Intelligent Transportation Systems

Ask about this topic

Overview

Intelligent Transportation Systems study how to monitor and manage road, rail, air, maritime, and public transit networks, with goals such as safer travel, less congestion, and reliable service. Common approaches include computer vision and multimodal sensing, graph-based traffic forecasting, trajectory prediction, reinforcement learning and model-predictive control, and optimization for routing, scheduling, and infrastructure. Methods are tested on trajectory and traffic datasets and in tools such as SUMO and CARLA, alongside field deployments for tasks including signal control, crash-risk assessment, and transit operations. Large language and multimodal models are beginning to support planning and control, but generalization across cities and changing networks, safety verification, privacy, and evidence from real-world deployment remain key challenges.

Latest papers

CardsList

303 papers25 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. Analysis of Efficient Transmission Methods of Grid Maps for Intelligent Vehicles

    Apr 2, 2026Robin Dehler, Dominik Authaler, Aryan Thakur +2Intelligent Transportation SystemsV2X Communication

    Institute of Measurement, Control and Microtechnology, Ulm University, Albert-Einstein-Allee 41, 89081 Ulm, Germany

  2. An Empirical Markov Chain Car-Following (MC-CF) Model

    Mar 29, 2026Sungyong Chung, Yanlin Zhang, Nachuan Li +2Intelligent Transportation SystemsMarkov Chains

    Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign · Northwestern University Transportation Center, Northwestern University

  3. CARGO: Carbon-Aware Gossip Orchestration in Smart Shipping

    Mar 29, 2026Alexandros S. Kalafatelis, Nikolaos Nomikos, Vasileios Nikolakakis +2Carbon-Aware ComputingFederated Learning

    Department of Ports Management and Shipping, National and Kapodistrian University of Athens, 34400 Euboea, Greece · Laskaridis Shipping Co. Ltd, 14562, Kifisia Greece

  4. Macroscopic Characteristics of Mixed Traffic Flow with Deep Reinforcement Learning Based Automated and Human-Driven Vehicles

    Mar 26, 2026Pankaj Kumar, Pranamesh Chakraborty, Subrahmanya Swamy PeruruIntelligent Transportation SystemsRL for Autonomous Driving

    Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur-208016, U.P., India · Department of Electrical Engineering Indian Institute of Technology Kanpur, Kanpur-208016, U.P., India

  5. Ultra-fast Traffic Nowcasting and Control via Differentiable Agent-based Simulation

    Mar 26, 2026Fumiyasu Makinoshima, Yuya Yamaguchi, Eigo Segawa +2Intelligent Transportation SystemsAgent-Based Modeling

    Fujitsu Limited, Kawasaki, Japan · Fujitsu Research of America, Pittsburgh, PA, USA · Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA, USA +1

  6. Distributed Real-Time Vehicle Control for Emergency Vehicle Transit: A Scalable Cooperative Method

    Mar 26, 2026WenXi Wang, JunQi ZhangIntelligent Transportation SystemsMulti-Agent Control

    School of Computer Science and Technology, Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai 200092, China

  7. CROSS: A Mixture-of-Experts Reinforcement Learning Framework for Generalizable Large-Scale Traffic Signal Control

    Mar 26, 2026Xibei Chen, Yifeng Zhang, Yuxiang Xiao +3Traffic Signal ControlIntelligent Transportation Systems

    Department of Mechanical Engineering, National University of Singapore, Singapore · Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

  8. Refining time-space traffic diagrams: A neighborhood-adaptive linear regression method

    Mar 25, 2026Zhihong Yao, Yi Yu, Yunxia Wu +3Intelligent Transportation SystemsTraffic Flow Estimation

    National Engineering Laboratory of Integrated Transportation Big Data Application Technology, National United Engineering Laboratory of Integrated and Intelligent Transportation, School of Transportation and Logistics, Southwest Jiaotong University, Sichuan 610031, China · School of Transportation, Changsha University of Science and Technology, Changsha, China · Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China

  9. Multi-Agent Training-free Urban Food Delivery System using Resilient UMST Network

    Mar 24, 2026Md Nahid Hasan, Vishwam Tiwari, Aditya Challa +2Vehicle RoutingIntelligent Transportation Systems

    Department of Computer Science and Software Engineering, Miami University, Oxford, Ohio, USA · Department of Computer Science & Information Systems, BITS Pilani K. K. Birla Goa Campus, and APPCAIR, BITS Goa, India

  10. A Game-Theoretic Framework for Intelligent EV Charging Network Optimisation in Smart Cities

    Mar 23, 2026Niloofar Aminikalibar, Farzaneh Farhadi, Maria ChliElectric Vehicle ChargingIntelligent Transportation Systems

    School of Computer Science and Digital Technologies, Aston University, Birmingham, UK.

