Autonomous Driving Planning

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30 papers in the last four weeks, up 76% on the four weeks before. 0.3% of all new papers.

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Real-Time Evaluation of Autonomous Systems under Adversarial Attacks
May 5, 2026Adithya Mohan, Xujun Xie, Venkatesh Thirugnana Sambandham +1Autonomous Driving Safety Evaluation Adversarial Robustness
AI Motion Institute, Technische Hochschule Ingolstadt, Germany
Unified Map Prior Encoder for Mapping and Planning
May 4, 2026Zongzheng Zhang, Sizhe Zou, Guantian Zheng +12End-to-End Autonomous Driving Autonomous Driving
Institute for AI Industry Research (AIR), Tsinghua University. · Bosch Corporate Research, China. · Shanghai Jiao Tong University. +1
Parking Assistance for Trailer-Truck Transport Vehicles Using Sensor Fusion and Motion Planning
May 4, 2026George Alenchery, Thomas Jeske, Tova Quinones +4Nonlinear MPC Autonomous Parking
Software Engineering Department Florida Gulf Coast University
MILD: Mediator Agent System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle Collaboration
May 2, 2026Jiyao Wang, Yunbiao Wang, Yubo Jiao +6AI Alignment AI Agent Safety
Department of Civil Engineering, McGill University, Montreal H3A 0G4, Quebec, Canada · Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, Guangdong, China · Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg L-4365, Luxembourg
VLADriver-RAG: Retrieval-Augmented Vision-Language-Action Models for Autonomous Driving
May 1, 2026Rui Zhao, Haofeng Hu, Zhenhai Gao +2Retrieval-Augmented Generation VLMs for Autonomous Driving
College of Automotive Engineering, Jilin University · The National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University · ReeFocus AI Technology
Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive
Apr 30, 2026Yiru Wang, Anqing Jiang, Shuo Wang +4Autonomous Driving Benchmarks Autonomous Driving Safety Evaluation
Bosch Corporate Research, Bosch (China) Investment Ltd., Shanghai, China
Judge, Then Drive: A Critic-Centric Vision Language Action Framework for Autonomous Driving
Apr 30, 2026Lijin Yang, Jianing Huang, Zhongzhan Huang +2VLMs for Autonomous Driving Vision-Language-Action Models
Bosch Research
PALCAS: A Priority-Aware Intelligent Lane Change Advisory System for Autonomous Vehicles using Federated Reinforcement Learning
Apr 29, 2026Yassine Ibork, Nhat Ha Nguyen, Myounggyu Won +1Federated RL Autonomous Driving
School of Computing, Wichita State University · Department of Computer Science, University of Memphis
ProDrive: Proactive Planning for Autonomous Driving via Ego-Environment Co-Evolution
Apr 28, 2026Chuyao Fu, Shengzhe Gan, Zhuoli Ouyang +5End-to-End Autonomous Driving World Models
1Southern University of Science and Technology · 2Hong Kong University of Science and Technology
Hybrid A*-Based Reverse Path-Planning of a Vehicle with Trailer System
Apr 27, 2026Xincheng Cao, Haochong Chen, Bilin Aksun-Guvenc +6Motion Planning Autonomous Driving Planning
Automated Driving Lab, Department of Mechanical and Aerospace Engineering, The Ohio State University, Columbus, OH 43210, USA · Hyundai America Technical Center, Inc. (HATCI), Superior Township, MI 48198, USA
Large Language Model based Interactive Decision-Making for Autonomous Driving
Apr 26, 2026Xinwei Dong, Jiyang Li, Jiabin Xie +5Language Model-Based Control Autonomous Driving
College of Transportation, Tongji University, Shanghai 201804, China · School of Automotive Studies, Tongji University, Shanghai 201804, China · School of Computer Science and Technology, Tongji University, Shanghai 201804, China
Cross-Stage Coherence in Hierarchical Driving VQA: Explicit Baselines and Learned Gated Context Projectors
Apr 24, 2026Gautam Kumar Jain, Carsten Markgraf, Julian StählerVisual Question Answering VLMs for Autonomous Driving
Technische Hochschule Augsburg TTZ Landsberg, Landsberg am Lech, Germany
MISTY: High-Throughput Motion Planning via Mixer-based Single-step Drifting
Apr 23, 2026Yining Xing, Zehong Ke, Yiqian Tu +3Trajectory Generation Diffusion-Based Planning
School of Vehicle and Mobility, Tsinghua University, Beijing, China · State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University, Beijing, China
Reasoning About Traversability: Language-Guided Off-Road 3D Trajectory Planning
Apr 23, 2026Byounggun Park, Soonmin HwangVLM Adaptation Motion Planning
Department of Automotive Engineering, Hanyang University, Seoul, Republic of Korea
Lexicographic Minimum-Violation Motion Planning using Signal Temporal Logic
Apr 22, 2026Patrick Halder, Lothar Kiltz, Hannes Homburger +2Motion Planning MPPI Control
