ABSTRACT. BKK Centre for Budapest Transport – established in 2010 – is acting as a responsible mobility manager of the city providing strategic planning and organising public transport services, harmonising travel demand based upon sustainability principles. As a result of the past years’ development and innovation, Budapest managed to join the league of metropolises that have an efficient transport governance system with an integrated mobility manager, a sustainable urban mobility plan (SUMP) and a public transport system that provides better services, integrated transport infrastructure with more connections and has attractive vehicles, is customer oriented and values quality and innovation. A responsible mobility manager has to be committed to helping citizens to become smart travellers with reasonable mobility choices, and be aware and implement the latest trends in mobility, such as e-mobility, automation, public participation, mobility as a service and sharing based mobility.

ABSTRACT. Traditionally, the first steps in long-term road traffic models are based on the establishment of a relationship between transportation demand and certain explanatory variables for which available information and prediction capacity are greater than for traffic itself. Then, in successive steps, transportation mode choice and route choice models are applied. 
However, when there are available data on traffic during a long enough period, it may be argued that the evolution of traffic itself contributes better information than other variables. In this regard, there is evidence that, under the traditional approach, the uncertainty due to the inputs of the model is more important than the uncertainty due to the model itself. This may lead to the reflection that, when there is appropriate information on the evolution of traffic in a relatively stable environment, it may be more useful an analysis based on univariate time-series models that the development of a complex traffic model. 
Possibly, the choice of a univariate time-series model is not suitable for the evaluation of a new road infrastructure project, but it may be appropriate in other cases, like, for example, the appraisal of an existing motorway concession. In this paper, a methodology based on this approach is applied to a Spanish motorway concession (taken as an example) to build a confidence interval for the traffic forecast. Additionally, this methodology is used to characterize the behavior of traffic during different economic crisis in the last decades.

ABSTRACT. The increasing sensibility of the policy makers towards more sustainable and healthy transportation is leading to a wider diffusion of cycling mobility especially in urban areas; at the same time, recent studies have underlined as in EU, US and other countries the cyclist fatalities are still alarming. These circumstances lead researchers to improve knowledge about bicycles traffic flow theory. The challenge is to make available robust analysis methods and models for getting effective and safe infrastructures allowing to increase cycling mobility with positive effects on transportation and social systems. 

This work presents the application of a consolidated procedure for fitting bicycle time headways and bicycle speeds distributions starting from traffic data collected at exclusive bicycle lanes. The general framework of the procedure, together with functional components and their mutual interactions, are recalled in the paper. The effect of flow rate in both directions (analysed and opposite) on time headway and vehicle speed distributions was examined. The possibility of associating the bicycle time headways and speeds probability density functions with different cycling traffic conditions is a significant and interesting advance with respect to previous works. 

The procedure was applied to cross-sections belonging to the cycling network of the city of Bologna (Italy). The attention was focused on single models. The analysis allowed to compare a set of headway and speed distribution models highlighting their goodness-of-fit with reference to the empirical distributions.

ABSTRACT. Traffic management is being more important than ever, especially in overcrowded big cities with over-pollution problems and with new unprecedented mobility changes. In this scenario, road-traffic prediction plays a key role within Intelligent Transportation Systems, allowing traffic managers to be able to anticipate and take the proper decisions. This paper aims to analyze the situation in a commercial real-time prediction system with its current problems and limitations. We analyze issues related to the use of spatiotemporal information to reconstruct the traffic state . The analysis unveils the trade-off between simple parsimonious models and more complex models. Finally, we propose an enriched machine learning framework, Adarules, for the traffic state prediction in real-time facing the problem as continuously incoming data streams with all the commonly occurring problems in such volatile scenario, namely changes in the network infrastructure and demand, new detection stations or failure ones, among others. The framework is also able to infer automatically the most relevant features to our end-task, including the relationships within the road network, which we call as “structure learning”. Although the intention with the proposed framework is to evolve and grow with new incoming big data, however there is no limitation in starting to use it without any prior knowledge as it can starts learning the structure and parameters automatically from data.

ABSTRACT. According to recent literature, the aggregate traffic conditions of an urban road network may be measured by an asymmetric inverse-U shaped diagram, called Network Fundamental Diagram (NFD) or Macroscopic Fundamental Diagram (MFD). In the last decade, the research on NFD was finalizes for applications connected to congestion control by means of gating, pricing schemes, multi-modal network analysis, freight vehicle routing. The control of urban road networks by means of NFD is a promising research area, where new methods and models are proposed to reduce traffic congestion and delay.
The general objective of the research is to investigate if and in which measure the NFD profile (estimated by means of observed traffic data) changes according to the control strategy adopted for junction signals in an urban area. The first empirical evidences presented in this paper are related to a portion of Santander urban area, where a specific zone has been identified according to traffic characteristics and land uses. Data from traffic loops are collected and correlated with the signal control plans in different periods of a working day at road link (flow-density diagrams) and network levels (NFD). Some preliminary considerations are derived from the empirical results. The cycle length with a fixed regulation plan does not influence the main traffic variables (flow, density) at link and network level, but these results cannot be generalized.

ABSTRACT. This research presents multi-criteria vehicle routing problems. Mathematical models are formulated as mixed integer programming. We consider maximization of capacity of truck vs. minimization of utilization of fuel, carbon emission and production of noise. The problems deal with green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country and La Rioja, Spain.

We consider heterogeneous fleet of trucks. Different types to trucks have not only different capacity, but also require different amounts of fuel for operations, so the amount of carbon emission and noise vary, too. For company it is important to plan the delivery routes considering trade off between money and environmental aspects of transportation. It can be done by choosing different size of trucks and dividing the long delivery routes for smaller ones.

The results of some computational experiments modeled after a real data from the Spanish food distribution company are reported. Computational results based on formulated optimization models shown some balance between fleet size, truck types and utilization of fuel, carbon emission and production of noise. As the results company could consider to mixed trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving fuel, minimizing pollution.

ABSTRACT. The paper presents the methodology of selecting low-floor trams for a medium sized public transportation system in a metropolitan area of Poznan city in Poland. The real world case study of selecting trams in an open bid competition constitutes a background for a research project. The author proposes a universal methodology of solving the decision problem at stake. The proposed methodology has a hybrid character and combines the concepts and rules of two methodologies: MULTIPLE CRITERIA DECISION MAKING/AIDING and GROUP DECISION MAKING. The tram selection problem is formulated as a multiple criteria ranking problem and solved with the application of selected MCDM/A methods (ELECTRE, AHP). The dynamics of individual interactions between members of the groups of Decision Makers (DM-s) and stakeholders as well as between the considered groups (Local Authority; Passengers, Operator) are considered. Different approaches to modeling and aggregating the preferences of the DM-s and stakeholders are presented. The Ex-ante analysis (group interaction prior to computational experiments), focused on building a common preference model for all stakeholders before calculations is compared with the Ex-post analysis featured by a series of computational experiments performed according to different preference models and aggregating its results afterwards (group interaction after computational experiments). A series of computational experiments is carried out and the generated results are demonstrated. They are compared and thoroughly analyzed.