  11. TRACE: Trajectory Recovery with State Propagation Diffusion for Urban Mobility

    Mar 19, 2026Jinming Wang, Hai Wang, Hongkai Wen +2Trajectory ReconstructionDiffusion Models

    University of Exeter Department of Computer Science Exeter, United Kingdom · Jingdong Logistics Beijing, China · University of Warwick Department of Computer Science Coventry, United Kingdom

  12. Bridging Network Fragmentation: A Semantic-Augmented DRL Framework for UAV-aided VANETs

    Mar 19, 2026Gaoxiang Cao, Wenke Yuan, Huasen He +4Intelligent Transportation SystemsWireless Communications

    Department of Automation, University of Science & Technology of China

  13. MicroVision: An Open Dataset and Benchmark Models for Detecting Vulnerable Road Users and Micromobility Vehicles

    Mar 18, 2026Alexander Rasch, Rahul Rajendra PaiObject DetectionAutonomous Driving Datasets

    Chalmers University of Technology, Gothenburg, Sweden

  14. Multisource human-in-the-loop digital twin testbed for connected and autonomous vehicles in mixed traffic flow

    Mar 18, 2026Jianghong Dong, Chunying Yang, Mengchi Cai +5Intelligent Transportation SystemsAutonomous Driving Simulation

    School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China. · Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, USA.

  15. From Optimizable to Interactable: Mixed Digital Twin-Empowered Testing of Vehicle-Infrastructure Cooperation Systems

    Mar 18, 2026Jianghong Dong, Chunying Yang, Mengchi Cai +4Intelligent Transportation SystemsDigital Twins

    School of Vehicle and Mobility, Tsinghua University, 100084 Beijing, China

  16. LLM-Powered Flood Depth Estimation from Social Media Imagery: A Vision-Language Model Framework with Mechanistic Interpretability for Transportation Resilience

    Mar 17, 2026Nafis Fuad, Xiaodong QianDepth EstimationIntelligent Transportation Systems

    Civil and Environmental Engineering Wayne State University 5050 Anthony Wayne Drive, Detroit, MI, USA, 48202 · Civil and Environmental Engineering Institute for AI and Data Science (AIDaS) Wayne State University 5050 Anthony Wayne Drive, Detroit, MI, USA, 48202

  17. Data-driven generalized perimeter control: Zürich case study

    Mar 17, 2026Alessio Rimoldi, Carlo Cenedese, Alberto Padoan +2Data-Driven ControlTraffic Signal Control

    Automatic Control Laboratory, ETH Zürich · Delft Center for Systems and Control, TU Delft · Dep. of Electrical and Computer Engineering, UBC

  18. ExpressMind: A Multimodal Pretrained Large Language Model for Expressway Operation

    Mar 17, 2026Zihe Wang, Yihuan Wang, Haiyang Yu. Zhiyong Cui +4Intelligent Transportation SystemsMultimodal Large Language Models

    Beihang University Beijing, China · Shandong Hi-speed Group Co., Ltd Jinan, China · Institute of automation, Chinese Academy of Sciences Beijing, China

  19. Behavior-Centric Extraction of Scenarios from Highway Traffic Data and their Domain-Knowledge-Guided Clustering using CVQ-VAE

    Mar 17, 2026Niklas Roßberg, Sinan Hasirlioglu, Mohamed Essayed Bouzouraa +2Intelligent Transportation SystemsClustering

    Technische Hochschule Ingolstadt, 85049 Ingolstadt, Germany · AUDI AG, 85045 Ingolstadt, Germany · Technische Universität München, 80333 München, Germany

  20. The impact of machine learning forecasting on strategic decision-making for Bike Sharing Systems

    Mar 16, 2026Enrico Angelelli, Andrea Mor, Carlotta Orsenigo +2Intelligent Transportation SystemsSpatiotemporal Forecasting

