteria perspective. Analytic Hierarchy Process (AHP) was used as multicriteria decision technique, while a role-playing game was used to reproduce a participatory process where University students acted as key stakeholders. 
The case study regards the building of a new metro station in Catania (Italy), which will be the closest station to a high-demand district where healthcare and university services and a park-and-ride facility are located. Due to the distance and the high slope between the station and the district, a dedicated transit system linking the two nodes is under study and four different alternatives have been proposed. 
Students were initially informed about the objectives of key stakeholders in order to be able to play the different roles. A hierarchy of the problem was built with them in order to select the best transport alternative and AHP was used to elicit their preferences and evaluate priorities for each stakeholder group. Then, a comparison among mathematical aggregation of priorities and a consensus vote was done to verify the differences between the two alternative rankings and the correspondence with stakeholder preferences. AHP-based participatory procedure proved to be suitable to tackle complexity of transport decisions.

ABSTRACT. Autonomous vehicles are considered as the next major milestone in the history of transportation. Current vehicles are widely equipped with GNSS-based positioning unit and further sensors: cameras, laser scanner, radar-based sensors. These new technologies are capable of not only detecting other vehicles, pedestrians or road obstacles, but of collecting information about the vehicles’ neighborhood. If the vehicle positioning is to be extended by additional environmental information provided by these modern sensors, the available map database has to be prepared to be able to receive such data. This means that map databases have to be extended to 3D and the map content must be improved. Such advanced 3D maps enable to receive, manage and integrate all data collected by the vehicles. These maps can support autonomous vehicle control, since such vehicles must continuously survey their close- and mid-range environment, not only other road users but the partly changing road environment.
The terrestrial and mobile laser scanners are excellent instruments to capture 3D data about roads and their environment. One big problem with the laser scanning is that it results huge point clouds with high geometric resolution, but without any prior selection between more and less important details. Recording the measured points requires high storage capacity. The primary goal of the processing procedure is to extract the relevant content and transform it to useful and storage-optimized format.
The paper discusses a workflow for laser scanned road data processing and demonstrates several autonomous vehicle related use cases in storage, visualization and application.

ABSTRACT. Car drivers are assisted in many ways in perceiving driving conditions. Some of these conditions directly relate to the built environment of the road. The means of assistance include road and traffic signs, information and directional signs, maps, navigational devices, community-based information services. Furthermore, drivers may be also assisted by the on-board traffic sign recognition (TSR) systems. In our paper, we focus on a group of traffic signs and use traffic sign logs to statistically infer the type of urban environment in which the car is being driven. The signs are either seen and logged by a human data collector, or preferably automatically detected and logged by an on-board TSR system. A traffic sign record in the log-file registers the sign type and the along-the-route location. Furthermore, it notes the actual road environment category (e.g., town centre, residential area, industrial/ commercial area). These logs are seen as realisations of an inhomogeneous marked Poisson process, and the minimum description length principle is applied to infer the actual environment. The aim is to encode the current data in the shortest possible way ‒ assuming stochastic models derived from historic data (e.g., marked Poisson processes tuned to the empirical spatial rates of the traffic signs) ‒ and accept the corresponding model and environment as actual. To evaluate the quality of classification, the inferred environment categories are compared to the ground truth data in a manner that satisfies the training and testing separation requirement. Also, the delays experienced in detecting environmental boundaries are analyzed.

ABSTRACT. Urban traffic simulation models could benefit significantly from new validation methods with potential to reduce the time-consuming calibration and validation work needed before application of the model to evaluate city infrastructure or policy implementations. Current praxis is to validate simulation models locally through comparison with point flow measurements and travel times on some important routes. However, for many applications, the level of congestion in an entire area is important. During the last decade, several studies have found empirical evidence of a relation between flow and density on city district level, the existence of a so-called macroscopic fundamental diagram (MFD). This paper shows how the MFD can be used to validate results from a traffic simulation model for a city district. Furthermore, the paper shows empirical results for Stockholm, Sweden.

ABSTRACT. Cities, businesses and governments have recognized the value of Electric Vehicles (EV) in building a cleaner, smarter and more sustainable future. This study is focused on users’ perception of EV and its impact on users’ mobility. The main problem EV users report is its limited autonomy compared to Petrol-Fuelled Vehicles (PFV), a factor causing range anxiety to users.

A 3-months experiment has been conducted in the UPM in order to study the academic population. The sample size is 48 people, equally distributed between men and women, students and workers and private car and public transport users. Every user used the EV for a day and was controlled and evaluated through a customized on-line survey, where different aspects were rated on a scale from 1 to 5.

The main outputs of the analysis of results are: • The general experience of EV drivers has been positive (4,5). • Lack of noise (4,9), acceleration (4,7) and safety (4,6) are the best rated variables. • Autonomy (2,8) and autonomy accuracy (3,8) are the worst rated variables. • 95% of users would pay more for an EV than for a PFV. • Younger people have a higher average consumption than older people.

ABSTRACT. Within the project DESTination Rail, funded by the H2020 programme, a task is dedicated to the development of a tool for rail traffic flow optimization during maintenance work. On a single track line, priority is set for as much work as possible to be done in one time slot between two trains; moreover, there are even cases of the timetable modification for the more efficient maintenance work. For the developed bottleneck section, it is of great importance to have an efficient usage of capacity, for which mathematical framework called Kronecker Algebra has been selected as a methodology for the optimization of the speed profile of approaching trains. By adjusting the timetable and speed profile, trains are enabled to pass the bottleneck section exactly at the allowed speed limit to keep occupation time as short as possible and minimize energy consumption. The application of this algorithm will be shown on the case study of Northern line on the Irish railway network where energy consumption was reduced by 3% using optimization of the driving strategy. Finally, using Kronecker algebra, optimal timetable with the minimal delays during maintenance work on one section has been constructed.

ABSTRACT. Petri nets are used in this paper to estimate the indirect consequences of accidents in a railway network, which belongs to the class of the so-called transportation Critical Infrastructures (CIs), that is, those assets consisting of systems, resources and/or processes whose total or partial destruction, or even temporarily unavailability, has the effect of significantly weakening the functioning of the system. In the proposed methodology, a timed Petri net represents the railway network and the trains travelling over the rail lines; such a net also includes some places and some stochastically-timed transitions that are used to model the occurrence of unexpected events (accidents, disruptions, and so on) that make some resources of the network (tracks, blocks, crossovers, overhead line, electric power supply, etc.) temporarily unavailable. The overall Petri net is a live and bounded Generalized Stochastic Petri Net (GSPN) that can be analyzed by exploiting the steady-state probabilities of a continuous-time Markov chain (CTMC) that can be derived from the reachability graph of the GSPN. The final target of such an analysis is to determine and rank the levels of criticality of transportation facilities and assess the vulnerability of the whole railway network.