ABSTRACT. The design of public transport networks aims typically at maximizing the efficiency of regular movements and commuting. Such approaches tend to marginalize some urban areas (e.g. low density zones) and/or population groups (e.g. disabled, elderly, children, pregnant, people in poverty). Although those transport networks are often redesigned and adjusted in order to become more inclusive and to improve the accessibility for citizens that are more vulnerable to exclusion, in this context, a number of critical issues still often arise, namely:
(i) mobility information must be better addressed;
(ii) as travellers have different needs and capabilities, such information should be personalized according to their specific profiles;
(iii) public transport has not been able to follow the fast changes of demand, and therefore new business models are needed to better serve the population, with a particular focus on a closest interaction between offer and demand.
Taking into account these points, the authors are developing a conceptual, integrated framework, supporting social, technological and economical components, to be used as a decision support tool.
Land use profiles, travel behaviour, social habits, mobility needs and capabilities of population are studied taking into account gender, age or socio-economical differences. Past and real-time information is combined for knowledge extraction.
The new knowledge will also allow transport providers and policy makers to better known travel demands in prioritized areas. Based on the developed solution, new policies and business models may be proposed, to enhance urban mobility, and to achieve more inclusive and accessible solutions for all travellers.

ABSTRACT. The rapid increase in passenger traffic on the one hand and the slow expansion of airport capacity on the other have over the years limited the airport’s capability to maintain satisfactory service to the customer. The main objectives of airport operators are the cost effectiveness and the customer satisfaction. These two indicators are related to the first two phases of an airport terminal departure operations that involve the check-in controls and the security controls. This paper proposes an optimization model that, given a certain layout and a passengers flow, decides the number of check-in desks and security control checkpoints to minimize a cost function. The cost function considers the costs of check-in and security control checkpoints and an estimate of the passenger dissatisfaction. The model develops an optimization algorithm that integrates a simulation module. The optimization algorithm is based on the surrogate method that minimizes the cost function that does not have a closed-form expression. To this reason, the simulation module reproduces the real scenario of the terminal operations and the passengers behavior and calculates the value of the cost function. Tests have been conducted considering the real case study of Napoli-Capodichino (IT) airport.

ABSTRACT. Variable speed limits are used in traffic management to improve the traffic conditions on the road. Traditionally focus has been on improving safety. Due to the increasing traffic demand, traffic efficiency is becoming more important and the aim of the variable speed limit system is today often to reduce congestion in addition to increase safety. Further, the development in vehicle technology has made it possible to use connected vehicles, which continuously broadcast information about speed level, position on the road, etc., in order to improve existing traffic management systems. In this paper, we extend a variable speed limit system with information from connected vehicles to be able to apply traffic control independent of detector positions. First, by including connected vehicles and sparsely located detectors the variable speed limit system is not limited to a beforehand known bottleneck. Connected vehicles allow changes in the traffic state in between detectors to be detected, resulting in that non-recurrent bottlenecks can be identified. Second, to keep the flow levels as high as possible through the identified bottleneck, the capacity is estimated based on on-line calibration. Finally, a variable speed limit is applied at the identified bottleneck based on the identified capacity. Additionally, the connected vehicles receive information on the current speed limit before the actual speed limit sign becomes visible to the drivers. This lead to a smoother transition towards the new speed limit on the road. The proposed system is evaluated through microscopic traffic simulation, and numerical result are presented in the paper.

ABSTRACT. For reducing the amount of CO2 emissions from vehicles approaching a signalized intersection in car-following situation, the information provision system to a driver is proposed in this paper. The system provides mainly accelerator-off indication, in which the vehicle could pass through the intersection or shorten the idling time if it would follow the information. In car-following situation, the distance between the lead vehicle and the following vehicle might become shorter by the information provision so that risk of traffic collision may be raised. Therefore, the influence of the information provision on driving behavior in car-following situation is grasped using a driving simulator in this paper. The risk of traffic collision is measured by TTC (time to collision) inverse when the information is provided, and the effectiveness in reducing the amount of CO2 emissions from a vehicle is also evaluated quantitatively. From results of the experiments with 25 participants, although the information provision only to the lead vehicle might raise the risk of traffic collision, it can be seen that the information provision to the following vehicle can contribute to reduce the risk of traffic collision even under car-following situations. Moreover, it can be seen that the information provision to both vehicles reduces the amount of CO2 emissions from the following vehicle most effectively.

ABSTRACT. The automotive industry is changing from conventional driving into connected and later on autonomous driving. The fundamental principle of this alteration is communication and exchange of data between vehicles and other kind of traffic objects, for example traffic lights. The knowing about basic conditions from all traffic objects within a close proximity can ensure a more precise reaction of advanced driver assistant systems (ADAS). Thereby V2V-Technology contributes to increase traffic safety. This paper describes an investigation of V2V-Communication based on commercial On-Board-Units. These units, integrated in two test-vehicles, transmit and receive data based on the IEEE 802.11p standard (ETSI ITS-G5). The messages include basic conditions like position, motion vector and vehicle configuration parameters. Those information ensure a relative positioning which is also implemented in the paper on hand. The calculations provide the prerequisites for additional autonomous vehicle system applications like autonomous braking or steering maneuver. To improve precision and reliability of ADAS, statements about integrity are inevitable. These can be achieved by a fusion of different sensor information. Therefore the paper also presents possibilities to ensure an accurate localization and object detection, regarding a LiDAR System (Velodyne VLP-16) and an approach using differential GPS (DGPS). The interaction of communication, sensor fusion algorithms and integrity considerations form the basis for autonomous driving.

ABSTRACT. Due to the increasing level of automation in road vehicles, passenger safety and driver comfort constantly improves. Cooperative environment detection and situation awareness are essential components of next-generation advanced driver assistance systems and fully autonomous vehicles too. The quantity and quality of information needed for such functionalities requires new methods for data fusion. The paper presents the performance evaluation of a multi-sensor object detection algorithm applied in traffic situation. Vehicles share their information about the environment via V2V communication. The chosen data fusion and estimation procedure is the Bernoulli particle filter, which is ideal for cooperative object detection, as it can handle the varying number of sensor measurement and object appearance-disappearance too. The simulated detectors are automotive radar sensors, capable measuring object speed, distance and bearing. The filter performance is examined along four aspects: number of particles used, simulation timestep, sensor noise and object motion model noise. The applied noise models represents the quality of the equipped sensors and our lack of knowledge on object motion, therefore the robustness of the filter can be examined by varying these parameters. The amount of particles and the used timestep effect the demanded computational power and also the estimation error, hence the scaling of the algorithm can be measured. In order to obtain a statistically meaningful result, a batch of 50 runs for every parameter set were used. The maxima of the Gaussian distributions fitted to the dataset obtained for every batch were considered the performance of the filter with a given setup.

ABSTRACT. This study deals with the design and the evaluation of technological solutions for the electrification of public transport in urban areas. 
A Decision Support System (DSS) developed by ENEA within the Research program on Electric System has been adopted on order to verify the technical feasibility of several proposed architectures based on the most recent bus electric vehicle’s technologies. Then, it compares the investment and management costs, as well as the external costs due to vehicle emissions and noises, of the feasible architectures respect to the standard fuel alternatives (Compressed Natural Gas, CNG, and diesel). 
The DSS has been applied to several bus lines located in the south-west area of the city of Rome, Italy, and covering different types of service: peripheral lines, main lines connecting suburbs with the city center and secondary lines going to the main metro stations. 
Input data for the DSS derived both by simulation and by adopting open data available from the public transport operator in Rome (ATAC). 
Results show that a suitable electric architecture can be found for each of these lines with lower or comparable total costs respect to the traditional alternatives. Finally, a sensitivity analysis has been performed considering several scenarios in terms of average load factors of the bus lines as well as, discount rates of the bus electric vehicles and batteries.