    Department of Economics and Management University of Brescia, Italy · Department of Management, Economics and Industrial Engineering Politecnico di Milano, Italy

  21. Video Detector: A Dual-Phase Vision-Based System for Real-Time Traffic Intersection Control and Intelligent Transportation Analysis

    Mar 16, 2026Mustafa Fatih Şen, Halûk Gümüşkaya, Şenol PazarIntelligent Transportation SystemsVideo Object Detection

    Ankageo Co. Ltd., Yıldız Technical University, İkitelli Technopark, 34220 Istanbul, Türkiye · Department of Computer Engineering, Istanbul Arel University, 34537 Istanbul, Türkiye · Department of Electrical and Electronics Engineering, Biruni University, 34015 Istanbul, Türkiye

  22. ST-ResGAT: Explainable Spatio-Temporal Graph Neural Network for Road Condition Prediction and Priority-Driven Maintenance

    Mar 14, 2026Mohsin Mahmud Topu, Azmine Toushik Wasi, Mahfuz Ahmed Anik +1Predictive MaintenanceSpatiotemporal GNNs

    Shahjalal University of Science and Technology, Sylhet, Bangladesh · University of Oklahoma, Norman, OK, United States

  23. Simulation-in-the-Reasoning (SiR): A Conceptual Framework for Empirically Grounded AI in Autonomous Transportation

    Mar 11, 2026Wuping XinIntelligent Transportation Systems

    Caliper Corporation, Newton, MA 02461, USA

  24. Computer Vision-Based Vehicle Allotment System using Perspective Mapping

    Mar 9, 2026Prachi Nandi, Sonakshi Satapathy, Suchismita ChinaraIntelligent Transportation Systems

    National Institute of Technology Rourkela

  25. Automating Crash Diagram Generation Using Vision-Language Models: A Case Study on Multi-Lane Roundabouts

    Mar 9, 2026Xiao Lu, Hao Zhen, Jidong J. YangVision-Language ModelsIntelligent Transportation Systems

    Smart Mobility and Infrastructure Lab, College of Engineering University of Georgia Athens

  26. A Lightweight Digital-Twin-Based Framework for Edge-Assisted Vehicle Tracking and Collision Prediction

    Mar 7, 2026Murat Arda Onsu, Poonam Lohan, Burak Kantarci +3Traffic Accident AnticipationIntelligent Transportation Systems

    School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada. · Nokia Bell Labs, 600 March Road, Kanata, ON K2K 2E6, Canada.

  27. Metalearning traffic assignment for network disruptions with graph convolutional neural networks

    Mar 6, 2026Serio Agriesti, Guido Cantelmo, Francisco Camara PereiraTraffic Flow EstimationIntelligent Transportation Systems

    Department of Technology, Management and Economics, Technical University of Denmark, Lyngby, Denmark

  28. Spatiotemporal Heterogeneity of AI-Driven Traffic Flow Patterns and Land Use Interaction: A GeoAI-Based Analysis of Multimodal Urban Mobility

    Mar 5, 2026Olaf Yunus Laitinen ImanovTraffic Flow EstimationIntelligent Transportation Systems

    Department of Applied Mathematics and Computer Science (DTU Compute), Technical University of Denmark, Kongens Lyngby, Denmark

  29. Semantic Communication-Enhanced Split Federated Learning for Vehicular Networks: Architecture, Challenges, and Case Study

    Mar 5, 2026Lu Yu, Zheng Chang, Ying-Chang LiangSplit Federated LearningFederated Learning

    School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China · Faculty of Information Technology, University of Jyväskylä, FIN-40014 Jyväskylä, Finland · Center for Intelligent Networking and Communications (CINC), University of Electronic Science and Technology of China, 611731 Chengdu, China

  30. Digital-Twin Losses for Lane-Compliant Trajectory Prediction at Urban Intersections

    Mar 4, 2026Kuo-Yi Chao, Erik Leo Haß, Melina Gegg +3Multi-Agent Trajectory PredictionVehicle Trajectory Prediction

    * Chair of Robotics, Artificial Intelligence and Real-Time Systems Technical University of Munich, Munich, Germany · † BMW Group, Munich, Germany