ABSTRACT. In case of railway disruptions, the whole railway traffic will be impacted in a large area and for a long time. There are three stakeholders in railway disruption management process that cannot be neglected: passengers, train operators and infrastructure managers. Infrastructure managers are mainly responsible for operational feasibility of the rescheduled timetable. Train operators aim at minimizing operation costs and maximizing the services offered to passengers. Passengers’ needs are an important evaluation for rescheduled timetable in railway disruptions. Since the three stakeholders have diverse and even conflicting objectives in the disruption management process, how to handle the trade-offs of these objectives deserves further discussion. This paper summarizes the possible methods to solve the holistic rescheduling process including passengers, train operators and infrastructure managers in railway disruptions. Specifically, this paper discusses two reschedule process and compare their pros and cons. This research links passengers, train operators and infrastructure managers in the rescheduling process of disruption management. It is the base for solving the trade-offs of different objectives of stakeholders.

ABSTRACT. Using mathematical methods to support the yearly timetable planning process has many advantages. Unfortunately, the train timetabling problem for large geographical areas and many trains is intractable for optimization models alone. In this paper, we therefore present a MILP-based heuristic that has been designed to generate good-enough timetables for large geographical areas and many trains. In the incremental fixation and release heuristic (IFRH), trains are added to the timetable in batches. For each batch of trains, a reduced timetable problem is solved using a mathematical integer program and CPLEX. Based on the solution, the binary variables defining meeting locations and stops are fixed, and the next batch of trains is added to the timetable. If previously fixed variables make the problem infeasible, a recovery algorithm iteratively releases fixed variables to regain feasibility. The paper also introduces a simple improvement heuristic (IH) that uses the same idea of working with batches of trains. The heuristics are tested on a real case-study from Sweden consisting of both small problem instances (approximately 300 trains and 1400 possible interactions) and large problem instances (approximately 600 trains and 5500 possible interactions). IFRH returns a feasible timetable within 30 minutes for all problem instances, and after running IH the optimality gaps are less than 5%. Meanwhile, if CPLEX is used without the heuristic framework to solve the total optimization problem, a feasible timetable is not returned within 2 hours for the larger problem instances.

ABSTRACT. In the paper the modeling and the analysis of the multi-class traffic flow, focusing on the cruising of the look-ahead controlled vehicles is presented. The look-ahead controlled vehicles optimize their speed profile based on the energy consumption and traveling time minimization performances, considering the forthcoming terrain characteristics, speed limits and traffic environment. Therefore, the speed profile of the look-ahead controlled vehicles can significantly differ from the speed selection strategy of the conventional vehicles. The increasing number of cruised controlled vehicles can modify the dynamics of the traffic, the average speed and the critical density/speed parameters. Moreover, the cruising of the numerous look-ahead controlled vehicles can have an impact on the energy consumption of the vehicles in the entire traffic. The paper presents a the modeling and analysis of the mixed-traffic based on various simulation scenarios. During the analysis the high-fidelity VISSIM software is used, by which the effect of the look-ahead vehicles on the traffic is examined. The contribution of the paper can be used in the coordination of the look-ahead controlled vehicles and the traffic control systems.

ABSTRACT. In traffic engineering, the most established procedure to describe the (activity-specific) demand is to subdivide the study area into single units called traffic zones. While estimating origin-destination (OD) demand flows usually requires a large amount of data, nowadays a key issue in traffic engineering is to estimate the trip purpose while protecting user privacy. The aim of this work is to derive from macroscopic and aggregate information production distribution for each traffic zone of a system, with a trip-purpose specification. 
In this work, we suggest novel procedures for estimating the production factors, which make better use of the precision level of the available information. If time-dependent demand data are available, such as the preferred departure time for each zone, the production factor can be estimated through a simple Monte Carlo simulation model. Otherwise, we propose a Markov Chain Monte Carlo (MCMC) approach to approximate a set of functions that describe the production of trips with regard to one specific zone along the day. This algorithm requires a lower level of information and computes the likelihood with regard to the number of generated and attracted trips. Even if static data are the sole source of information available, MCMC can still provide reasonable results, although the precision level will strongly decrease. 
Using dynamic/static OD matrices, the model can be used to identify purpose-dependent demand flows. Moreover, this methodology can provide the missing inputs for various other models, which require a more detailed dataset to estimate activity patterns on a daily basis.

ABSTRACT. At weaving segments, traffic merges, diverges, and weaves in a limited space. These traffic maneuvers might result in high crash hazards. To improve the safety of a congested expressway weaving segment, this study tested several variable speed limit (VSL) strategies in a well-calibrated and validated microsimulation (VISSIM). Ten simulation runs’ worth of results showed that 96.4% of the simulated volume were consistent with the filed volume, and 86.46% of the simulated speeds were less than five mph different from field speeds. The VSL was activated in simulation only when the traffic was in hazardous conditions, and the status of VSL was updated every 5 minutes. Crash odds and conflict count were used to evaluate the impact of VSL strategies on traffic safety. The crash odds were calculated based on a real-time safety analysis model for weaving segments, and conflicts were obtained by processing the VISSIM vehicle trajectory file in the Surrogate Safety Assessment Model (SSAM). The results showed both the location and the speed value of VSL were important. The VSL installed at the upstream of the weaving segment better enhanced the safety than the VSL set at the downstream. Meanwhile, the 45 mph upstream VSL improved safety more than the 50 mph VSL did. Therefore, compared to other VSL scenarios, the 45 mph upstream VSL was the best in improving the safety of the congested weaving segment. It decreased crash risk and conflict count by 18.0% and 18.4%, respectively.

ABSTRACT. We present a real-time traffic state estimation algorithm for motorways. Natural constraints on the variables, like practical bounds on densities and velocities, are incorporated in the estimation process aiming to obtain better estimation results.
The dynamic equation for the evolution of the traffic is defined by a second order macroscopic model which computes the density, the flow and the mean speed according to several nonlinear equations, but nothing avoids the results being out of those practical bounds. Different extensions of the Kalman method were already applied to this problem, but none of them consider natural constraints in the variables. On the other hand, general filter methods have been designed to cope with a constrained state. 
In order to incorporate the natural constraints of the traffic model, we adapt one of those methods based on the Unscented Kalman Filter. To validate the approach, many simulation cases over a freeway section were made using a microscopic simulation tool and comparing the Extended Kalman Approach with the proposed one.

