Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness

Human-level control through deep reinforcement learning

Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Ioffe, S., & Szegedy, C. (2015) · arXiv · doi:10.48550/arxiv.1502.03167 · Cited by 27,818

Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate ShiftPreprint

Ioffe, S. (2024) · arXiv (Cornell University) · doi:10.57702/o9raffed · Cited by 15,273

Are we ready for autonomous driving? The KITTI vision benchmark suite

Geiger, A., Lenz, P., & Urtasun, R. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248074 · Cited by 14,897

CARLA: An open urban driving simulator

Dosovitskiy, A., Ros, G., Codevilla, F., Lopez, A., & Koltun, V. (2017) · arXiv · doi:10.48550/arxiv.1711.03938 · Cited by 3,718

Dueling Network Architectures for Deep Reinforcement Learning

Wang, Z., Schaul, T., Hessel, M., van Hasselt, H., Lanctot, M., & de Freitas, N. (2015) · arXiv · doi:10.48550/arxiv.1511.06581 · Cited by 3,300

Prioritized Experience Replay

Schaul, T., Quan, J., Antonoglou, I., & Silver, D. (2015) · arXiv · doi:10.48550/arxiv.1511.05952 · Cited by 3,120

A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles

Paden, B. A., Čáp, M., Yong, S. Z., Yershov, D. S., & Frazzoli, E. (2016) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2016.2578706 · Cited by 2,724

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

Yu, F., Chen, H., Wang, X., Xian, W., Chen, Y., Liu, F., Madhavan, V., & Darrell, T. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00271 · Cited by 2,641

International Conference on Machine Learning (ICML)-2005

津田, 宏. (2006) · 人工知能学会誌 = Journal of Japanese Society for Artificial Intelligence · Cited by 2,558

Enhanced deep reinforcement learning model with bird’s eye view design strategy for decision control in vehicle-road collaboration

Luo, Y., Zhang, R., Chen, Z., Xie, C., Zheng, S., Yu, S., & Li, W. (2025) · Control Engineering Practice · doi:10.1016/j.conengprac.2025.106315 · Cited by 2

Taxonomy of Safe Uncertainty Handling in the Context of Dynamic Risk Management

Schleiß, P., Zafar, S. A., Tanzarella, L., & Carella, F. (2024) · International Conference on System Reliability and Safety (ICSRS) · doi:10.1109/icsrs63046.2024.10927431 · Cited by 2

A Review of Lane-Changing Models Based on Scenarios and Performance Metrics

Wang, L., Wen, X., & Hao, Y. (2025) · International Journal of High Speed Electronics and Systems · doi:10.1142/s0129156425405236 · Cited by 2

A Comprehensive Review on Reinforcement Learning Methods for Autonomous Lane Changing

Bouali, M., Sebaa, A., & Farhi, N. (2025) · International Journal of Intelligent Transportation Systems Research · doi:10.1007/s13177-025-00521-9 · Cited by 3

Decision-Making for Autonomous Vehicles in Multi-Scenarios With Global Map Model and Dynamic Safe Topological Structure

Ouyang, D., Li, J., Li, G., Ren, X., & Peng, Q. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3604972 · Cited by 2

Adaptive Kalman-Based Hybrid Car Following Strategy Using Td3 and CaccPreprint

Zheng, Y., Yan, R., Jia, B., Jiang, R., Tapus, A., Chen, X., Zheng, S., & Ying, S. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4681766 · Cited by 2

Human-Agent Teaming: A System-Theoretic OverviewPreprint

Meimandi, K. J., Bolton, M. L., & Beling, P. A. (2024) · doi:10.36227/techrxiv.170629550.02125312/v1 · Cited by 2

Enhanced Adaptation of Reinforcement Learning Algorithms to Actuator Variability in Autonomous Driving: Error Observation and LSTM Prediction