ABSTRACT. The emergence of innovative mobility solutions that offer flexible transport services, is changing the way urban public transport systems will be designed. Such mobility solutions offer on demand transport services and hence can solve the problems inherent with traditional line based and schedule based public transport systems. It is essential to understand the dynamics of this new demand-supply market with co-existing and competing fixed and flexible public transport. However, the performance of the system comprising of users and transit services and the factors influencing them, have received limited attention in literature. In this paper a model is developed to analyse the system performance when the modes of fixed public transport and flexible public transport operate in competition. The model is implemented in the multi-agent simulation framework MATSim with dynamic assignment in which the users optimize their travel plan through iterative learning from the service experienced and altering their travel plan. The scenarios in which the flexible public transport offer private and shared services are considered. The system performance is analysed for varying fleet size of flexible public transport and ratio of cost of flexible to fixed public transport.

ABSTRACT. Bus travel time analysis is essential for transit operation planning. Then, this topic obtained large attention in transport engineering literature and several methods have been proposed for investigating its variability. Nowadays, the availability of large data quantities through automated monitoring allows more in-depth this phenomenon to be pointed out with new experimental evidence. The paper presents the results of some analyses carried out using automatic vehicle location (AVL) data of bus lines and automated vehicle counter (AVC) data on some corridors in the urban area of Rome where the bus services are mixed with other traffic and travel times are subject to high degrees of variability. The results show the effect of temporal dimension and similarity between travel time and traffic temporal patterns, and could open the road for the improvement of the short-term forecasting methods, too.

ABSTRACT. Promoting a sustainable mobility is a major concern of many countries around the world. Therefore, the use of cleaner and more efficient transport modes, such as public transport, must be encouraged. Adopting a holistic point of view, and considering that every trip has a purpose (work, school, shopping or entertainment), we propose a new service approach linking city services and public transport. This approach consists in partnerships that may include discounts, combined packages, reduced prices, deals and marketing campaigns, targeted to each specific audience. In order to develop these partnerships it is important to analyse the services located around the stations and the public transport usage. We use the city of Porto, Portugal, as an illustrative example and we rely on two data sources: Automated Fare Collection system data and business data points. The analysis of both datasets allowed us to determine the level of concentration of city services located around public transport stations and to identify the types of services that tend to agglomerate near the stations. We were also able to identify patterns of public transport usage based on the age and income of passengers and to analyse the correlation between the number of travel card validations and the number of services located around the stations. Finally we present a case of a service exposure to different demographic segments.

ABSTRACT. Mainly after the emergence of the term “walkability” in the 90’s, many metrics have been developed with the aim of evaluating the quality of the built environment for pedestrians. They present a diversity of factors, different levels of analysis, as well as several contexts and approaches to perform studies on active mobility. More recently, researches have also sought an association of these metrics with the pedestrian behavior, by regarding the relation of built environment measures with the walking characteristics in the field: do better conditions of sidewalks and its surroundings go along with higher pedestrian activity?

To pursue the relation of the built environment with the pedestrian share of displacements, two different indexes – at the city and at the neighborhood level – were proposed, using georeferenced data from São Paulo (Brazil). So, data for different transport analysis zones could be collected to be related with the available built environment and transport-related data.

Once related, the neighborhood-level index and the share of pedestrian displacements presented a strong positive correlation (adjusted R² = 0.797). The city-level index, though not correlated with the displacements’ data, allowed the assessment of specific guidelines for designing pedestrian-oriented policies. Besides the contribution in the relation of walkability scores with walking displacements, the discussions presented in this paper intend to provide insights on the appreciation of disparities in pedestrian mobility, mainly the ones related to socio-spatial disaggregation and to gender studies.

ABSTRACT. Research into sustainable transport modes has become increasingly relevant in the last decades. They can help overcome some of societies’ current challenges like energy consumption, climate change, an aging population and increasing scarcity of land. For this reason, the relationship between pedestrian activity and various influence factors of the built environment is of great interest.

One such influence factor is the height difference between two points along a walk. It has a significant influence on the energy required to travel between them. Whereas fields like biomechanics and movement sciences feature extensive literature on walking on inclined surfaces, the influence of slopes on walking activity has not been researched extensively in transportation science. 

We will use pedestrian counting data from steeply sloped streets and walkways with high pedestrian volumes, as well as revealed preference survey data, to analyze the effect of the inclination on pedestrian activity as well as the modal split. With this we aim to formulate a quantitative relationship between elevation difference and walkability. Subsequently, the results will be discussed in terms of their validitiy and applicability in a wider context.

ABSTRACT. According to Cervero and Kockelman (1997), one of the variables influence walkability is design (the others “d” are density and diversity), in other words, the urban form is important to displacements. In a study conducted by Handy (1996) the urban form was used only like a different urban grid, but didn’t use the systemic conception of urban form. To try to fill this gap, it was used a Space Syntax Theory that is based on in systemic conception which allows understanding the interrelations more wide way. So, this paper aims to analyses how the urban form interferes on displacements by foot. For this it was used some indicators (integration, connectivity, etc.) of the Space Syntax Theory and put into the database. That is compound of four types of factors: (a) geometric; (b) syntactic; (c) transport accessibility; and (d) activities. The case study was in three neighbourhoods in Lisbon, with different urban form/urban fabric: Campo de Ourique (orthogonal grid); Graça (organic fabric); and Telheiras (contemporaneous fabric). The modelling used was the Trip Generation Analysis with flow counting of people (based on Gate Method) of the three neighbourhoods. The results shown that urban form (integration indicator) is the second factor that more explain the presence of people in the neighbourhoods (in the counting gates). The first is the presence of subway station and the third is the presence of mixed land use. We can is demonstrate that urban form it is one of most important factors to promotes walkability in the cities.

ABSTRACT. The objective of the present study was to analyze the drivers’ behavior while approaching pedestrian crossings under different driver – pedestrian interaction conditions and to assess the effectiveness of Advanced Driving Assistance Systems (ADASs) for pedestrian detection among several road environments. Three different road environments were implemented in a fixed-base driving simulator: urban road, sub – urban road and rural road. Several driver – pedestrian interactions were implemented in addition to the pedestrian absence condition. The simulated ADAS provided a visual – auditive message. Forty – five participants drove the three road environments scenarios in which three pedestrian crossroads were implemented (pedestrian absence, pedestrian presence with ADAS and pedestrian presence without ADAS). Overall, 369 driver speed profiles of the last 150m in advance of each pedestrian crossroad were plotted. ADAS affected the driver behavior in the interaction conditions with Time-To-Zebraarrive < 4s (TTZarr*< 4s), which return aggressive drivers behaviors. As expected, no effect was observed for the averagely cautious (4s < TTZarr* ≤ 6s) and very cautious drivers (TTZarr* > 6s). The effect of ADAS among the road environments was similar for the urban and sub – urban road, resulting in a less abrupt braking maneuver that began in advance compared to that adopted in ADAS absence condition. For the rural road, the main effect was the reaching of a lower minimum speed near the pedestrian crossing and an advanced end of braking maneuver, highlighting the ability of the driver to complete a safer and effective yielding maneuver.

ABSTRACT. The last decades brought social and economic changes and these together with the technical developments and more conscious mobility planning and travelling of people called for a new transport model for Budapest. A strategic, macro level decision supporting and project appraisal tool was developed based on open and transparent methods to give more insight for users and accommodate the best practice for all professionals. In order to reflect person-specific influence factors of the traffic behaviour, based on the latest observations and house-hold surveys, 20 population segments and 12 trip purposes were identified. The numerous demand strata led to pretty realistic generation figures. The destination choice behaviour model is tour based instead of the most common home-based trip-pair practice. Trip distribution functions implies a gravity approach by logit functions applying general utility. The tour based model works with non-symmetric generation – attraction matrices and the distinction between home zone and non-home zone made the use of area specific variables (like parking fee for non-residents) possible. The aim of the paper is to describe the model structure but also explaining what observations were made and what were the key finding in terms of citizens’ transport characteristics and what decisions led to the applied model components. The fitting to the observed volumes and the sensitivity and validity of the model is fairly good, thus against the preceding model set-ups the direct use of observed matrices was not necessary.

