TALK KEYWORD INDEX
This page contains an index consisting of author-provided keywords.
5 | |
5G | |
5G Network | |
5G New Radio | |
5G NR V2X | |
A | |
accelerometer data | |
Accessibility and social equity | |
Adaptive Traffic Signal | |
ADAS | |
AI-driven autonomous systems | |
Ambulance placement optimization | |
Anomaly detection | |
Arterials | |
Artificial Intelligence | |
assessment model | |
Auction-Based Mechanisms | |
audit | |
Autoencoder | |
Automated Planning | |
Automated Vehicle | |
Automated Vehicles | |
Automated vehicles | |
Automatic parameter configuration | |
Autonomous and Connected Vehicles | |
Autonomous Driving | |
autonomous intersection control | |
Autonomous Intersection Management | |
Autonomous Vehicles | |
Average travel time | |
B | |
Backcasting | |
Balance Cascade | |
barriers | |
Bayesian filtering | |
behavioral adaptation | |
Behaviour Change | |
bi-level optimization | |
Bicycle simulator | |
Big traffic data | |
Bike Sharing | |
bikeability | |
Blockchain | |
Brain–Computer Interface | |
Bus demand prediction | |
Business Models | |
C | |
C-ITS | |
C-ITS | |
calibration | |
Capacitated charging station | |
car-following | |
CARLA | |
Case Study | |
CCAM | |
Centralised Traffic Routing | |
Charging Behaviors | |
Charging Demand Prediction | |
charging infrastructure planning | |
Charging Profiles | |
City logistics | |
Clustering | |
Collaborative Localization | |
Computer Vision | |
congestion modeling | |
Connected and Autonomous Vehicles | |
Connected Autonomous Vehicles | |
connected vehicle | |
Control Room | |
Convoys | |
Coordination | |
COPERT model | |
Crash Statistics | |
crowd-sourced parcel delivery | |
Curve speed warning | |
Cyclist tactical maneuver prediction | |
D | |
data | |
Data Collection | |
Data Fusion | |
Data Imbalance | |
data spaces | |
data-driven network assignment | |
Datasets | |
Decision-making | |
Deep learning models | |
Deep Reinforcement Learning | |
Delay propagation | |
demand responsive transport | |
Digital platform | |
Digital Twin (DT) | |
Digital twins and simulation technologies for ITS | |
Dijkstra’s algorithm | |
discrete choice models | |
disruption | |
Distributed Control | |
DQN | |
Driving Simulator | |
Dynamic Charging | |
dynamic dial-a-ride | |
Dynamic optimization model | |
Dynamic Surveys | |
dynamic traffic assignment | |
E | |
E-scooter safety | |
eBus | |
Eco-routing | |
Electric Bus | |
Electric Urban Mobility | |
electric vehicle | |
Electric vehicles | |
Emergency response time | |
emergency vehicles | |
Emission Reduction | |
energy arbitrage | |
Ensemble learning | |
Environmental impact on response times | |
Error checking | |
ERTMS | |
Event Detection | |
expectations | |
Experimental Evaluation | |
Explicit simulation | |
F | |
fairness | |
Feature Importance Analysis | |
Federated Q-learning | |
floods | |
Fragility | |
Freeway Traffic Control | |
fuel saving | |
Future City and Road Design | |
Future Mobility | |
Fuzzy Logic | |
G | |
Gamification | |
Generative AI | |
geofencing | |
Glass-to-Glass Latency | |
Google Popular Time | |
Google popular times | |
gps data | |
Graph neural network | |
Graph Neural Networks | |
green energy | |
H | |
High Occupancy Vehicles | |
Historical accident data analysis | |
horizontal curvature | |
hybrid charging | |
I | |
I2V Communication | |
Incentives | |
Infrastructure lifetime | |
Infrastructure modification | |
Injury severity | |
Innovative Public Transportation Systems | |
Integrated dial-a-ride | |
Intelligent Public Transportation System | |
intelligent transportation systems | |
Inter-UE Coordination | |
Interoperability | |
Intersection accident management | |
Intersection Control | |
Intersection Grouping | |
IoT-enabled predictive maintenance | |
irace | |
ITS | |
ITS | |
ITS-G5 | |
J | |
Japan | |
K | |
K Means Clustering | |
Kalman filters | |
L | |
Lane changing dynamics | |
Lane-free traffic | |
large-scale problem | |
Last mile freight distribution system | |
local digital twins (LDTs) | |
Long Short-Term Memory | |
Loop-Detectors | |
Low Emission Zones | |
LSTM | |
M | |
MaaS | |
MaaS Subscription Models | |
Machin Learning (ML) | |
machine learning | |
Macroscopic Fundamental Diagram | |
Macroscopic modelling | |
Macroscopic simulation | |
Matching | |
Max-pressure control | |
Message-passing neural networks | |
Meta-Learning | |
Metaheuristics | |
metamodel | |
Metro stations | |
mFSTSP | |
Micro simulation | |
Micromobility | |
Microscopic simulation | |
Microservices | |
Microsimulations | |
Microtransit | |
mixed fleet | |
Mixed integer linear programming | |
Mixed Reality (XR) | |
Mixed Traffic Flow | |
Mixed-Integer Programming | |