Zhou, Y., Hu, J. F., Cheng, L., Zhang, Y., Du, Y., Ding, W., & Wang, Z. (2024) · CAA International Conference on Vehicular Control and Intelligence (CVCI) · doi:10.1109/cvci63518.2024.10830032 · Cited by 1

Review of Autonomous Driving in Unexpected Events

Chen, Y. (2024) · International Conference on Intelligent Robotics and Automatic Control (IRAC) · doi:10.1109/irac63143.2024.10871588 · Cited by 1

Robust Decision-Making for Off-Ramp in Intention-Based Deep Reinforcement Learning

Fang, H., Liu, L., Gu, Q., Xiao, X., & Meng, Y. (2024) · International Conference on Automation in Manufacturing, Transportation and Logistics (ICaMaL) · doi:10.1109/icamal62577.2024.10919832 · Cited by 1

Probabilistic Decision-Making for Virtually Coupled Trains Under Uncertainty

Wu, Y., & Yan, F. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3554231 · Cited by 1

Deep Reinforcement Learning with Driving Intention for On-Ramp Decision-Making

Fang, H., Liu, L., Gu, Q., Xiao, X., & Meng, Y. (2025) · Lecture notes in electrical engineering · doi:10.1007/978-981-96-3560-3_5 · Cited by 1

Generative policy-driven HAC reinforcement learning for autonomous driving incident response

Zhang, H., Wang, J., Zhang, S., Jiang, Y., Li, M., Yong, B., Zhou, Q., & Zhou, X. (2025) · Future Generation Computer Systems · doi:10.1016/j.future.2025.108106 · Cited by 1

Review of Scenario Virtual Testing Technology for Autonomous Vehicles: Migration Challenges Between Symmetric Frameworks and Asymmetric Scenarios

Chen, Y., Jiang, H., & Sun, T. (2025) · Symmetry · doi:10.3390/sym17091503 · Cited by 1

Privacy-Preserving Personalized Autonomous Vehicle Lane Change Using Inverse Reinforcement Learning

Zhou, Z., & Chen, J. S. (2025) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2025.3617416 · Cited by 1

Decision planning for intelligent vehicles in obstacle avoidance using APF-QP methods

Ma, M., Huang, B., Ma, L., & Yang, X. (2025) · International Journal of Dynamics and Control · doi:10.1007/s40435-025-01924-y · Cited by 1

Trajectory Planning for Autonomous Driving in Transportation Systems Based on Deep Reinforcement Learning and Spatio-Temporal Voxels

He, G., Yu, H. N., Li, G., & Li, K. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3630994 · Cited by 1

Concept, principle, and modeling of driving risk entropy based on human-vehicle-road coupling model for autonomous vehicle

Gao, H., Yang, H. C., Zhu, J., Su, H., Tang, C., Wang, X., Shi, J., Shen, C., Liu, Z., & Li, K. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.132395 · Cited by 1

Digital Twins as Predictive Models for Real-Time Probabilistic Risk Assessment of Autonomous Vehicles

Vadnerkar, K. M., & Pisu, P. (2025) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2025.3641530 · Cited by 1

Adaptive AI-Driven Cybersecurity Framework for Threat Detection and Response in Networks

Ghazal, T. M. (2025) · International Conference on Cyber Resilience (ICCR) · doi:10.1109/iccr67387.2025.11292061 · Cited by 1

Risk-rule filtered LSTM-dueling DQN for autonomous lane change decision

Chen, Z., & Zhu, K. (2026) · Traffic Injury Prevention · doi:10.1080/15389588.2025.2607637 · Cited by 1

Car Safety Airbags Based on Triboelectric Nanogenerators

Cha, B., Luo, J., Guo, Z., & Pu, H. (2026) · Sensors · doi:10.3390/s26031043 · Cited by 1

Decision-Making of automated vehicles under diverse risky pedestrian crossing behaviors

Chen, X., & Wang, H. (2026) · Accident Analysis & Prevention · doi:10.1016/j.aap.2026.108448 · Cited by 1