ABSTRACT. The CapTA model of traffic assignment to a large transit network is aimed to deal with traffic phenomena, including a range of capacity constraints, as well as with passenger route choice (Leurent et al, 2014). To this end it has a 3-layer architecture that involves (i) passenger route choice on a network of transit legs and pedestrian links, (ii) line coordination of service missions, vehicle runs with their link running times and station dwelling times, track occupancy and passenger waiting at stations, (iii) vehicle running, including the alighting and boarding of passengers in relation to run dwelling time at the station, in-vehicle passenger load in relation to seat capacity and total vehicle capacity. Yet the line model is macroscopic both for passenger flows and for vehicles serving a given mission, through a frequency variable per station. The paper brings about a novel, hybrid line model that can be used on a standalone basis at the line level or by inclusion in a three-layered model such as CapTA. In the model, a macroscopic representation of passenger flows is hybridized with a microscopic simulation of vehicles. This enables us to simulate headway (ir-)regularity and derive its consequences on vehicle loads, passenger wait times and on-board comfort, track occupancy and vehicle delay for railway modes. After presenting the model and the simulation algorithm, we provide an application to a metro line under two alternative operational policies.

ABSTRACT. This paper proposes a method for netwok signal setting design, based on enhacements of an existing coordination method aiming: 1) to extend the existing approach in order to address the Traffic Control through Scheduled Synchronisation (i.e ‘one step’ optimisation of stage matrix, green timings, and node offsets ); 2) to extend the considered Mesoscopic Traffic Flow model (TRAFFMED) to the vehicle platoon speed dispersion; 3) to build up a solution method suitable for both off-line and on-line applications. The proposed optimisation method is an application of the Simulated Annealing meta-heuristic. Some numerical applications are proposed, specifically analysing ‘two step’ optimisation (synchronisation), and‘one step’ optimisation (scheduled synchronisation), for off-line (pre-timed strategy) and on-line applications (on-line computation strategy). A grid network was considered as case study and the effectiveness of the proposed strategies were evaluated by comparing the obtained results with those computed through commercial (benchmark) and in-house codes.

ABSTRACT. To improve the management of its network in the North of France, the operator DIRN tested in 2016, on an experimental basis, a new ramp metering (RM) combined with a dynamic speed control (DSC), on the A25 motorway in the direction of the city of Lille. The simultaneous and on-line functioning of these two measures, based on new algorithms, is innovative in France.

This paper describes the a posteriori and the short-term assessment of this operation. The first section describes the various devices put on the site and the associated developed algorithms. The ex post evaluation of the impacts is the subject of the second section. It is based on statistical comparisons of samples covering periods with and without control. The impact of the two combined measures is evaluated on both travel time and level service.

The major findings are summarized as follows.

• DSC associated with RM significantly reduces travel time. In addition, it reduces the variance of travel time and thus improves regularity of trips. More users are served during the morning peak of working days. 

• The benefits of the combined measures, recorded on the main route regulated, remain partly effective downstream. 

• During the morning peak, the duration of level of service in fluidity increases significantly with the combined actions. 

The lessons of this experimentation on A25 will, in particular, serve to guide future decisions for the other axes of the motorway network, managed by the DIRN operator. 

ABSTRACT. This paper describes an agent-based modelling framework representing the interactions between firms, freight vehicle drivers, and the surrounding environment in the urban freight distribution system. Decisions are modelled in three temporal resolutions: strategic, tactical, and operational. A single set of agents is used throughout all levels ensuring the consistency and sequential flow of information.

At the strategic level, firms’ characteristics and strategic decisions are modelled. These include location choices, fleet constitution, annual inbound/outbound commodity flows as well as establishment-to-establishment expected commodity flows. At the tactical level, expected commodity flows are transformed into shipments and, if required, carriers are selected by the buyers/seller establishment pairs. In turn, carriers plan their operations, particularly vehicle/driver/route assignments. Finally, at the operational level, the interactions between behavioral models and a network simulation framework are captured. The latter has two levels (micro, meso) allowing different resolutions of behavioral representation.

The behavioral models account for carriers and freight drivers’ decision making such as route choice, parking location, or stop ordering. These are simulated together with the performance of freight and passenger movements at the network level. Agents' choices take place through the evaluation of planned tours against the realized tours, which can differ due to experienced congestion effects. This approach is distinct from previous work by considering the transportation system influence in the logistics choices, and the propagation of these influences throughout the planning horizons. The paper also includes a description of the associated data collection process plus suggestions for policy scenarios and case-specific applications.

ABSTRACT. A review of the literature shows that multi criteria decision analysis (MCDA) methods are hardly used to measure the importance that decision makers in freight transport attach to the performance criteria of transport services, measured in time, costs or reliability. Until now, behavioural choice modelling has been the traditional way to identify these weights. There is an abundance of studies based on discrete choice, random utility models (DC-RUM), mostly in the context of freight transport mode choice. 
The purpose of our paper is threefold: 1) to explore avenues for the application of MCDA, 2) to evaluate its performance in comparison to conventional approaches and 3) to discuss the implications for freight transport modelling. We describe two cases in which we used MCDA to estimate weights for performance criteria that affect the choice of mode in freight transport. Both cases provide reliable estimates at low costs and little computing effort. Comparisons with the DC-RUM approach show that the MCDA approach outperforms the conventional approach in terms of predictive capabilities. 
The paper is built up as follows. We introduce the subject and its literature in Section 1. Section 2 describes alternative MCDA approaches and argues which are promising contenders for the RUM approach. Section 3 and 4 describe the two cases in terms of the modelling approach chosen, the data, the results and the main implications. Section 5 summarizes the paper and provides recommendations for researchers and practitioners.

ABSTRACT. The density of railway traffic has been steadily increasing over past years and decades. The developments have implicated a growing need for efficient operation and maintenance of railway rolling stock systems. Also the increased operation of articulated trains has induced new challenges on maintenance organization and planning. 
Selecting optimal maintenance strategies for each component does not only influence the availability of the railway vehicles but also the operational performance and the profitability of the operator. Suitable tools to analyze, compare and optimize different maintenance strategies are therefore required.
Petri nets are such a mathematical tool that have been applied for maintenance modelling and simulations of different applications. Several types of Petri Nets with different properties have been introduced. One of the recently proposed extensions of Petri Nets are the Abridged Petri Nets (APN) which fulfil the specific requirements of railway rolling stock maintenance. 
In this paper, we propose the application of APN in combination with the Monte-Carlo simulation for railway rolling stock maintenance evaluation. In a first step, the applicability of the APN approach is demonstrated on a theoretical case study comprising a condition based maintenance strategy for a system. In a second case study, several real application case studies are modeled and compared based on the processes and real application field data of three railway vehicle components. 
The tool can be further extended by pre-defining selected strategies that can be easily implemented within an overall decision support system.

ABSTRACT. Synchromodal transport has the potential to offer flexible, reliable, cost-effective and sustainable freight transportation by enabling real-time switching between transport modes. Given the numerous stakeholders and network interdependencies within freight transport corridors, achieving efficient coordination and management is complex. Multiple stakeholders need to make consistent decisions under dynamic and time-pressed operational situations. Such situations request efficient information sharing, role awareness, optimization of services and assets in freight transport corridors. Situation Awareness (SA) has been proven as essential prerequisite for decision-making under dynamic operational situations. In this research, we aim to explore the decision choices and behavior of stakeholders related to synchromodal corridor management at various levels of SA. For this purpose, we developed a simulation game called ‘Modal Manager’ comprising logistic service providers and infrastructure managers. The participants of the game take over the role of infrastructure managers. They have to cooperate to solve several disruptions and incidents in a flexible way ensuring the time-efficient and reliable transportation of containers while maintaining the optimal utilization of the network. Our research study around the game includes a session consisting of briefing, game play and debriefing with transport professionals in the private and public sector in the Netherlands. The game results are expected to shed light on decision-making, information sharing strategies and interventions made by infrastructure managers for efficient synchromodal corridor management.