ABSTRACT. Fuel consumption and atmospheric pollution emissions of vehicles depend on driving conditions, the characteristics of the driver and the car. The influence of driving style on the environmental aspects of a car journey has been investigated. Driver characteristics were determined by a Driver Behaviour Questionnaire and observed acceleration and deceleration behaviour. That results in four types of drivers with similar characteristics within a type group. We measured 56 trajectories of 28 drivers using GPS devices. The measurements were done on a route of 8.4 km in an urban environment in Chengdu (PR China). From the trajectories, the emissions and fuel consumption were determined with the Comprehensive Modal Emissions Model. The results were related to the traffic control along the journey resulting in fuel consumption and emissions per stop and per second idling.
There are significant differences in saturation flow, emissions and fuel consumption between different driver types. Cautious, novice drivers have the lowest emission and fuel consumption and give the lowest saturation flow and have the lowest cruise speed; experienced smooth driving drivers give a high saturation flow while keeping fuel consumption and emissions also low. Aggressive experienced drivers have a high saturation flow and fuel consumption / emissions. Therefore, microscopic traffic models that simulate emissions and fuel consumption should take the differences between driver types into account.

ABSTRACT. An integrated monitoring platform (IMP) was developed for real-time monitoring of traffic flows and related air pollution in urban areas. The IMP includes: (i) an air quality monitoring unit, integrating the “Arduino” open-source technology with low-cost and high-resolution sensors, to measure air pollutant concentrations; (ii) a traffic monitoring device, equipped with a camera sensor and a video analysis software, to detect vehicles’ counts, speed and category; (iii) a spatial data infrastructure, composed of a central GeoDatabase, a GIS engine, and a web interface, for data storage and management. The IMP was tested in Florence (Italy) by installing sensor devices at a road site where a 1-year measuring campaign was carried out. A reference meteorological station in the city centre was used to provide observations of wind speed and direction, air temperature, and relative humidity. 
In this work, a statistical analysis was performed to investigate the influence of local road traffic and meteorological conditions on CO, NO2 and CO2 concentrations. Two different methods were applied: a linear regression model and an artificial neural network. To investigate the role played by emissions from road traffic, the influence of all drivers by period of the year (cold vs. warm months) and day of the week (weekdays vs. weekends) was analysed. As a result, the contribution of local road traffic on pollutant concentrations proved to be lower than meteorological parameters.

ABSTRACT. The reduction of energy consumption has gained significance in the past years as energy prices have been continuously increasing. Advances in railway telematics and the large amount of data obtained from train services enable the development of methods that are capable of further improving energy efficiency through the evaluation, control or prediction of energy utilization of the railways.The paper presents the results of a statistical analysis in which the rate of the possible energy savings is calculated using the on-line telemonitoring system data. During the analysis one month real train data was processed from the MÁV Electronic Logbook System, narrowing the data to the electric locomotives.
First a general statistical analysis is introduced to show the deviation of the energy consumption of trains running under the same conditions using a sufficiently large sample. In order to compare the individual train runs properly the train load has been taken into consideration, i.e. to evaluate the real energy consumption of the runs the effect of mass parameter should be taken into account. Next important question is whether only the traffic situation or also the human factor plays role in the energy consumption. The same dataset was analysed as above, but with considering the differences between the engine-drivers. The research has ended with the analysis of some sections microscopically. For this purpose, sections with relatively busy schedule table and large amount of data were chosen. Several parameters on the consumption were examined such as total journey time and the number of stops.

ABSTRACT. Currently, the single wagonload (SWL) traffic in Europe is at risk of disappearance. Nevertheless the European single wagonload traffic is required to attract more freight to rail. Especially, the incumbent railways have lost large transport volumes. Thus, they reduced their fleet and outsourced the wagons to private leasing companies to cut off costs. The new market entrants often have an asset light business model which includes the leasing of the required wagons. Expectedly the fleet of the wagon leasing companies has increased. Two market related conditions here are of utmost importance: Firstly the customer’s ease of access to competitive services at one single place. Secondly, the allowance of cooperation traffic between various rail market companies to organize international SWL transport is jeopardized. This regulatory condition comes in way of offering competitive complete services for single wagon load traffic. Thus, this paper proposes formulation of a neutral third party service provider formed by wagon lessors and other partners. A concept to consolidate international single wagon load traffic is introduced. This allows an easy access to customers for buying remaining wagon capacities. Thus, additional revenues will be generated and the economic sustainability of international single wagon load traffic for all stakeholders will be improved. This also fulfills the goals of EU policies on modal shift.

ABSTRACT. In this work a two level heuristic algorithm is described for a nearly real-time multi-vehicle many-to-many Dial-A-Ride Problem (DARP). This algorithm is ready to support a Demand Responsive Transportation System in which we face the problem of quickly evaluate a good-quality schedule for the vehicles and provide fast response to the users. The insertion heuristic is double dynamic nearly real-time and the objective function is to minimize the variance between the requested and scheduled time of pickup and delivery. In the first level, after a customer web-request, the heuristic returns an answer about the possibility to insert the request into the accepted reservations, and therefore in a vehicle schedule, or reject the request. In the second level, during the time elapsed between a request and the following, and after a reshuffling of the order of the incoming accepted requests, the same heuristic works for the whole set of accepted requests, trying to optimize the solution. We intensively tested the algorithm with a requests-generating software that has allowed us to show the competitive advantage of this web-based architecture.

ABSTRACT. Effective urban traffic management requires knowledge about current situation and tools to transfer information between local authorities and transport systems users. From this point of view individual user route planning should correspond with general traffic flow management. During recent years significant increase of interest of web-based travel planners was observed.
Authors suggest to connect above issues. By the reason Green Travelling Planner (GT Planner) was implemented. The tool among others allows to optimal route planning (four optimization criteria: quicker, shorter, cheaper and greener) using one of eleven travel modes (includes multimodal combinations). It may be use as official urban multimodal travel planner and can be controlled by local authorities. Heuristic approach which was implemented in GT Planner make possible to support urban traffic management by adding specified factors as attributes of links in graph of transport network. This solution can also be use to optimize of transport systems and public transport planning based on actual travel needs collected as Big Data during GT Planner usage. 
Examples provided in the article are based on partial results of the international project entitled “A Platform to analyse and foster the use of Green Travelling options” implemented under the ERA-NET Transport III Future Travelling programme and financed by the National Centre for Research and Development.