Trajectory planning for obstacle avoidance of unmanned vehicles considering front-wheel steering angle deviation fault

Wang, H., Xia, Z., Zheng, W., & Wang, Y. (2026) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070261430607 · Cited by 1

TGLD: A Trust-Aware Game-Theoretic Lane-Changing Decision Framework for Automated Vehicles in Heterogeneous Traffic

Pan, J., Wang, T., Wang, Y., Jiao, J., & Claudel, C. G. (2025) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc60802.2025.11423712 · Cited by 1

A deep reinforcement learning lane-changing model for autonomous vehicles during unexpected lane blockages

Kulkarni, M., Wei, Z., & Zhang, Y. (2026) · Journal of Intelligent Transportation Systems · doi:10.1080/15472450.2025.2597739 · Cited by 1

Minimum-time lane changing problem of vehicle handling inverse dynamics based on adaptive mesh refinement and collocation optimization method

Liu, Y., Cui, D., & Wen, P. P. (2023) · Journal of Vibroengineering · doi:10.21595/jve.2023.23085 · Cited by 1

Optimized TOPSIS technique for trajectory selection of self-driving vehicles on highways

Muñiz, A. A. A., Mújica‐Vargas, D., Rendón-Castro, A., Luna-Álvarez, A., & Vela-Rincón, V. V. (2024) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-219365 · Cited by 1

Intelligent control of self-driving vehicles based on adaptive sampling supervised actor-critic and human driving experience

Zhang, J., Ma, N., Wu, Z., Wang, C., & Yao, Y. (2024) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2024267 · Cited by 1

Predictive model for hazardous scenarios in autonomous driving based on graph neural networks and variational autoencoders

Tian, H., Wang, X., & Ma, X. (2024) · International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT) · doi:10.1117/12.3031014 · Cited by 1

Deep reinforcement learning for autonomous driving in uncontrolled intersections of Indian roads

Shankar, A. R., Mittur, A., Narasimhan, A., & Kayarvizhy, N. (2024) · Multimedia Tools and Applications · doi:10.1007/s11042-024-19812-6 · Cited by 2

Human-Centered Collaborative Decision-Making and Steering Control with Reinforcement Learning

Yan, L., Wu, X., & Lu, H. (2024) · Lecture notes in mechanical engineering · doi:10.1007/978-3-031-70392-8_105 · Cited by 1

Research on robust decision making for intelligent connected vehicle at highway on-ramp

Fang, H., Liu, L., Gu, Q., Xiao, X., & Meng, Y. (2024) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070241281396 · Cited by 1

Driving Risk Assessment Approach with Machine Learning under the Influence of Braking Rate

Wu, S., Su, M., Yang, H., Liu, Z., Yang, W., Zhou, C., & Zhu, X. (2024) · International Conference on Information Systems and Computing Technology (ISCTech) · doi:10.1109/isctech63666.2024.10845714 · Cited by 1

Risk-Aware Attention-Based TD3 Approach for Vehicle Decision-Making in Dynamic Traffic

Niu, Y., Hu, C., & Wang, Z. (2024) · IEEE International Conference on Unmanned Systems (ICUS) · doi:10.1109/icus61736.2024.10840090 · Cited by 1

Meta Reinforcement Learning for Autonomous Driving with Rapid Adaptation to Drivers*

Xing, J., Du, H., Wei, D., Zhang, X., Cui, Y., & Huang, Y. (2024) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc58415.2024.10919694 · Cited by 1

Reinforcement learning-based controller for path tracking of an autonomous vehicle

Norouzi, M., & Poshtan, J. (2025) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070251350409 · Cited by 1

GUIDEd Agents: Enhancing Navigation Policies Through Task-Specific Uncertainty Abstraction in Localization-Limited Environments

Puthumanaillam, G., Padrão, P., Fuentes, J., Bobadilla, L., & Ornik, M. (2026) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2026.3655198 · Cited by 1