ABSTRACT. Autonomous Vehicles (AVs) promise many benefits for future mobility. Several modeling studies investigated their potential impacts with special focus on spatial and/or socio-economic features. Spatial modeling represents (i) in detail the technical specifications of the novel mode, and ii) the spatial features of the area in which the system is implemented. Most of these models are agent-based. Socio-economic modeling addresses the conditions of market penetration and diffusion using mathematical methods with commercial or social orientation. Furthermore, it investigates investment and operating costs. 
This paper summarizes the main modeling works on transportation systems involving AVs that were published in the academic literature up to end 2016. In addition, we provide some examples of applications and address their respective outreach and limitations. We present recommendations for future developments. 
This way, the paper takes part to a research project of which the ultimate goal is to build a predictive model that can be used by operators and policy-makers in order to test AVs scenarios.

ABSTRACT. Vehicle automation is not yet a reality which casts huge speculation of what will really happen when implemented in the near future. The effective deployment of such novelty, especially full automation, foresees potential impacts at different levels, the most direct ones being on the mobility level. Since the deployment of fully automated vehicles cannot be realized instantaneously in all areas of a city, a transitional phase must be assumed to mitigate the changes to come. It is critical to devise policies in order to implement such technology to leverage the benefits that it may bring. According to a literature review, deployment on urban networks revealed to be a gap in the literature. In order to address that gap, we want to support city planners by developing a strategy of integration for such technology into urban networks. At a traffic level, a strategy of dedicated zones for automated vehicles will be settled. We develop a model whereby the aim is to minimize the congestion problem through dedicated links where only automated vehicles can drive. A traffic assignment approach is used where the minimization of the sum of link travel times is part of the objective function. The number of automated vehicles is changed in function of a penetration rate. Each scenario is simulated and compared. This study begins the discussion of how to help public authorities plan the deployment of such automated vehicles and bring improvement to traffic in cities.

ABSTRACT. Automated and connected vehicles (ACVs) have received a great deal of attention. Indeed, their full market penetration will be desirable in terms of traffic efficiency, as ACVs can efficiently drive by precisely and instantaneously communicating, recognizing, and reacting to other ACVs. However, it is not yet certain whether traffic efficiency is improved in mixed traffic where ratio of manual vehicles is substantially high. This is because, for example, ACVs in mixed traffic may require excessive safety clearance, as they have to rely on relatively imperfect vision/radar-based vehicle recognition. Meanwhile, relative benefit of ACVs compared to manual vehicles would be proportional to travel time (because the most significant merit of ACVs for their driver is comfortable in-vehicle experience) and therefore severity of congestion. Consequently, equilibrium states of a myopic car market may suffer severer congestion and higher social cost than the current state—this is congestion paradox. This kind of phenomena can be considered as a consequence of market penetration of a good with network externality or social interaction, where market penetration of ACVs is endogenously determined based on their cost/benefit which depend on current number of ACVs users. This study analyzes this problem under idealized conditions. Specifically, a theoretical model of endogenous market penetration of ACVs considering changes in value of time, travel time, and transportation fare, which are the most direct impacts of ACVs to the society, is formulated. Then, its market dynamics is analyzed. Finally, strategic policies to avoid such paradox and achieve social optimum are proposed.

ABSTRACT. In highly automated driving processes, the vehicle must recognize and record the roadway with the help of existing sensors (stereo cameras, radar, lidar, laser scanners etc.) and the associated driving area elements and convert them into a digital 3D-model in real time. The vehicle can then locate and orient itself and move in the so-called obstacle-free and restricted 3D-area. Localizing the vehicle precisely in the surroundings is often difficult because of the volume of data needing to be processed in real time, the accuracy of the object recognition process and the multiple disturbances like the weather, daytime and nighttime, the traffic situation etc. To gradually solve the object recognition problems in real time when depending on the available sensors and disturbances, the vehicle should have a detailed prior knowledge of the traffic infrastructure on the planned route through highly developed maps within its navigation system before the journey starts. By comparing the prior knowledge and the knowledge obtained from the surroundings, the localization of the vehicle can take place faster and more accurately. When selecting a route, the prior knowledge about the existing roads would be directly retrievable and could accelerate the localization process in the surroundings considerably and particularly make things safer if any problems occur. The digital data on roads and surroundings can also be used to calculate recommended speeds, the necessary distances between vehicles and other details for fully automated driving.

ABSTRACT. The demand-side of bike-sharing has been extensively researched in recent years and many of those studies deal with mode choice behavior. However, the behavioral realism of bike-sharing choice can be further enhanced by exploring the impact of personal attitude on mode choice decisions. This paper develops a hybrid choice model to assess the impact of an attitudinal factor, “satisfaction with local cycling environment”, on bike-sharing choice via a case study at Taiyuan, China. A survey was conducted to collect the local citizens’ travel behavior data as well as their attitudinal information. The final sample includes 9,499 individual travelers who produced 16,491 trips in total. The results show that being more satisfied with cycling environment is not only good for bike-sharing choice, but will also help increase the ridership of private bike and decrease the willingness to use private car and bus. In particular, females, younger generation and wealthier people are less satisfied with urban cycling environment. Policy makers could therefore work towards improving the satisfaction level of these traveler groups to promote bike-sharing usage. Additionally, studying bike-sharing choice in China especially using a large data sample is particularly valuable in this era given the recent boom of both publicly and privately operated bike-sharing schemes in this country. Nevertheless, further research is needed in order to fully apply the values of an attitudinal research in real practice.

ABSTRACT. Cycling has been commonly neglected in urban transport planning. In the same fashion, there is a shortage of available data on cycling mobility, especially in countries with low rates of bicycle share. Nevertheless, a modal shift towards soft modes such as cycling appears to be one of the keys for progressing towards a sustainable urban mobility paradigm. Understanding the factors that influence bicycle choice is necessary for implementing efficient probike transport policies. This research identifies the main factors affecting bicycle choice for commuting. It analyses an ad-hoc panel survey conducted in Vitoria-Gasteiz, a medium-sized city in northern Spain where cycle rate has rocketed in few years. Data from commuters, either workers or students, were collected in 2012, 2013 and 2014. An unbalanced binary panel model includes both objective – such as gender, age, occupation, car availability, or trip distance – and subjective variables – as attitudinal beliefs towards cycling–. The research confirms the importance of individual´s perceptions on cycling for understanding their modal choice and identifies main factors related to higher bicycle use likelihood.

ABSTRACT. Understanding and modelling travellers’ decisions, by correctly analysing their preferences and being able to forecast their choice, is essential in the planning and operation of any transport system. The air travel industry is certainly not an exception, particularly in a context of high competition, where airline carriers seek to attract customers by differentiating themselves from their competitors. A significant part of this behavioural modelling is the selection of a discrete choice mechanism, which guides and constraints the decision making-process. In the context of air itinerary choices, Random Utility Maximization has traditional been the framework for modelling individual preferences. Nevertheless, an exclusively compensatory approach, such as Random Utility Maximization, might not be suitable for modelling air travel preferences. This study proposes a modelling framework for multiple choice mechanisms, that combines a compensatory approach (Random Utility Maximization) and a non-compensatory approach (Elimination by Aspects). The proposed framework allows identifying and characterizing different decision-making processes within a population at an individual level. In the proposed model, individuals would have a probability of following a given choice mechanism. Different socio-demographic characteristics, as well as features from the choice scenarios themselves, are used to characterize the consideration of different choice mechanism. Then Bayesian conditioning is done to identify individual probabilities. The proposed modelling approach is tested in the context of air itinerary preferences in Australasia. Results show that the combined choice mechanism approach results on significantly better goodness-of-fit, superior forecasting capabilities and is able to capture different choice profiles within the population.