ABSTRACT. In recent years the concepts of carpooling and car-sharing have become popular research topics, both in passengers’ and freight transportation. In this paper, the authors develop a hybrid computational procedure that solves a joint multiple criteria problem of matching carpoolers and planning their common routes, formulated in the authors’ previous work. The solution procedure is a combination of Dijkstra algorithm (routing component) and an original, problem-specific heuristic method (carpooler’s matching component). While solving the routing problem the authors aggregate all the considered criteria by a weighted scalarizing function and then apply Dijkstra algorithm to generate rational routes, most satisfactory for all stakeholders (drivers and passengers). In this phase the stakeholders’ preferences concerning all considered criteria are defined through the application of one of the MCDM/A methods (e.g. ELECTRE, AHP) and used in the definition of the aggregated quality index. The authors propose a carpooling – specific decomposition of the original decision problem to speed up the solution procedure. The decomposition method is based on agglomerative clustering, which involves splitting carpoolers into specific groups featured by certain characteristics (geographic location, social preferences, etc.). It is assumed that each group must contain at least one driver. The decomposed problem is solved separately for each group of carpoolers. The proposed approach is tested and a comprehensive analysis of the generated results is presented. The developed software is organized as a computer-based DSS that helps both drivers and passengers searching for rational carpooling solutions.

ABSTRACT. Developing traffic control strategies taking explicitly into account the route choice behavior of users has been widely recognized as a very challenging problem. The inclusion of user behavior in optimization based control schemes introduces strong irregularities in the solution space shape, such as non-convexity and non-smoothness. In this work, we continue our effort to reduce this problem’s complexity by extending our previously developed optimization and decomposition scheme. We achieve this by including in its formulation a heuristic component, aiming at regularizing the solution space’s shape and structure.
In our own previous papers we address problem size reduction for the specific instance of anticipatory traffic control, that is the situation in which the underlying traffic model includes user behavior - specifically their route choice - together with flow propagation dynamics. We achieved this by performing a controller-wise decomposition and discussed conditions under which the proposed scheme is globally convergent. 
In this work, we extend the aforementioned scheme by including explicit considerations on how route choice behaves under different situations. Specifically, we employ a reformulation of the anticipatory traffic control problem subject to User Equilibrium, in which specific constraints are included so to guide the optimization towards a specific region of the underlying route choice solution space, that pertaining to System Optimum. Through this approach, we aim at regularizing the solution space’s shape and structure, such that gradient based optimization techniques can successfully reach significant optimal points regardless of the initial conditions. The technique is validated through simple test case scenarios.

ABSTRACT. Free flowing speed data are used in the geometric design consistency evaluation of highways. Video based data acquisition technique can be used for the purpose. In this, the vehicle speed is estimated from the travel time to cross known trap length. Now, the accuracy of the speed data depends on the frame rate of the camera and trap length. The maximum possible error in estimating the travel time to cross known trap length is one frame and its effect on vehicle speed estimation decreases with increase in trap length. However, observation (parallax) error increases with trap length. So it needs optimization for all of these factors. For speed based geometric design consistency evaluation, vehicles need to be classified and tracked. Further, in four-lane median divided highways, the vehicle needs to be monitored for the presence of other vehicles in the adjacent lane. The video log helps in vehicle tracking, vehicle classification, identification and monitoring free flow conditions along a stretch. A field study is conducted with varying trap length to come up with the optimum values. Also a video based data acquisition setup has been proposed to evaluate speed based geometric design consistency of four-lane median divided horizontal curves. Finally, data set from video recording technique have been compared with standard data set and no significant difference obtained.

ABSTRACT. Entry-only Automatic Fare Collection (AFC) systems are widely used in urban transports. Its main advantages include easy usability by passengers, improvement of the efficiency of revenue management, adequacy to integrate inter-modality approaches, easy cooperation between operators, systematic data collection and gathering tools, contributing to improve the planning process. This work starts with the literature review on applications of the Trip-Chaining Method (TCM) to the estimation of Origin-Destination (OD) matrices using entry-only AFC data. The main contribution of this study is to provide an OD matrix for the city of Porto, allowing to improve the quality of its public transport system. The paper reports the implementation of the TCM to estimate the alighting locations at the disaggregated level in the case study of Porto. The main assumptions adopted are: passengers start the next journey stage at or near the alighting location of their previous trip, passengers end the last trip of the day at the boarding location of the first trip of the day, passengers can only alight in the sequence of stops not yet traveled by the route / direction they boarded, passengers have a maximum interchange distance, above which the destination of that journey stage is not inferred.

ABSTRACT. A study is executed on the possibilities of utilizing traffic data from cameras with Automated Number Plate Recognition (ANPR), connected data from probe vehicles with GPS and loop detectors in an urban area. Afterwards, the methodology of enhancing data quality is explored.
In practice, empirical traffic data are not complete and only partially valid and the driver population is not homogenous.
Data analyzed in this paper are from three kinds of sources from the CBS of Changsha (P.R. China): ANPR cameras, loop detectors and probe vehicle data from taxis. By applying data cleaning and data completion methods, the flows and travel times between intersections are determined from the multi-source data. 
Travel time reliability, as defined by the standard deviation and the skewness of the travel time distribution, is rather sensitive to outliers. This is often caused by drivers who have an intermediate stop between two observation points. A method has been developed to identify and remove the outliers. After the elimination of the incompatible travel time, the relation between the empirical standard deviation and skewness has been determined as a function of traffic characteristics. 
The different data sources show an empirical Macroscopic Fundamental Diagram where the congested traffic states don’t have a decreased network flow, which was explained by the queue management of the local traffic police. The cleaned and fused data are useful inputs to the calibration of simulation programs.

ABSTRACT. Although examination of pedestrian origin-destination (OD) relations of enclosed areas such as pedestrian zones, underpasses and transport hubs is a key point in designing such infrastructure, a very few efficient methods are known in literature. This paper introduces a novel survey technique for this purpose called PFS (Pedestrian Following Survey).
The main principle of PFS method is that survey personnel follow randomly chosen pedestrians without any disturbance and record their routes through the investigated area (as well as some additional data). After the observed pedestrian leaves the area (at an egress point) the surveyor chooses a new pedestrian to follow from a nearby access-point. Collected data form a sample for pedestrian movements, similarly to floating car data in road transport.
After comparing PFS method to well-known survey types the mathematic model of relation between the sample and total OD matrices is described. Then results of completed surveys applying PFS method are presented. These surveys were organized at Móricz Zsigmond circus which is a major transport hub in Budapest, Hungary, and were carried out by university students.
Calculated OD matrices are validated by traffic volumes of particular public transport stops and cross-sections collected from other surveys. Experience shows that PFS method can be applied with success and can provide data efficiently compared to other OD survey types.