On the quantification of the spatiotemporal impact of a single discretionary lane change on upstream traffic safety and efficiency

Hou, K., Zou, J., Zheng, F., Liu, X., & He, Z. (2026) · Accident Analysis & Prevention · doi:10.1016/j.aap.2026.108774 · Cited by 1

An advanced deep learning model for maneuver prediction in real-time systems using alarming-based hunting optimization

Jaiswal, S., & Balasubramanian, C. M. (2023) · International Journal of Advances in Intelligent Informatics · doi:10.26555/ijain.v9i2.1048 · Cited by 1

Uncertainity and Noise Aware Decision Making for Autonomous Vehicles -A Bayesian ApproachPreprint

Sachdeva, R., Gakhar, R., Awasthi, S., Singh, K., Pandey, A., & Parihar, A. S. (2024) · doi:10.36227/techrxiv.170473946.60541924/v1 · Cited by 1

Promoting CAV Deployment by Enhancing the Perception Phase of the Autonomous Driving Using Explainable AI

Dong, J., Chen, S., & Labi, S. (2023) · doi:10.5703/1288284317701 · Cited by 1

Neuro-symbolic deep reinforcement learning for safe urban driving using low-cost sensors.

Albilani, M. (2024) · theses.fr (ABES) · doi:10.70675/ea6f5d11z7d78z4484zb809z38299a88535e · Cited by 1

Risk assessment of non-stationary time series driving data based on FMK method for autonomous vehicles

Du, J., Dai, M., Wang, W., Zhang, G., & Zhu, X. (2023) · International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB) · doi:10.1117/12.2686341

Joint Local Reinforcement Learning Agent and Global Drone Cooperation for Collision-Free Lane Change

Hao, J., Naja, R., & Zeghlache, D. (2023) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-031-34459-6_8

Choice Patterns for Self-Driving Vehicles in the 5th Generation Volkswagen Group

Viktor, P., & Garai-Fodor, M. (2023) · IEEE International Symposium on Computational Intelligence and Informatics (CINTI) · doi:10.1109/cinti59972.2023.10382113

Testing the acceptance of electric charges

Viktor, P. (2023) · IEEE International Symposium on Computational Intelligence and Informatics (CINTI) · doi:10.1109/cinti59972.2023.10382083

Few-shot decision-making method for high-speed driving based on large model architecture

Yu, Y., Guan, J., Cheng, L., Li, Y., & Xu, Y. (2024) · Asia Conference on Algorithms, Computing and Machine Learning (CACML) · doi:10.1145/3654823.3654894

Introduction

Qi, H. (2024) · Lecture notes in intelligent transportation and infrastructure · doi:10.1007/978-981-97-3597-6_1

Behavioral-Adaptive Deep Q-Network for Autonomous Driving Decisions in Heavy Traffic

Liu, Z., & Yu, H. Z. (2024) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981241262314

A Cooperative/Non-cooperative Game Based Lane-changing Decision-making Method for Intelligent and Connected Vehicles

Yang, P., Li, J., Liu, X., & Liu, X. (2024) · Chinese Control Conference (CCC) · doi:10.23919/ccc63176.2024.10662826

Research on Vehicle Trajectory Prediction Based on Improved LSTM Model

Li, J., & Wu, X. (2024) · Lecture notes in civil engineering · doi:10.1007/978-981-97-9640-3_25

Continuous Decision-Making for Risk-Based Collision Avoidance in Autonomous Driving using Twin-Delayed DDPG

Fan, S., Fan, X., & Wang, Y. (2024) · IEEE International Conference on Industrial Informatics (INDIN) · doi:10.1109/indin58382.2024.10774403

Digital Twin Virtual-Real Synchronization for Aeroengine Gas Path System Based on Deep Reinforcement Learning

Xu, C., Huo, Y., Shi, C., & Zhao, Y. (2025) · IEEE Systems Journal · doi:10.1109/jsyst.2025.3529705