ABSTRACT. More and more drivers use GPS based tools (GNSS) to plan their route in order to choose the optimum route (shorter, faster or the most economical). These GNSS devices can operate offline or online. Of-fline, when the GIS database is installed in the device and there is not any information regarding the ac-tual traffic flow, in this case the program always calculates the same route between two places. Online, when the actual traffic flow information is available, in this case there is the possibility of the calculation of the optimal route in real time. Based on the above options, the driver’s route-choice decision can be static, dynamic or informed. Static, when the driver always follows the same route: either without using a GNSS device (choosing the usual way) or with an offline device. Dynamic, when the driver chooses the way conforming to only real time visual information on the spot without any navigation tool or external information, and decides according to traffic density. Informed, when the GNSS device calculates the optimal route in line with the current traffic flow information.
The aim of this study is the presentation of influence the proportion of the different route-choice decision modes.

ABSTRACT. "Sharing economy", including car-sharing and ride-sharing, will change our society and transport in the near future. To effectively introduce ride-share-based transport service into a society, we need to estimate the required number of vehicles and determine route and schedule of vehicles, based on travelers’ activity. We also need to understand how spatial and temporal characteristics of travelers' activity patterns affect the performance of this sharing service. Finally, we have to evaluate social benefit of introducing ride-share transport instead of conventional private-owned car. Previous studies have tried to estimate benefit to introduce ride-share transport. According to the related papers, the objective of this service is generally to minimize the total travel time of vehicles, but it may prevent travelers to carry out their activities as they planned. 
The objective of this study is to investigate features of society that ride-share transport would be successfully operated in the above context. The optimal vehicle routing and scheduling problem which satisfies all the travelers' activities is formulated as an integer linear programming problem. By using the proposed model, numerical experiments to find optimal vehicle routings are conducted with different types of activity patterns. Then, efficiency of the optimized ride-share transport service is examined by comparing its performance with those of fully private-owned car transport. The results show spatial and temporal distribution of travelers' activity patterns that ride-share transport service achieves positive impact.

ABSTRACT. Data from a panel survey among (non-)users of BiciMAD, the public bike-sharing of Madrid is analyzed to understand the relationship of intention-to-use and actual use of such systems (N=205). Results of a statistical test indicate that there is a moderate association. Findings indicate that a dense and extensive network as well as proper bicycle road infrastructure is crucial in the promotion of bike-sharing among non-users and occasional users.

ABSTRACT. Recently, vehicle sharing emerged as a new type of mobility service. In particular, if these systems happen to be free-floating, their operating area is typically located within the city and vehicles could be picked up and parked in any permitted spot, and not only at predetermined stations. This specific feature enables everyone to pick up and drop off a rented vehicle close to his demand points, with no need to visit a station before or after the ride, granting greater flexibility for users together with the opportunity of a shorter trip. Free-floating systems -due to their inherent characteristics- are becoming more popular, but at the same time, they involve additional operational challenges especially in facing the vehicles relocation process.
Similar to the station based ones, free-floating vehicle shared-use systems deal with significant fluctuation in demand, depending on day/time and area of a city. We suggest a methodology for generating a dynamic zone clustering in order to define cost-efficient relocation strategies. A proper and flexible clusterization of a city could actually allow the identification of the optimal size and number of areas among which perform an effective and enhanced vehicle repositioning, to have a better balance between demand and supply. Considering the spatio-temporal usage patterns, and forecasting their future trends, vehicles have to be displaced from areas with higher concentration, toward those that have a higher request of the service. The method is applied to a test case study, in order to verify the accuracy of the proposed model.

ABSTRACT. In a corporate context, (individual) mobility of employees still is often addressed by "owning cars" instead of "using mobility" - at least in Austria.
Therefore, the national research project "SEAMLESS - Sustainable, Efficient Austrian Mobility with Low-Emission Shared Systems" aims at providing novel (company) mobility services considering private and business trips.
The idea is to shift from owning overdimensioned and underutilized cars towards using sustainable and flexible mobility offers including shared car (pools), bike (sharing), taxis, and/or public transportation services.
The goal is to achieve a more efficient utilization and possibly a reduction of the company fleet as well as a significant CO2 reduction by fostering the usage of the aforementioned alternatives. 
In order to achieve this, not only business culture and employees' perception have to be investigated but also thorough technical support must be provided.
Within the models presented in this work, we focus on fulfilling the (original) mobility demand by incorporating alternative (to self-owned car) mobility modes such as shared (e-)cars, bike sharing, or public transport.
At the same time, side constraints related to e-mobility (e.g., temporal load distribution to avoid peaks on the energy grids) are considered.
The resulting models aim at combining different well-known and so-far mostly individually considered problems like fleet size and mix, vehicle-to-tour assignment, (e-)routing, battery load management, and general fleet management operations.
In this work, we will report on first mixed integer linear optimization models focusing on multimodal mobility and fleet management.

ABSTRACT. In this paper we introduce a search approach for shortest path algorithm in a parallel distributed architecture which is designed to handle the time-dependent for multimodal transportation network. Our proposed algorithm relies on its effective target-oriented approach of reducing the search space while the distributed parallel processing focuses on reducing the computational time. The optimality of the algorithm is principally based on computing a virtual path which is basically an Euclidean distance from the source to the destination aiming at a restriction of the search space. After the presentation of the distributed algorithm, a profiling of the algorithm is given to evaluate its computing performance.

ABSTRACT. There is a growing interest in the literature regarding the flexibility of activities and reduction of travel times in an urban environment. For the optimization of daily activity chains a method has been elaborated, which includes the temporal and spatial flexibility of activities. In the course of the optimization process possible alternatives are searched using a modified version of the Traveling Salesman Problem with Time Window. The algorithm provides an optimal order of activities as the minimum of the pre-defined cost function. In our case the cost function is travel time. The optimization process results in travel time reduction of the users. In order to provide some insight regarding the performance of the optimization, application oriented simulations are realized on a real transportation network using real travel time information. Three transportation modes are considered: car, public transport and combined (public transport with car-sharing option). We conclude that with the use of the optimization algorithm approximately 20-25% travel time reduction can be achieved, but the exact value highly depends on the original location of the activities.

ABSTRACT. This paper investigates the multimodal nature of urban congestion and network performance, with the aim of developing practice ready policy tools to alleviate the adverse effects of excess demand, no matter in which mode it realises. As part of the efforts to get an overall understanding of how congestion is defined in various disciplines, we conduct a literature review of relevant engineering and microeconomics studies. The investigation reveals the main areas where contradiction can be identified between engineering and economics approaches. In a second step, we investigate the results of an expert survey about the principles of congestion analysis from a multimodal perspective. The main contribution of the paper is twofold. First, we draw attention to the pitfalls of oversimplified and narrow viewpoints on congestion. Second, we operationalise these principles in order to enable decision makers to assess the impact of urban transport measures on congestion.