Mobile charging stations | |
mobile edge computing | |
mobile phone data | |
Mobility | |
Mobility as a Service | |
Mobility as a Service (MaaS) | |
mobility observatories | |
Mobility Planning Digital Twin (MPDT) | |
Mobility-as-a-Service | |
Model Predictive Control | |
Model verification | |
Modular Parcels | |
MOST | |
Multi Agent Reinforcement Learning | |
Multi-agent reinforcement learning | |
Multi-class traffic model | |
Multi-hop relaying | |
Multi-modal transportation systems | |
Multimodal hub | |
Multimodal intelligent transportation systems | |
multimodal operations | |
Multinomial Logit (MNL) | |
Multinomial logit model | |
multitask learning | |
N | |
Network simulation | |
Neurotechnology | |
non-negative matrix factorization | |
Nonlinear Model Predictive Control | |
O | |
on-demand mobility | |
On-demand Transport | |
Online Routing | |
Online traffic modeling | |
open data | |
OpenStreetMap | |
operation efficiency | |
Optimal Control | |
Optimization | |
Ordered probit model | |
origin-destination estimation | |
Origin-destination matrix | |
P | |
Parallel simulation | |
Parking Data | |
Passenger-in-the-loop (PIL) | |
Pedestrian safety | |
Perimeter Control | |
Person-based Intersection Control | |
Personalized Contents | |
Physical Internet | |
PID Control | |
Platooning | |
Pothole detection | |
Priority Vehicles | |
privacy preservation | |
Private cars | |
profitability | |
Psychological approach | |
public acceptance | |
Public transport | |
Public transport systems | |
Public Transportation | |
Q | |
Q-learning | |
R | |
Rail-road service | |
Railway | |
Ramp Metering | |
random parameter logit model | |
Re-identified vehicle data | |
Real-Time | |
real-time data | |
Real-time telemetry | |
Real-time trajectories | |
Real-world Scenario | |
Rebalancing strategy | |
RECIFE-MILP | |
Reference security architecture | |
Reinforcement learning | |
reservation-based control | |
Resilience | |
ride-hailing | |
Ride-hailing services | |
rider behavior | |
Road features | |
road geometry | |
Road networks | |
Road Risk Analysis | |
Road Safety | |
Road Safety Management | |
Road Traffic | |
Robustness | |
Roundabout | |
route choice | |
route choice model | |
S | |
Seamless mobility | |
self-attention | |
Self-Determination Theory | |
self-supervised learning | |
Sensor-based perception | |
sensors | |
Shared Autonomous Vehicles (SAVs) | |
Shared Charging | |
Shared On-demand mobility services | |
Sidelink scheduling | |
Signal Control | |
Simulation metamodels | |
Simulation-Based Framework | |
SIS model | |
Smart Highways | |
Smart Infrastructure | |
Smart Mobility | |
Smart Mobility | |
SoA | |
spatial anticipation | |
Spatial extrapolation | |
stated adaptation choice experiment | |
Station Capacity | |
Structural Equation Model | |
sub-circuit construction | |
SUMO | |
Supervised Learning | |
sustainability in freight transport | |
Sustainable and inclusive mobility | |
sustainable mobility | |
sustainable transportation | |
T | |
TBD | |
TBD 1 | |
TBD 2 | |
TBD 2 | |
TBD 3 | |
Technology Acceptance Model | |
Teleoperated Driving | |
temporal convolutional network | |
Time of Day Breakpoints | |
time-series analysis | |
Timetable regularity | |
Tobit regression | |
Traffic | |
Traffic Accident Severity | |
Traffic Analysis Zones | |
Traffic assignment | |
Traffic control | |
Traffic data collection | |
Traffic data fusion | |
Traffic flow estimation | |
Traffic flow prediction | |
traffic forecasting | |
traffic incidents | |
Traffic light | |
traffic management | |
Traffic Micro-simulation | |
Traffic microsimulation calibration | |
Traffic modeling | |
Traffic patterns | |
Traffic safety | |
Traffic Signal Control | |
Traffic Signal Control | |
Traffic Signal Optimisation | |
Traffic simulation | |
Train Timetabling | |
Trajectories data | |
Trajectory Tracking | |
Transformer | |
transport emissions | |
transportation infrastructure | |
travel demand | |
travel times | |
Trip Reconstruction | |
Truck platooning coordination | |
Truck-drone combined logistics | |
U | |
Unsupervised learning | |
urban and transport planning | |
Urban Mobility Planning | |
Urban Traffic Control | |
Users perceptions | |
V | |
V2X | |
Van Robot | |
Variable Speed Limit | |
Vehicle Routing Problem | |
Vehicle to Grid | |
Vehicle-bridge interaction | |
Vehicle-in-the-Loop (VIL) | |
Vehicle-Road-Cloud Integration | |
Vehicle-to-Everything | |
Vehicle-to-Vehicle charging | |
Viral spread modeling | |
Virtual Reality (VR) | |
Virtual Train Coupling | |
Virtualization | |
Volunteered geographic information | |
VR | |
VR simulation | |
VRPPDTW | |
VRUs safety | |
Vulnerability | |
W | |
walkability | |
Z | |
Zero-Trust |