A Hippocampus-Inspired Dynamic Planning Method for Overtaking Scenes via Predictive Map

Liu, Y., Chen, D., Lu, C., Lu, H., & Zhu, M. (2024) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc58415.2024.10920239

A Graph-Based Method for Tactical Planning of Lane-Level Driving Tasks in the Outlook Region

Zhang, Q., & Guan, H. (2025) · Applied Sciences · doi:10.3390/app15094946

A Priori Estimates for Deep Residual Network in Continuous-Time Reinforcement Learning

Yin, S., Zhou, Q., Fei, W., & Luo, T. (2025) · SIAM Journal on Mathematics of Data Science · doi:10.1137/24m1640811

A Literature Review on Machine Learning-Based Risk Prediction and Decision Support Systems in Autonomous Driving

Aslantaş, M., & Gündoğdu, F. K. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-97992-7_82

A Spatially Structured Collision Avoidance Model for Low-Altitude Uav Navigation in Multi-Layered AirspacePreprint

Xiao, Y., Li, Z., & Huang, W. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5357458

Lane-Level Navigation: A Local Drive Guide Sitting by the Roadside

Li, H., Lei, M., Lin, W., & Hu, J. (2025) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv64158.2025.11097382

Distributional Soft Actor-Critic with Harmonic Gradient for Safe and Efficient Autonomous Driving in Multi-Lane Scenarios

Zhang, F., Zhan, G., Shuai, B., Zhang, T., Duan, J., & Li, S. E. (2025) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv64158.2025.11097749

Enhanced DACER Algorithm with Multimodal Q-value Distribution for Risk-Sensitive Stochastic Vehicle Environments

Liu, T., Song, X., Wang, Y., Zou, W., Shuai, B., Gao, H., He, W., Duan, J., & Li, S. E. (2025) · IEEE Intelligent Vehicles Symposium · doi:10.1109/iv64158.2025.11097380

Dynamic lane-changing trajectory planning for autonomous vehicles: A novel approach using Gravitational Search Algorithm with Blend Crossover

Nithya, M., & Sundararaj, V. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112022

Heuristic Reinforcement Learning-Based Multi-Objective Speed Coordination for Autonomous Vehicles

李, 琦. (2025) · Computer Science and Application · doi:10.12677/csa.2025.159224

Decision-Making Research for Intelligent Connected Vehicles Considering Adhesion Condition

Wang, H., & Hou, D. (2025) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2025-99-0028

Lane Change Decision Making Using Deep Reinforcement Learning

Lamei, P., & Haeri, ء. (2025) · doi:10.1109/icee67339.2025.11213683

Leveraging Diminishing Demonstrations in Deep Reinforcement Learning for Decision Making of Autonomous Driving at Unsignalized Intersections

Wu, B., & Yu, H. Z. (2025) · Transportation Research Record Journal of the Transportation Research Board · doi:10.1177/03611981251388620

MATRICS: A Multi-Agent Deep Reinforcement Learning-Based Traffic-Aware Intelligent Lane-Change System

Das, L. C., & Won, M. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11246051

A Framework to Support Over-The-Air Updates for Autonomous Driving Software

Shen, D., Shen, W., & Nearchou, I. (2025) · ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD) · doi:10.1109/snpd65828.2025.11253604

SAFE-Q: Safety-Aware End-to-End Driving Using CrossQ Deep Reinforcement Learning

Park, Y., Jun, W., & Lee, S. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3633658

Improvement for vehicle following safety in mixed traffic flow: A cooperative guidance method for driving behavior decision-making

Liu, H., Shi, C., Liu, F., Xie, J., Yao, Z., & Zou, Z. (2025) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2025.131182

A study on the development of an automated control system for slipform construction based on deep reinforcement learning

Wu, K. (2025) · Discover Computing · doi:10.1007/s10791-025-09812-x

Collision Avoidance for Autonomous Driving by Integrating Risk Evaluation Into Deep Reinforcement Learning