ABSTRACT. Route planners are widely used nowadays. There are several available solution which can support travelers planning their routes. Although the number of combined route planners is low. Moreover in most cases the customization possibilities are limited. The application called Waze is a good example of it’s importance. Sometimes the users know better optimums or they have other wishes what the program couldn’t take into account. In this case the statistical evaluation of the data could be used.
Based on a previous research a multimodal technic is used in this paper. This routing algorithm was developed and prepared to recognize and take into account the habits of the travellers. In this paper effects of different parameter sets are described. This study focuses on the importance of the user habit factor.
The routing algorithm is a modified ant colony algorithm. This algorithm is parallelized and it is capable to use multi threaded processors.

ABSTRACT. People living close to main roads may suffer from the nuisance of traffic and noise pollution. This paper assesses the effect of full routing cost in vehicle routing decisions by internalizing the external cost of noise. On a first step, noise externalities are economically assessed through a contingent valuation procedure. Secondly, a novel methodology is proposed to allocate the external costs to the road network links. Results show significant differences in routing planning depending on the approach: minimization of traditional internal cost versus minimization of full cost. These results encourage further research in pricing and methodologies to internalize externalities.

ABSTRACT. Several studies on the relationship between tourism transport and CO2 emissions have shown that the transport sector generates the largest proportion of emissions, accounting for 75% of overall emissions. These studies have also shown how the measures to reduce these emissions vary according to the different tourist destinations. Accordingly, this paper focuses on the impacts of mass-tourism mobility on the transport system of a prototypal Mediterranean coastal city. Conscious of the fact that not all Mediterranean maritime cities are the same, this work identifies the three major characteristics (urban structure, environmental fragility and cultural heritage) that influence – negatively or positively – tourism and the transport sector. The aim of this paper is to develop an original taxonomy of the best transport practices for reducing the congestion effect and GHG emissions, which is adapted to the prototypal coastal city and in line with its historical and environmental value.

ABSTRACT. Information and Communication Technologies (ICTs) have been widely applied in the monitoring, operation and management of transport services, while they were proven to have a great potential to increase the efficiency in the use of urban transport infrastructure and at the same time reducing negative impacts on the environment. The aim of this paper is to explore the impact of ICTs applications in reducing carbon dioxide emissions and costs in different regions across Europe: a) Bucharest - Ilfov (Romania), b) Centro Region (Portugal) and c) Extremadura (Spain). Through different scenarios we estimate potential emissions savings and damage costs for carbon dioxide. The total emissions in each scenario were calculated using COPERT 4, while the estimation of the total emission costs was based on the updated values of damage costs (€ per tonne, 2010) that are provided from European Commission’s Handbook on External Costs of Transport. Results show that ICT measures can have significant impacts in terms of costs savings and can contribute to the rapidly reduce of carbon dioxide emissions.

ABSTRACT. Infrastructure and infrastructure development plays an important role in economy, in regional economic development. In this paper authors have designed a survey and asked SMEs in order to assess the role of infrastructre in SMEs' life. The same survey has been asked in Germany and in Hungary to be able to compare the cross cultural differencies.

ABSTRACT. Roadworks can be hazardous for both road workers and road users. Even with state-of-the-art safety measures in place, serious accidents do happen there, particularly when drivers do not heed roadwork signs and speed limits. Crashes at roadworks that involve killed or seriously injured (KSI) casualties account for about 2% of all KSI crashes in developed countries, even though the roadworks are normally well-signalled and are also marked in quick-reaction road/traffic maps. These media provide several means for the drivers ‒ and for the advanced driving assistance systems (ADAS) helping them ‒ to duly detect roadworks. In the paper, we present an approach ‒ based on statistical inference ‒ for noticing roadworks. The approach takes into account the engineering regulations and practice concerning setting up temporary road configurations near and along roadworks. Such configurations often involve narrower traffic lanes and traffic signs installed closer to traffic. The approach detects change in the lateral positions of the signs ‒ measured relative to the ego-car ‒ along the road. In its other embodiment, it compares the newly acquired positions to those recorded earlier. Practically, the traffic sign detection, measurement and data collection are carried out by some traffic sign recognition system installed in the ego-car. The traffic sign data gathered in this manner is seen as a realization of a marked binomial point process; and the minimum description length principle – implemented by the on-the-fly minimization method used in the Page-Hinkley change detector – is applied for detecting change in the road environment.

ABSTRACT. The paper presents the development of an experimental vehicle framework for testing autonomous vehicle functions. The development of system serves primarily the education and the scientific work of the students. It is a good experience for the students on any level of mechatronic education because of its diverse possibilities for mechanical engineering, embedded systems, or control design. Overall system architecture, sensors, actuators and control solutions are outlined in this paper along with the development of a low-cost 3-D LIDAR sensor and some Simultaneous Localization and Mapping (SLAM) experiments
In the first part of the paper the vehicle framework, the sensor architecture, the on-board communication system and the control system is shortly outlined. After that the development of low-cost 3-D LIDAR sensor is detailed. The concept is built on a special LED-based light detection and ranging device which is capable to measure with 16 channel in a 2-D plane. Rotating mechanism with electronic control unit and CAN interface was developed and the prototype was built by 3-D printed parts, assembled and installed on the vehicle framework.
Finally the experiments with a special SLAM-based vehicle function development the so-called “home zone assist” is presented. Two versions of the function were tested and evaluated. The first one was used only an automotive ultrasonic sensor kit and its raw “echo” data, while the second one processed and utilized the point-cloud of the LIDAR sensor. 

ABSTRACT. Technologies for automated and autonomous vehicles (AVs) are fast developing, so that they seem ready for substituting in the near future privately owned non-autonomous vehicles (NVs) and further supporting the spread of shared vehicles both for travellers and freight transportation. On the other hand, it may easily anticipated that time period needed to turn the existing stock of vehicles to autonomous will last several years.
A change so great may not be allowed to be technology-driven only, but also requires a carefully analysis of its several impact through well designed enhancements of tools already available to the transportation systems modellers and planners. Such enhanced tools may be casted in the general framework of multi-user class assignment to transportation networks, concerning:
- transportation network analysis, through level-of-service models distinguishing between non-autonomous vs. autonomous vehicles, presumably sharing same infrastructure;
- travel demand analysis, through behavioural choice modelling paradigms, including choice between AVs vs. NVs, owned vs. shared, as well as path choice behavior;
- steady-state vs within-day dynamic equilibrium assignment.
This paper describes a general modelling framework encompassing all the above issues; it is used to investigate to which extent existing models can still be applied as well as which issues remain still open and worth of further research efforts.

ABSTRACT. A platoon is an array of vehicles that drive together with short inter-vehicle distances in the same lane. It has been reported that platooning has the potential of fuel saving and increasing traffic throughput. Recent studies about platoon coordination are motivated by safety concerns, fuel efficiency and the impacts on traffic flow. However, the operational issue has barely been explored.
We formulate the platoon coordination problem with time windows as a mixed-integer linear programming problem and solve it with exact solutions. The objective function consists of drivers’ wage, schedule miss penalties and fuel costs. In the test cases, a Swedish highway network model is used and the computational test result shows that, for 20 randomly generated tasks, the average computation time is within 100 seconds. The potential of platooning is evaluated by calculating the optimal preferred arrival time and without loss of generality, the time windows are shifted to study the impact of penalty costs. Both the scenario where only fuel costs are considered and the scenario where all operational costs are included are studied. The comparison shows that the optimal cost in the latter scenario is about 20% higher, which implies that the former scenario overestimates the improvement in fuel saving which can be achieved by platooning. Although the figure will be affected by the specific cost coefficients, it can be shown that by imposing time window constraints and drivers’ wage cost, the number of feasible routes are reduced dramatically, which decreases the opportunities of platoon formation.