ABSTRACT. In the last decade, many papers focused on the study of the variability of passenger journey time in multimodal transport networks in cities on an aggregated level. Unfortunately, among this considerable body of research, only few papers account for passenger underlying walking factors, named walking speed and walking distance, in mass transit stations on a disaggregated level. Our recent research tried to overcome this drawback by modelling a uniform-distributed walking speed in a general stochastic model along a mass transit line. To optimize our previous model, a new model M1 (a normal-distributed walking speed) is confronted with the previous models M2 (a uniform distribution) and M0 (fixed value). A global comparison approach is proposed to compare the three models from numerical analyses, model framework to real case study. Numerical analyses of the analytical formulae hold for detailed comparisons for each part of the stochastic model. The closed-form formula of the general function in M1 is reduced to 5 pieces. On the contrary, M2 involves 17 different pieces. The stochastic models’ frameworks based on Maximum Likelihood Estimation are then given. The real case study of the busiest express rail transit line RER A in Parisian region is applied based on the AFC and AVL data with standard statistical features analyses of the basic distributions, yielding a better model.

ABSTRACT. The standard timetabling process used today is challenged by both congestion on the railway tracks and an increasingly dynamic railway market. Many operators know their transport demand very short in advance and thus have trouble to get train paths in the timetable. The timetabling process is also accused of being unfair and inflexible. The deregulation of the railway network has enabled a more market based timetabling process which can improve the situation. In this paper, we suggest a process for dynamic pricing of track capacity. The suggested process includes a method for calculating the supply of capacity for a certain train path application and another method for representing forecasted, future demand for train paths in the timetabling process. These models make it possible to apply techniques for dynamic pricing on the timetabling problem to find a market based price of a train path. Track capacity in high demand will thus get a higher price than less requested times and tracks, thus encouraging operators to avoid to apply for train paths to be operated during the most congested hours of the day. Subsequently, the congestion is reduced and the timetabling process will be fair and flexible. The dynamic pricing process is implemented in a test case for a 87 km track in the Swedish railway network, consisting of both single and double track sections.

ABSTRACT. The significant growth of pedestrian flows through stations of mass public transport has turned the two issues of passenger comfort and safety into major concerns for railway station operators. Managing these issues is a challenging task due to the complexity of in-station pedestrian facilities, of passenger behaviors and of train and railway operations. Therefore, station management can no longer be limited to the management of train traffic. Several research studies have been developed in recent years that aim to evaluate pedestrian infrastructure within railway facilities by monitoring pedestrian flows and/or modeling them (“crowd dynamics” models). However, the way from these studies to the management of train stations remains to be paved. This paper brings about a framework for station manager information with special focus on passenger flows. We put forward a set of indicators for system state analysis in real time, including notably (i) dynamic cartography of passenger traffic with congestion assessment (taking into account the specific micro-local features of the facilities), (ii) predictive traffic cartographies under a range of pre-defined scenarios, (iii) demand index (daily or finer) and quality of service index over a set of predefined paths within the station, (iv) the minimum time for station evacuation on the basis of passenger load current or predicted – in connection to risk assessment. We also address (i) observation requirements and the toolbox available for measurement, (ii) simulation requirements for real-time situation assessment and decision-making, (iii) the toolbox of action levers and their respective range of application.

ABSTRACT. The variability in passengers’ waiting times in urban mass transit is significant at the trip level since it ranges from some dozen seconds to half headway. Despite the attention paid so far to individual wait times in urban transit systems, a related issue seemed to remain unexplored: the re-use of wait time for passenger repositioning along the boarding platform. The paper is focused on passenger wait time on urban railway platforms and its re-use for longitudinal repositioning on the boarding platform in order to save on walking time at the egress station. Building upon our stochastic model of passenger’s individual journey time between access and egress stations, we refine the representation of the on-platform phases and their potential coupling, since a passenger’s relocation along the access platform influences the egress situation. In the new model, the stochastic features pertain to (i) the distribution of walking speed among passengers, (ii) the distribution of repositioning times in relation to that of the residual time between passenger arrival and train departure at the station of passenger boarding, (iii) the distribution of in-station distances between the station access/egress points and the platform. Analytical properties are obtained, including the Probability Density Function of Tap-In, Tap-Out time pairs. The analytical formulas for normal distributed speeds and shifted exponential distributed distances in stations are tractable. This enables for maximum likelihood estimation. A real case study of urban rail transit line RER A in Parisian region is addressed, yielding reasonable results for heterogeneous and homogeneous scenarios.

ABSTRACT. Modeling and simulating activities in and around train stations is a challenging task. Indeed, it implies the consideration of a dynamic and heterogeneous set of actors, obeying to different rules and control systems. In this paper, we propose a multi-agent model for such simulations. The proposal comprises three parts. The first part is a multi-agent simulation model of travelers together with their interaction with the station platform. Passengers adapt their behavior to the other travelers while pursuing their travel objective, and in interaction with the available information sources, either local at the station, or personalized (through their smart phones for instance). The modeling of this traveler’s information system is the second part of the model, where transportation operators are able to define strategies regarding the type of information to be provided, their frequency, and the medium used to broadcast it. Finally, the third part of the model is the management platform of the train station, which monitors both trains and pedestrians behaviors in the station. The platform is responsible for the optimization of the traffic fluidity and passengers’ safety and proposes actions related to crowd deviation and access control. The architecture advocates for a closed-loop modeling between the simulation, the train station management and the traveler information, allowing for the testing of whole control systems instead of specific strategies.

ABSTRACT. In this paper, we propose a method of automated vehicle operation in taxi systems that addresses the problem of associating trips to automated taxis (ATs) and assigning those vehicles to paths on an urban road network. This system is envisioned to provide a transport service within a city area with a seamless door-to-door connection for all passengers’ origins and destinations. ATs can drive themselves on the roads with reduced direct human input, which allow taxis to satisfy the next trip or park themselves while waiting for a request if needed. We propose an integer programming model to define the routing of the vehicles according to a profit maximization function while depending on dynamic travel times which vary with the flow of the ATs. This will be especially important when the number of automated vehicles circulating on the roads is so high that will cause traffic congestion. The total profit involves the system revenue, vehicle fuel costs, vehicle depreciation costs, parking costs, penalties for unsatisfied trips and passengers’ congestion delay. The model is applied to a small case study and the results allow assessing the impact of the ATs movements on traffic congestion and the profitability of the system. Even with a small case study, it is possible to conclude that having in consideration the effect of the vehicle flows on travel time leads to different results in terms of the system profit, the parking cost and the driving distance which points out the importance of this type of models.