Fan, X., Wang, Y., & Che, X. (2026) · International Journal of Intelligent Transportation Systems Research · doi:10.1007/s13177-025-00586-6

Generative Reinforcement Learning for Multimodal Trajectory Planning in Autonomous Driving

Zou, W., Tao, L., Wang, Y., Zhang, X., Shuai, B., Duan, J., & Li, S. E. (2025) · CAA International Conference on Vehicular Control and Intelligence (CVCI) · doi:10.1109/cvci66304.2025.11348183

Dual-Constrained Actor-Critic Deep Reinforcement Learning for Autonomous Driving Decision-Making

Wang, K., Liu, J., Meng, Q., & Guo, H. (2025) · CAA International Conference on Vehicular Control and Intelligence (CVCI) · doi:10.1109/cvci66304.2025.11348303

Robust Motion Control Policy Learning for Autonomous Driving Under Coupled Uncertainties

Shen, Y., Zhou, Y., Lan, Q., Ren, X., Li, J., & Li, G. (2025) · CAA International Conference on Vehicular Control and Intelligence (CVCI) · doi:10.1109/cvci66304.2025.11348424

Risk-anticipatory attention-based SAC approach for vehicle decision-making at unsignalized intersections

Zhang, S., Wang, L., Ruan, H., Zhang, W., & Zhu, B. (2026) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070251413023

Reinforcement Learning for Driving Policy Generalization via Risk-Aware Expert Policy and Conditional Diffusion

Li, G., Wang, Y., Ouyang, D., Li, J., & Ren, X. (2026) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2026.3657609

Fusing speculated risk into reinforcement learning-based autonomous driving decision-making for mixed traffic

Cai, M., Tan, Q., Hua, S., & Huang, Z. (2026) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070261421459

OPTIMA: Optimized Policy for Intelligent Multi-Agent Systems Enables Coordination-Aware Autonomous Vehicles

Du, R., Zhao, K., Hou, J., Zhang, Q., Li, T., & Zhang, P. Y. (2025) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc60802.2025.11423551 · Cited by 2

Research and Analysis on the Application of Artificial Intelligence Technology in the Automotive Field

Ma, Z. (2026) · ITM Web of Conferences · doi:10.1051/itmconf/20268404003

Contributions to safety assurance of autonomous trains

Chelouati, M. (2024) · doi:10.70675/370d5308z351bz48baz8627zbce71f5b44ac

Game-theoretic conflict resolution for tunnel emergencies in mixed connected traffic

Wang, L., Xiao, W., & Qiu, C. (2026) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070261433507

Tracking and Clustering Experience Replay for Balancing Sample Immediacy and Diversity

Chen, Y., Sun, Z., & Xia, Y. (2025) · China Automation Congress (CAC) · doi:10.1109/cac67268.2025.11487311

Risk-Augmented Loss With Attention Mechanisms: Enhancing Proximal Policy Optimization for Safer Autonomous Driving

Safae, B., Boumhidi, J., & Nikolov, N. S. (2026) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2026.3687399

Ontology-driven cloud dynamic Bayesian network model integrated with deep reinforcement learning for dynamic maintenance decision-making

An, X., Zhou, D., Guo, Z., Meng, H., & (75170), L. C. (2026) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2026.113001

Robust Lane Change Decision for Autonomous Vehicles: A Causal-Invariant Adversarial Reinforcement Learning Approach

Wang, Y.-J., Wang, K.-Y., Niu, Y.-C., Zhang, Z.-X., Li, Q., & Mao, X.-H. (2026) · IEEE transactions on intelligent transportation systems (Print) · doi:10.1109/tits.2026.3698480

Explainable Underlying Mechanism of the Driver's Decision‐Making Process

Gim, J., Yoo, D., & Ahn, C. (2026) · IET Intelligent Transport Systems · doi:10.1049/itr2.70257