ABSTRACT. The quality offered by railway and bus providers (state and look of the vehicles, inner appearance, ticket purchasing options) plays a major part in the public transportation system in Hungary. These quality measurements influence passengers in their choice of travelling method. The presence of paralellism of railway and bus transportation is an actual problem in regional transportation in Hungary. The solution of this problem lies not only in professional traffic organizing methods, but also regarding the needs of passangers and satisfying said needs. Defining the optimal demand for the development of this subject is based on interviewing passengers directly. The questions asked are specifically targeting percetion of the quality of service. Based on this perception conclusions can be drawn regarding passenger's choice of transportation methods. The purpose of our subject is to use the results gotten from multicriterional analysis and questionnaires to give a general idea of the demands from the passenger's side, especially in case of co-existence of the possiblity of transportation by bus and railway.

ABSTRACT. The Mobility as a Service (MaaS) concept has recently emerged capitalising on ICT developments and the sharing economy. Through MaaS users are able to fulfil all their mobility needs via a single, digital platform. The mobility operator integrates all offerings and customers can purchase monthly plans. As a novel concept, there is still much to understand about how these mobility plans should be created for them to truly satisfy user needs. This study aims to address one of these, namely whether users prefer to choose from fixed MaaS bundles or they would prefer flexibility through 'create your own' approaches.
First, a survey and a personalised pivot style stated preference (SP) experiment is designed and carried out in London. The SP has three fixed and one menu based options with transportation mode specific (amount of each mode, special features) and non-mode specific (price of plan, transferability to next month) attributes. 1000 Londoners are each presented with 4 SP experiments, leading to 4000 SP observations. Second, binary choice analysis is used to reveal preferences for fixed versus flexible MaaS plans and to determine the most important plan characteristics that influence this choice. Willingness to pay for flexibility is also examined. To our knowledge, this is the first attempt to model user preferences for MaaS. By conducting an original data collection and analysis specifically aimed at MaaS plans, this research will provide valuable insights not only to research community but to the industry and policy makers as well.

ABSTRACT. The paper focuses on unreliable dynamic transit service networks, on which, even if predictive info is available, trip planners should give dynamic strategy-based path suggestions, rather than provide a complete path up to destination. In the paper, the search for a travel strategy to be used as a path recommendation in innovative transit trip planners is analysed as a Markov decision problem, together with the relative solution approaches. Applicative examples of the procedure on a simple test network are then reported. Finally, some concluding remarks are made and future research perspectives outlined.

ABSTRACT. Norwegian railways experienced a steady decline in punctuality during the period 2007-2010. This paper briefly discusses the concept of train punctuality, influencing factors on punctuality, and investigates relationship between punctuality and weather factors on Norwegian railways by analysing data for the period 2007-2010. This study is particularly interested in data from the Oslo area, namely the section between Drammen and Eidsvoll, a stretch that has many travellers and affects all the train companies involved in the study. The analyses are based on data concerning punctuality and potential weather factors that are likely to influence punctuality. Data are studied on a weekly basis, and correlation and regression analyses are carried out. The results show that the influence of a harsh winter with extreme cold days on punctuality is strong and their correlation is statistically significant. The contribution of this paper lies within research on the empirical study of delay causes in the railway industry.

ABSTRACT. Forecasts pertaining to urban freight transport and international freight transport in the European Union unanimously imply that, within at least the next thirty years, the main indicator of functionality and growth will be dynamic supply chains, as they are commonly referred to, where logistics centres supported by almost infinite possibilities of new e-technologies will play the most crucial part.
Owing to industrial tradition and well-developed transport infrastructure, including primarily the most densely built network of high-class roads in the country and fast road connections with central Poland as well as neighbouring countries, the territory of Silesian Province has become an important warehousing market of all-Polish and Central-Eastern European relevance. Identifying the trends observed in the development of freight transport logistics within the territory in question is the first step towards improvement of the current state of matters. It also provided grounds to perform one of tasks defined under the international S-mile project implemented within the framework of the ERANET Transport III “Sustainable Logistics and Supply Chain” programme. This article is mainly an attempt to review results of the analyses undertaken in this scope, including those pertaining to the specificity of the existing infrastructure and the projected development of the logistic infrastructure in Silesian Province along with orientations of its development proposed in strategic documents of both national and regional level, such as the Silesian Province development strategy, development plans, concepts, forecasts as well as projects concerning transport and freight transport logistics.

ABSTRACT. Agent-based models (ABM) are widely used to reproduce complex phenomena involving human decision-making and behaviour, included transport problems and interaction among transport stakeholders. In this respect, not only decisions are complex because transport problems are “wicked”, requiring the evaluation of plans/projects considering multiple criteria and points of view; participation of multiple actors in the decision-making process adds further complexity being a social phenomenon characterised by emerging dynamics, e.g. consensus building.
Notwithstanding their potential in reproducing real-world processes and aiding decision-making, ambiguity arises with respect to model validation. Empirical validation of ABM implies assessing the extent to which the model, from the assumptions to the results, is capable of approximating reality. To this end, different methods have been proposed, but there is yet not a widely accepted procedure.
This paper addresses this problem and suggests using role-playing games as potential means for ABM validation. An application is described with the intent of providing a preliminary contribution to the solution of the daunting validation problem of an ABM that mimic stakeholder interaction in a multi-level decision-making process about urban freight transport policies. The aim is twofold: (1) understand if the structure of the model and the opinion dynamics envisioned are consistent with a real decision-making process, (2) verify if the results derived from the ABM effort are in line with those derived from a real-life experiment.
Results of the experiment show that the model seems capable of reproducing real-world processes and confirm that well-thought-out role-playing games can contribute in validating ABM models.

ABSTRACT. To determine the optimal volumes of cargo deliveries to terminal complexes is an urgent task. The existing techniques do not meet the requirements for formation of transportation rates depending on volumes of deliveries; do not take into account the discrete changes in connection with periodic accumulations and expenditures of stock volumes which fully depend on the intensity ratio of deliveries and shipment of goods.
In order to optimize the volumes of transit cargo deliveries to reduce the costs of transportation and storage the models for forming such costs depending on quantities of transported enlarged discrete lots of transit cargo at fixed volumes (cargo units) are developed. 
In the cost structure there are singled out storage costs of the present stock during its expenditures between two adjacent supplies with intervals throughout the delivery period, maintenance costs for excess volumes of supplied goods and storage costs of the maintained stock during its expenditure after the end of the delivery period and up to the end of the shipment period.
The problem is solved by searching the extreme value of the objective function, with the minimum and maximum number of cargo units being restricted.
Using the developed regulations the optimal volume of cargo shipments along the route Chelyabinsk – Moscow into the terminal complex for retail trade network is defined. The effect of the reduced total costs of transportation and storage of goods in stock has exceeded 2 million rubles per year.

ABSTRACT. The paper presents an approach to estimate the number of vehicles used in the process of service of requests on cargo deliveries. The proposed approach is based on a simulation model of servicing the requests flow with the known stochastic characteristics. A problem of determining such a number of lorries that provides the maximum profit of a transport company with the maximum level of the clients’ service is quite a complex issue due to the stochastic nature of the transport process and the random nature of the demand for cargo deliveries. The author presents a mathematical model of the transport process; on the basis of this model, the simulation model implemented in Python for the technological process of the requests flow servicing is developed. The results of the simulation experiment, based on the proposed software, allowed the author to determine the functional dependence of a level of service on parameters of demand for goods delivery and the number of vehicles. Using the obtained dependence, a formula for estimating the optimal number of vehicles was established as an argument, in which the function of the transport company’s profit reaches its extreme maximum.