School of Computation, Information and Technology, Technical University of Munich, 85748 Garching, Germany · 2ZF Friedrichshafen AG, 88046 Friedrichshafen, Germany · Institute of System Dynamics, HTWG Konstanz, 78562 Konstanz, Germany
Toward Cooperative Driving in Mixed Traffic: An Adaptive Potential Game-Based Approach with Field Test Verification
Apr 22, 2026Shiyu Fang, Xiaocong Zhao, Xuekai Liu +4Intelligent Transportation Systems Autonomous Driving
Key Laboratory of Road and Traffic Engineering of the State, Ministry of Education, Tongji University, Shanghai, 201804, China · State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University, Beijing, 100084, China · State Key Lab of Intelligent Transportation System, School of Transportation Science and Engineering, Beihang University, Beijing, 100191, China
SpanVLA: Learning from Negative-Recovery Samples with Fast Action Bridging for Vision-Language-Action Model
Apr 21, 2026Zewei Zhou, Ruining Yang, Xuewei Qi +7VLMs for Autonomous Driving Autonomous Driving
Tony · University of California, Los Angeles, USA · Motional, USA +1
OneDrive: Unified Multi-Paradigm Driving with Vision-Language-Action Models
Apr 20, 2026Yiwei Zhang, Xuesong Chen, Jin Gao +5VLMs for Autonomous Driving End-to-End Autonomous Driving
State Key Laboratory of Multimodal Artificial Intelligence Systems, CASIA · School of Artificial Intelligence, University of Chinese Academy of Sciences · AutoLab, School of Artificial Intelligence, Shanghai Jiao Tong University +2
Evolution of Lane-Changing Behavior in Mixed Traffic: A Quantum Game Theory Approach
Apr 17, 2026Sungyong Chung, Tina Radvand, Alireza TalebpourHuman Behavior Simulation Autonomous Driving Planning
Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign
RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework
Apr 16, 2026Hao Gao, Shaoyu Chen, Yifan Zhu +4Diffusion-Based Planning RL for Diffusion Models
Huazhong University of Science & Technology · Horizon Robotics
Mosaic: An Extensible Framework for Composing Rule-Based and Learned Motion Planners
Apr 15, 2026Nick Le Large, Marlon Steiner, Lingguang Wang +4Safe Motion Planning Motion Planning
Institute of Measurement and Control Systems, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany · FZI Research Center for Information Technology, Karlsruhe, Germany
DriveVA: Video Action Models are Zero-Shot Drivers
Apr 5, 2026Mengmeng Liu, Diankun Zhang, Jiuming Liu +7Action-Conditioned Video Generation World Models
University of Twente, The Netherlands · Xiaomi EV, China · University of Cambridge, United Kingdom +1
Deconfounded Lifelong Learning for Autonomous Driving via Dynamic Knowledge Spaces
Mar 15, 2026Jiayuan Du, Yuebing Song, Yiming Zhao +6End-to-End Autonomous Driving Lifelong Learning Agents
Tongji University, Shanghai, China
PC-Diffuser: Path-Consistent Capsule CBF Safety Filtering for Diffusion-Based Trajectory Planner
Mar 11, 2026Eugene Ku, Yiwei LyuConstrained Motion Planning Trajectory Generation
Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA
VertiAdaptor: Online Kinodynamics Adaptation for Vertically Challenging Terrain
Mar 6, 2026Tong Xu, Chenhui Pan, Aniket Datar +1Dynamical Systems Online System Identification
Department of Computer Science, George Mason University
HERMES: A Holistic End-to-End Risk-Aware Multimodal Embodied System with Vision-Language Models for Long-Tail Autonomous Driving
Feb 1, 2026Weizhe Tang, Junwei You, Jiaxi Liu +7VLMs for Autonomous Driving End-to-End Autonomous Driving
Department of Civil and Environmental Engineering, University of Wisconsin–Madison, Madison, WI 53711 USA
Drive-JEPA: Video JEPA Meets Multimodal Trajectory Distillation for End-to-End Driving
Jan 29, 2026Linhan Wang, Zichong Yang, Chen Bai +6End-to-End Autonomous Driving Joint-Embedding Predictive Architecture
Virginia Tech · Purdue University · XPENG Motors +1
UniDrive-WM: Unified Understanding, Planning and Generation World Model for Autonomous Driving
Jan 7, 2026Zhexiao Xiong, Xin Ye, Burhan Yaman +5Vision-Language Models World Model Learning
Bosch Research North America · Bosch Center for Artificial Intelligence (BCAI) · Arizona State University +2
AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving
Jan 5, 2026Yanhao Wu, Haoyang Zhang, Fei He +6Collision Avoidance End-to-End Autonomous Driving
School of Software Engineering, XJTU · Horizon Robotics · Shenzhen Loop Area Institute +1
SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving
Dec 11, 2025Peizheng Li, Zhenghao Zhang, David Holtz +6Vision-Language Models VLMs for Autonomous Driving
Mercedes-Benz AG · TU Munich · Karlsruhe Institute of Technology +4