Modeling Discretionary Lane-Changing Decisions: A Multi-Vehicle Information Enhanced Machine Learning Approach

Zhu, C., Yao, J., & Aernali, A. (2026) · Electronics · doi:10.3390/electronics15132912

Research on intelligent driving environment perception methods based on deep integration of self-sensing concrete pavement monitoring and on-board sensor data

Liu, X., Guo, Y., Shen, H., Wang, M., & Zhou, Y. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2026.133532

Path Planning Algorithm for Self-Driving Cars Based on High-Precision Maps and Improved A*

Wang, S., Zhou, R., Shi, T., Xu, Z., & Zhao, Z. (2026) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2026-99-0588

Spiking neural network-based decision framework for real-time-ball-on-plate balancing: Sim-to-real

Fan, Y., Zhao, C., & Zhang, L. (2026) · SIMULATION · doi:10.1177/00375497261448920

Deep Reinforcement Learning and Proximal Policy Optimization for Jetbot Automation

Ramesh, G., Shreyas, J., & Sowjanya, N. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-19321-6_8

Risk-aware offline reinforcement learning for longitudinal decision-making under potential cut-in disturbances

Xue, Q., Ma, J., Zhao, X., Liu, R. C., Li, S. W., Yi, H., & Zhu, X. (2026) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2026.115773

A Multi-Stakeholder Collaborative Decision Framework for Marine Emergency Management Using Big Data

Yan, T., Guo, E., Shankar, A., & Li, S. (2026) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.418733

Rain-Aware Lane Change Decision Model for Autonomous Vehicle Using Deep Reinforcement Learning

Alzubaidi, A. A., Babu, R., Byon, Y.-J., Hosani, K. H. A., Kumar, R., & Al‐Sumaiti, A. S. (2026) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-026-11580-9

A Hybrid DDPG+MPC Framework for Safe and Efficient Autonomous Lane-Changing in Highway Overtaking

Khaleel, A., & Ballagi, Á. (2026) · Vehicles · doi:10.3390/vehicles8080194

Adaptive bus service scheduling with stochastic running times via an adversarial reinforcement learning approach

Li, G.-Y., Chow, A. H. F., & Ying, C.-S. (2026) · Transportmetrica B Transport Dynamics · doi:10.1080/21680566.2026.2718463

A DRL-Based Lane-Changing Decision Model for Connected and Automated Trucks to Reduce Congestion in Freeway Merging Areas

He, X., Chen, X., Li, P., Huang, J., Liu, A., & Yu, L. (2026) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2026.3722503

Autonomous Motion Decision-Making Considering Dual Uncertainties in Surrounding Vehicle Cut-in Intention-Action

Cao, M., Wang, C., Zhao, W., & Zhang, Z. (2026) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2026.3723895

Lane Change Strategies for Autonomous Vehicles: A Deep Reinforcement Learning Approach Based on Transformer

Li, G., Qiu, Y., Yang, Y., Li, Z., Li, S., Chu, W., Green, P., & Li, S. E. (2022) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2022.3227921 · Cited by 127

Risk-aware Deep Reinforcement Learning for Decision-making and Planning of Autonomous Vehicles

Zeng, L., Hu, W., Zhang, B., Wu, Y., & Cao, D. (2022) · CAA International Conference on Vehicular Control and Intelligence (CVCI) · doi:10.1109/cvci56766.2022.9965018 · Cited by 8

Safe Reinforcement Learning of Lane Change Decision Making with Risk-Fused Constraint

Li, Z., Xiong, L., Leng, B., Xu, P., & Fu, Z. (2023) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc57777.2023.10422331 · Cited by 16

Deep Reinforcement Learning Based Decision-Making Strategy of Autonomous Vehicle in Highway Uncertain Driving Environments

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Don't Get Yourself into Trouble! Risk-aware Decision-Making for Autonomous VehiclesPreprint

Mokhtari, K., & Wagner, A. R. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.04625 · Cited by 3