ABSTRACT. This paper presents issues, trade-offs and challenges encountered while developing a UK national transport model as part of a large interdisciplinary project, ITRC MISTRAL. The Infrastructure Transitions Research Consortium (ITRC) is a consortium of seven leading UK universities focusing on analysis of national infrastructure systems using a system-of-systems approach. In this paper, we describe a multi-modal multi-scale national transport model being developed by ITRC which includes passenger and freight transport via highways, railways, airports, seaports and local transit networks. The model predicts future demand for each mode on individual flows using an elasticity-based simulation approach. These flows are then assigned to transport networks to assess infrastructure capacity utilisation and obtain new estimates of inter-zonal travel times. The model explicitly considers cross-sectoral interdependencies with other infrastructure networks, including the energy sector (where transport is the largest consuming sector), digital communications (which provide bandwidth to passengers and enable smart mobility), waste management (which requires transport services) and water supply (where flooding poses a major risk of transport disruptions). It is also planned to be capable of estimating environmental emissions and assessing the vulnerability and resilience to risk of transport systems. The enhanced transport model discussed here builds on an existing modelling framework which has been used by the UK government to inform their National Infrastructure Assessment. As such, the model has the potential to support policy making with regards to infrastructure investment on a decadal scale, under a range of possible future scenarios including population growth, new technologies and climate change.

ABSTRACT. Natural and man-created disasters, such as hurricanes, earthquakes, tsunamis, accidents and terrorist attacks, require evacuation and assistance routes. Evacuation routes are mostly based on the capacities of the road network. However, in extreme cases, such as earthquakes, road network infrastructure may adversely be affected, and may not supply their required capacities. If for various situations, the potential damage for critical roads can be identified in advance, it is possible to develop an evacuation model, that can be used in various situations.
This paper focuses on the development of a model for the design of an optimal evacuation network which simultaneously minimizes retrofit costs of critical links (bridges, tunnels, etc.) and evacuation time. The model considers infrastructures' vulnerability (as a stochastic function which is dependent on the event location and magnitude), road network, transportation demand and evacuation areas. Furthermore, the model evaluates the benefits of managed evacuation (system optimum) when compared to unmanaged evacuation (user equilibrium).
The paper presents a mathematic model for the presented problem. However, since an optimal solution cannot be found within a reasonable timeframe, a heuristic model is presented as well. This heuristic model is based on evolutionary algorithms, which also provides a mechanism for solving the problem as a multi-objective stochastic problem.
Using a real-world data, the algorithm is evaluated and compared to the unmanaged evacuation conditions. The results clearly demonstrate the advantages of managed evacuation, as the average travel time can be reduced by 5% to 30%.

ABSTRACT. Urban regions account for 64% of global primary energy use and 70% of carbon emissions. For that reason, options to decarbonize urban environments are receiving increasing attention. Public transport shall play a key role in decarbonizing urban road transport. One efficient way is shifting towards clean fuels and modern electric buses which can be seen already in several cities around the world. However, barriers related to planning and investing in charging infrastructure hinder a faster development. In this paper, a dynamic optimization model for establishing charging infrastructure for electric buses is presented, using Stockholm, Sweden, as a case study. The model uses daily bus timetables for optimizing the chargers’ location as well as their time of operation over a full day. It also identifies the optimal technology type for the buses: conductive or inductive. The electric buses compete with buses run on biogas or biodiesel. Furthermore, the model minimizes the total cost and/or the energy consumed in the bus network over a day. The results indicate a charging time of two minutes on average for most of the stations selected. Most of the chargers are concentrated in public transport hubs, which is positive from the point of view of investments, as a high use to idle time ratio is ensured for chargers in these locations. However, such a solution would require scheduling adjustments and careful planning for the density of charging occasions. This model serves as a tool for simulating real-operation conditions including dynamic aspects for electric bus networks.

ABSTRACT. Limited range compared to conventional vehicles is still a significant barrier for drivers. Therefore, development of charging infrastructure is required based on the charging demands. The aim is to increase vehicle miles using electricity, relieve range anxiety and reduce inconvenience concerning charging process. The research question was, where to install the charging stations in order to facilitate the long-distance travels and to meet the urban (local) demands considering both the existing stations and the installations are to be realized by legal regulations. We have elaborated weighted multi-criteria methods for both the national roads and the counties or districts. Several demographic, economic, environmental and transportation-related attributes, as well as the available services (points of interests) that influence the potential for charging station use, have been identified and their effects have been revealed in system approach. On the national roads point-oriented assessment, whereas in urban environment territorial unit-oriented assessments have been applied. On the national roads, the existing petrol stations as prospective charging stations have been investigated. The strategic points (nearby border stations and capital city) as mandatory charging stations have been also designated. The methods have been applied to Hungary (on level of national roads) and to Újbuda (11th district of Budapest, on urban level).

ABSTRACT. Implementation of the car traffic and parking restrictions is one of the most controversial aspects of the urban transport policy. Such initiatives frequently meet with the opposition of the local user groups. These changes affect not only private car users, but also shopkeepers and restaurant owners, who are afraid of the income decrease. On the other hand, these solutions, typically introduced in the city center, improve the public transport vehicles flow, enhancing its competitiveness, and increase the public space attractiveness. Nevertheless the public awareness of the restrictions positive effects is low and it is important to show that their introduction brings benefits for the inhabitants and visitors and does not cause negative owners’ income changes. The paper presents the results of the research carried out to evaluate the impact of car restrictions implemented in several locations in the Krakow City center. The survey was conducted among customers and owners of the facilities located in the area of implemented changes. The results show that a very small percentage of customers has accessibility problems and they are mostly related to the traffic congestion. Satisfaction with the public space quality is declared by approx. 80% of customers. The vast majority of owners do not want to restore the previous situation and their income remained at similar level. This is also confirmed by the Krakow Tax Office. The clients get these areas mostly on foot or by public transport, but the public transport trip percentage perceived by the owners is lower than in reality.