May 5, 2026, cs.AIJ/K move · Enter open · S save

Real-Time Evaluation of Autonomous Systems under Adversarial Attacks

Adithya Mohan, Xujun Xie, Venkatesh Thirugnana Sambandham, Torsten Schön

AI Motion Institute, Technische Hochschule Ingolstadt, Germany

Autonomous Driving Safety Evaluation Adversarial Robustness Imitation Learning Adversarial Perturbations Autonomous Driving Planning Trajectory Prediction

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Most evaluations of autonomous driving policies under adversarial conditions are conducted in simulation, due to cost efficiency and the absence of physical risk. However, purely virtual testing fails to capture structural inconsistencies, supervision constraints, and state-representation effects that arise in real-world data and fundamentally shape policy robustness. This work presents an offline trajectory-learning and adversarial robustness evaluation framework grounded in real-world intersection driving data. Within a controlled data contract, we train and compare three trajectory-learning paradigms: Multi-Layer Perceptron (MLP)-based Behavior Cloning (BC), Transformer-based object-tokenized BC, and inverse reinforcement learning (IRL) formulated within a Generative Adversarial Imitation Learning (GAIL) framework. Models are evaluated using Average Displacement Error (ADE) and Final Displacement Error (FDE). Inference-time robustness is assessed by subjecting trained policies to gradient-based adversarial perturbations across multiple intersection scenarios, yielding a structured robustness evaluation matrix. Results show that state-structure design and architectural inductive biases critically influence adversarial stability, leading to markedly different robustness profiles despite comparable nominal prediction accuracy (ADE < 0.08). Inference-time Projected Gradient Descent (PGD) attacks induce final displacement errors of up to approximately 8 meters. The proposed framework establishes a scalable benchmark for studying offline trajectory learning and adversarial robustness in real-world autonomous driving settings.

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Latest papers 250