ABSTRACT. PEDIBUS, also known as "walking-school-bus", is a popular system in Western countries aimed at increasing the percentage of children walking to school and reducing vehicular congestion at primary school gates, besides providing informal teaching of pedestrain safety rules, increased exercicing and social interaction, and legitimating walking as a means of mobility.
In its simplest version, a PEDIBUS line is a sequence of stops starting from a child home, visiting a sequence of other children's home, and ending at the school.
Given a set of locations (children homes and the school) and the distance between each pair of locations corresponding to the shortest safe pedestrian itinerary, the objective is to design a minimum number of lines rooted at the school, so that each stop belongs to a line and the distance from school to each stop along the line is below a given threshold.
This objective function is due to the requirement of two supervising adults for each line, which may impair the service long term viability if not handled.
Since the itineraries must be re-designed each year, whenever the pupils set changes, a decision support tool must be provided to the school board in charge of service management to solve this challenging optimization problem.
A few heuristic solution approaches have been proposed in the literature, based on similarities to the school bus routing problem. 
We propose an exact approach exploiting an ad hoc arc based network design model and present results for realistic data for the city of Ferrara, Italy.

ABSTRACT. For future’s highly automated road vehicles, dynamically feasible, comfortable, and customizable trajectories must be planned in order to ensure the maximum level of road safety and passenger satisfaction. The planned trajectories then have to be followed by the vehicle, which means that they must be applicable as reference signals for the trajectory tracking controllers of the vehicle. To fulfil these requirements, a constrained nonlinear optimization based trajectory planning method can be applied, which is generating the trajectories by the model-based prediction of the vehicle’s motion. The evaluation of vehicle dynamics in closed loop with the trajectory tracking control can also allow the direct planning of controller reference signals. The aim of this paper is to investigate the sensitivity and robustness of such a trajectory planning method based on simulation results, taking special account of the impact of deviations from normal operating conditions such as rapid changes in road surface. Firstly, the inspected trajectory planning algorithm is described. Then the performance of the method is examined in terms of changes in the parameter values of the applied model of vehicle dynamics and the optimization problem setup. The deviations between the planned and actually travelled trajectories are also inspected in case of different nominal and actual vehicle model parameter values. Finally, the performance, sensitivity, and robustness of the presented trajectory planning algorithm is evaluated based on the simulation results, and the conclusions are summarized.

ABSTRACT. Recent research shows every so often upcoming cases of dangerous accidents happening at jam tails so that the introduction of a proper warning system is helpful to alleviate the problem. Since traffic is a highly dynamic and complex system of spatiotemporal patterns one has to have an outright understanding of the underlying phases of the real traffic to make a qualified assertion when a dangerous jam tail in a traffic pattern occurs. Kerner showed with the three-phase traffic theory an alternate approach of traffic modeling to the classical theories based on the fundamental diagram. With the help of splitting traffic into three distinct phases: free flow, synchronized flow and wide moving jams, potentially dangerous situations can be detected and identified.

We illustrate an approach of identifying critical jam tails based on microscopic FCD and the three-phase traffic theory. With the sheer amount of vehicle probe data available today we developed a process to identify jam fronts and detect critical jam tails. With this knowledge a system to generate jam tail warnings is proposed.

It is further discussion if and how automated and autonomous vehicles can use this information to adapt the behavior to a more safe and comfortable assisted braking.

ABSTRACT. Autonomous vehicular technology significantly stresses the issue of safety. Although the use of driverless cars raises considerable expectations of a general improvement in safety, new challenges concerning the safety aspects stem from the changing context. On the one hand, the paper addresses regulatory issues raised by the impact of technological changes, particularly standardization problems. On the other hand, the issue of liability questions is investigated as it might cause today’s main legal obstacle for the wide spreading of autonomous cars, especially as autonomous cars might jeopardize the existing approaches to vehicular liability. The aim of this paper is to scrutinize the basic problems in both fields. We provide what, at the current state-of-the-art, appear to be reasonable recommendations from the perspective of technological regulation and law, in order to deal with the main problems that might hamper the development of autonomous transport technology.

ABSTRACT. Technology of autonomous vehicles (AVs) is getting mature and some types of autonomous public transportation have been successfully tested. However, the replacement of conventional public transportation requires new planning and operational methods. The research questions were how to designate stops, routes, operational time, travel frequency and how to model the seat reservation process in order to satisfy personal requirements of travelers. As the operations of the new transportation system is to be derived from the user demands it has been investigated and described in detail, which was the base of the demand-capacity coordination method. Both the preliminary capacity planning and the real-time coordination methods have been developed with special focus on the required data structure and the information management processes. The methods are to be applied during creation of this advanced, high quality mobility service.

ABSTRACT. The development of cities and transportation systems of the last few years made possible to expand the range of individuals, giving them the opportunity to locate their residence far away from the places where they carry out daily activities. The ability to make long journeys has become more and more an essential condition for access to the opportunities of the territory.

This necessity can be connected to transportation social need, which scholars defines both in terms of people requiring a public transportation service and number of trips they would make if they had minimal limitations on their mobility; accessibility refers to the ease of reaching goods, services, activities and destinations, which together are called opportunities. 

This research presents the application of a measure of transportation social need and measures of accessibility for the city of Catania, in Italy. The measure of transportation social need, based on transportation and social disadvantage indicators, has been evaluated with reference to Italian national statistical institute zonation of the city. Accessibility measures, considering different modes of mobility, both private and public transportation and evaluating the ease of reaching desired destinations, have been calculated for each zone of the study area. An analysis of correlation among transportation social need measure and accessibility measures for each zone has been carried out in order to verify the strength of relation between them. Due to the high resolution level of spatial analysis, manipulation of data and computation of indicators and measures was supported by a Geographic Information System approach.

ABSTRACT. Ridesharing has attracted considerable attention in recent years, as a simple, relatively inexpensive, yet efficient way to curb greenhouse gas emissions in the private transport sector. This is in particular the case in the Paris region: as the road network is increasingly congested, leading to more and more frequent heavy air pollution episodes, local authorities seek to promote ridesharing in order to improve travel conditions and mitigate the environmental impact of road traffic. This research seeks to assess through sensitivity analysis what is the potential of ridesharing regarding these two points, namely reducing congestion and mitigating pollutant emissions, in the case of the Paris region. The effects of various ridesharing scenarios will be investigated by using an integrated transport land-use model and by considering each of the following mechanisms successively: 1) traffic assignment, 2) mode choice, 3) distribution. Results include a quantitative assessment of what level of ridesharing is reached to observe significant improvements regarding congestion and pollutant emissions, and on which trip segments (e.g., purpose and range) should one focus the efforts to do so. A step by step decomposition of the effects will also help better understand the various implications of ridesharing on the urban system as a whole.

ABSTRACT. Selection of a location for residential purpose has a long-term impact on the individual’s life. The decision-making process can be supported by location assessment applications. The individual value of a location is a subjective value depending on several non-mobility and mobility related attributes. Missing services are accessible by transportation therefore mobility attributes are to be considered. We have elaborated quantitative assessment method to determine the individual value of a location; with consideration to personal preferences. The attributes of the territory, where the assessed location is located, and the attributes of routes by different transportation modes to frequent destinations are considered by the value of location. The value expresses how attractive the territory for living purpose is and how attractive the mobility from the location for the individual is. The method is based on a simplified city model containing the relevant entities and their attributes. The elaborated method is to be embedded in applications for residential location selection. The method can be applied to compare the value of a location before and after a development.

ABSTRACT. Partly related to its connection with information and telecommunication technologies home-based telework (also known as telecommuting) emerged as one attractive travel demand management strategy. This enthusiasm was supported by the first studies about the impact of telework on travel patterns, but more recent research pointed to inductive effects on travel. This work, following previous research, analyses the effects of home-based telework on total households’ weekly number of trips and miles traveled for Great Britain using data from the National Travel Survey, between 2005 and 2012. Since our previous research concluded that teleworkers tend to travel more than other workers we aim to investigate the existence of potential within household interaction effects that might compensate the higher mobility of teleworkers. Path analysis models are developed both for one and two worker households. These models study the effects of teleworking frequency in the context of home and workplace land use characteristics, commuting distance, car ownership levels and household weekly trips and travel distances by mode and purpose. By using this framework we explicitly model endogenous relationships in the chain of decisions relating location land use patterns, telecommuting adoption and travel patterns, as well as within household interactions. The obtained results will be discussed in terms of the insights provided about causality between teleworking adoption and location patterns and commuting distance, within household interactions, as well as its effects on travel patterns and its implications on sustainability.

ABSTRACT. Travel time reliability on public transport systems plays an important role in quality perception. Nevertheless, subjective elements such as mode/service reliability (the certainty travellers have regarding their travel time, their arrival time or the comfort level they will experience inside the vehicle) have been usually neglected from planning models. This study focuses on characterizing travel time reliability for public transport routes of similar length, providing a comparison between different public transport modes, and comparing travel time reliability experienced by travellers and operators.

A two-step approach is applied. The first step consists on a statistical analysis of actual travel times of all travellers on a given week. The data comes from smartcard transactions, GPS information, vehicles’ arrival and departure times. A comparison between public transport travel time reliability is performed across route lengths and modes for all recorded trips. The second step of the analysis consists on weighting every public transport route by its demand. This allow us to compare travel time reliability indicators from a travellers’ perspective and an operational perspective (i.e. between passengers and vehicle’s perspective.

This study provides evidence of significant differences among travel time variability for trips of similar length and different mode. This variability also increases with travel length for every mode. However, the variability is always smaller than 2.5 minutes for metro, which could hardly be perceived by travellers. When taking into consideration route demand, most travellers experience the slower trips; this causes a spread in the travel time distributions towards larger values.

ABSTRACT. Previous research has shown that timetables are important for punctuality, and research is ongoing on how to improve timetables through more simulation, optimization techniques, better scheduling of track works, and data analysis. Relatively little attention has been given to the actual planners. In this study, we have conducted interviews with timetable planners in Southern Sweden, and analyzed the interviews with the perspective of explaining the punctuality problems. From these we have identified four common errors in timetables, such as “conflicting train paths at stations” and “insufficient dwell or meet times at stations”. These errors cause, increase and spread delays, and require recurring interventions from traffic control. We also identify 11 reasons for such errors, such as “insufficient time for quality assurance of timetables” and “missing tools for track allocation and conflict management”. We discuss three themes among these reasons: “missing tools and support”, “role conflict”, and “single- rather than double-loop learning”. New tools and processes are currently being rolled out, which is expected to improve the situation with regards to the first of these themes. While the role conflict will remain, the new tools can perhaps also help to elevate the planners from first- to double-loop learning, allowing them to focus on quality control and on finding better rules and heuristics.

ABSTRACT. It has been recognised that travelers do not only take travel time into account, but also travel time reliability (TTR). This extra time allowance could be decreased reducing unreliability with a clear user benefit. Therefore, the evaluation of TTR has been receiving considerable attention in recent years, also in consideration of the current availability of real-time traffic data.
This study addresses this need by proposing a methodology for estimating TTR of an extended traffic network using real-time data.
The basic variables used are travel times, traffic flows and speeds of each link, estimated through a transport model, combining dynamic assignment with rolling horizon technics, taken into account real-time traffic measures from radar sensors.
The statistical measures used to analyze the quality of the database and its usefulness for monitoring and quantifying TTR are Standard Deviation and Buffer Time measures, incorporating the evaluation of Coefficient of Variation and Congestion Index.
The methodology is applied to the urban area of Catania (Italy). Three type of analysis were performed: Single Link Analysis (SLA); Multi Link Analysis (MLA) and Global Network Analysis (GNA). Each of these was conducted using simulated data for the last and this year, including weekdays and weekends.
The results from the comparison of different aggregation level, shows in some cases that travel time variability is higher in peak than inter-peak periods with the effect of a low TTR. 
This work concludes discussing how the process for estimating TTR in urban areas can be improved and into recommendations to implement it.

ABSTRACT. On highly used railway lines with heterogeneous traffic, timetabling is challenging. In particular, the limited existing capacity means that to guarantee an acceptable level of quality, the infrastructure provider must cancel some train services on the expense of others. In this article, we study the conflicts between commercial long-distance trains and subsidised commuter trains in a socio-economic perspective. The study attempts to answer the following question: What is the socio-economic effect of modifying the train timetable of a commuter service? 

The case study treats the commuter train service in Stockholm. Trips data was collected from the local operator. An entropy maximisation-based model was implemented to estimate the dynamic network OD-matrix. This dynamic matrix, of one full working day, was then used to estimate the number of travellers per train, and further converted for use in the microscopic simulation tool RailSys. The simulation estimates the travel times (with a crowding factor), waiting times and interchanges for each OD pair, and with that the generalised costs and estimation of parameters.

The article contributes with a novel method to calculate effects of changes in commuter timetables. It enables to price train slots in the capacity allocation process such as in an auction. The model provides a new way to estimate the local operator´s valuation of the different parameters (i.e. waiting and travel time, etc.). Using RailSys for the estimation of times makes it possible to include capacity aspects that normally are difficult to reveal.