End-to-End Autonomous Driving

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19 papers in the last four weeks, up 90% on the four weeks before. 0.2% of all new papers.

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Latest papers 146

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Multi-Resolution End-to-End Deep Neural Network for Optimizing Latency-Accuracy Tradeoff in Autonomous Driving
May 27, 2026Qitao Weng, Heechul YunEfficient Neural Network Inference Adaptive Inference
University of Kansas Lawrence, KS, USA
DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving
May 27, 2026Chen Shi, Jinrui Xu, Shaoshuai Shi +3Video Diffusion Models End-to-End Autonomous Driving
The Chinese University of Hong Kong, Shenzhen · Voyager Research, Didi Chuxing
ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation
May 24, 2026Zhengcheng Yu, Changze Li, Haoran Liu +1End-to-End Autonomous Driving Autonomous Parking
Tsinghua University · Shanghai Jiaotong University
NudgeVAD: Language-Nudged End-to-End Driving via FiLM Residuals
May 23, 2026Chieh-Chi Yang, Yu-Hsiang Chen, Yi-Ting ChenEnd-to-End Autonomous Driving Residual Learning
National Yang Ming Chiao Tung University
SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation
May 23, 2026Ruoyu Wang, Jingke Wang, Yukai Ma +5World Model Learning End-to-End Autonomous Driving
Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, China · Labs, Huawei
ChainFlow-VLA: Causal Flow Planning with Vision-Language Models
May 22, 2026Xiyang Wang, Xinlin Wang, Tingguang Zhou +7Trajectory Generation VLMs for Autonomous Driving
1Afari Intelligent Drive · 2Tianjin University · University of Macau
Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving
May 22, 2026Kewei Zhang, Jin Wang, Sensen Gao +9VLMs for Autonomous Driving End-to-End Autonomous Driving
1Peking University · 3The University of Hong Kong · 2NVIDIA +1
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training
May 20, 2026Hongzhi Ruan, Pei Liu, Weiliang Ma +5Autonomous Driving Datasets Synthetic Data Augmentation
Li Auto · HKUST (GZ) · HKUST
Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving
May 20, 2026Yang Wu, Qiang Meng, Zhaojiang Liu +3End-to-End Autonomous Driving World Models
SJTU · FDU · NJU
Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives
May 19, 2026Junli Wang, Zhihua Hua, Xueyi Liu +7End-to-End Autonomous Driving Imitation Learning
Institute of Automation, Chinese Academy of Sciences · Xiaomi Embodied Intelligence Team · Fudan University
HEAT: Heterogeneous End-to-End Autonomous Driving via Trajectory-Guided World Models
May 19, 2026Hoonhee Cho, Giwon Lee, Jae-Young Kang +3World Model Learning End-to-End Autonomous Driving
1All authors are with KAIST, Daejeon, Republic of Korea.
SafeAlign-VLA: A Negative-Enhanced Safe Alignment Framework for Risk-Aware Autonomous Driving
May 19, 2026Kefei Tian, Yuansheng Lian, Kai Yang +2End-to-End Autonomous Driving Risk-Sensitive RL
aCollege of Transportation, Tongji University, Shanghai, 200092, China · bDepartment of Civil Engineering, Tsinghua University, Beijing, 100084, China · cSchool of Vehicle and Mobility, Tsinghua University, Beijing, 100084, China +1
Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations
May 18, 2026Zhiyuan Zhang, Zhenghao Jin, Yanlun Peng +8Autonomous Driving Benchmarks End-to-End Autonomous Driving
Sch. of Computer Science & Sch. of Artificial Intelligence, Shanghai Jiao Tong University · Institute of Trustworthy Embodied AI (TEAI), Fudan University · Great Wall Motor +2
CLAP: Contrastive Latent-space Prompt Optimization for End-to-end Autonomous Driving
May 17, 2026Ruiyang Zhu, Yuehan He, Boyuan Zheng +4VLMs for Autonomous Driving End-to-End Autonomous Driving
University of Michigan · University of Arizona
DriveSafer: End-to-End Autonomous Driving with Safety Guidance
May 16, 2026Shounak Sural, Raj RajkumarEnd-to-End Autonomous Driving Diffusion-Based Planning
Carnegie Mellon University Pittsburgh, PA
CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning
May 14, 2026Sining Ang, Yuguang Yang, Canyu Chen +1End-to-End Autonomous Driving Value Function Estimation
Department of Automation, University of Science and Technology of China · Institute for AI Industry Research, Tsinghua University · School of Electronic Information Engineering, Beihang University +1
Learning Direct Control Policies with Flow Matching for Autonomous Driving
May 14, 2026Marcello Ceresini, Federico Pirazzoli, Andrea Bertogalli +5Flow Matching End-to-End Autonomous Driving
1Università degli Studi di Parma · 2Alma Mater Studiorum - Università di Bologna · 3VisLab (an Ambarella Inc. company)
MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving
May 13, 2026Rajeev Yasarla, Deepti Hegde, Hsin-Pai Cheng +9End-to-End Autonomous Driving Vision-Language-Action Models
Qualcomm AI Research · Qualcomm Technologies, Inc
Causality-Aware End-to-End Autonomous Driving via Ego-Centric Joint Scene Modeling
May 13, 2026Seokha Moon, Minseung Lee, Joon Seo +2Causal Representation Learning End-to-End Autonomous Driving
Korea University · Kakao Mobility
MindVLA-U1: VLA Beats VA with Unified Streaming Architecture for Autonomous Driving
May 12, 2026Yuzhou Huang, Benjin Zhu, Hengtong Lu +6VLMs for Autonomous Driving End-to-End Autonomous Driving
CUHK MMLab · Li Auto · Tsinghua University
Action Emergence from Streaming Intent
May 12, 2026Pengfei Jing, Victor Shea-Jay Huang, Hengtong Lu +3End-to-End Autonomous Driving Robot Motion Generation
1Li Auto · 3CUHK · 2Tsinghua University
DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
May 11, 2026Lingjun Zhang, Changjie Wu, Linzhe Shi +6World Model Learning End-to-End Autonomous Driving
Tsinghua University · Amap, Alibaba Group · Nanyang Technological University
Temporal Sampling Frequency Matters: A Capacity-Aware Study of End-to-End Driving Trajectory Prediction
May 11, 2026Yumao Liu, Tao Liu, Xiangyu Li +2Autonomous Driving Datasets End-to-End Autonomous Driving
The Hong Kong University of Science and Technology (Guangzhou)
HiDrive: A Closed-Loop Benchmark for High-Level Autonomous Driving
May 11, 2026Zhongyu Xia, Guanyu Zhu, Guo Tang +2Autonomous Driving Benchmarks End-to-End Autonomous Driving
Wangxuan Institute of Computer Technology, Peking University
Latency Analysis and Optimization of Alpamayo 1 via Efficient Trajectory Generation
May 9, 2026Yunseong Jeon, Namcheol Lee, Yoonsu Lee +4Efficient Inference End-to-End Autonomous Driving
Graduate School of Automobile and Mobility, Kookmin University, Seoul, Republic of Korea · Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving
May 9, 2026Rui Zhao, Jianlin Yu, Zhenhai Gao +2VLMs for Autonomous Driving End-to-End Autonomous Driving
College of Automotive Engineering, Jilin University · 2The National Key Laboratory of Automotive Chassis Integration and Bionics, Jilin University · 3ReeFocus AI Technology
REAP: Reinforcement-Learning End-to-End Autonomous Parking with Gaussian Splatting Simulator for Real2Sim2Real Transfer
May 9, 2026Changze Li, Zhe Chen, Shaoyu Chen +7End-to-End Autonomous Driving Autonomous Parking
Horizon Robotics Technology Research and Development Co., Ltd.
See Tomorrow, Act Today: Foresight-Driven Autonomous Driving
May 8, 2026Bozhou Zhang, Nan Song, Yuang Wang +3End-to-End Autonomous Driving World Models
School of Data Science, Fudan University · Shanghai Innovation Institute · Imperial College London +1
Can Attribution Predict Risk? From Multi-View Attribution to Planning Risk Signals in End-to-End Autonomous Driving
May 7, 2026Le Yang, Ruoyu Chen, Haijun Liu +3Feature Attribution End-to-End Autonomous Driving
1Sun Yat-sen University · University of Chinese Academy of Sciences · 3Nanyang Technological University
InterFuserDVS: Event-Enhanced Sensor Fusion for Safe RL-Based Decision Making
May 5, 2026Mustafa Sakhaia, Kaung Sithua, Min Khant Soe Okea +1Event-Based Vision End-to-End Autonomous Driving
aFaculty of Computer Science, Electronics and Telecommunications, AGH University of Krakow, Krakow, 30-059, Poland · bAcademic Computer Centre AGH, Krakow, 30-950, Poland

May 27, 2026, cs.ROJ/K move · Enter open · S save

Multi-Resolution End-to-End Deep Neural Network for Optimizing Latency-Accuracy Tradeoff in Autonomous Driving

Qitao Weng, Heechul Yun

University of Kansas Lawrence, KS, USA

Efficient Neural Network Inference Adaptive Inference Dynamic Neural Networks End-to-End Autonomous Driving Convolutional Neural Networks

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Latency-accuracy tradeoffs are fundamental in real-time applications of deep neural networks (DNNs) for cyber-physical systems. In autonomous driving, in particular, safety depends on both prediction quality and the end-to-end delay from sensing to actuation. We observe that (1) when latency is accounted for, the latency-optimal network configuration varies with scene context and compute availability; and (2) a single fixed-resolution model becomes suboptimal as conditions change. We present a multi-resolution, end-to-end deep neural network for the CARLA urban driving challenge using monocular camera input. Our approach employs a convolutional neural network (CNN) that supports multiple input resolutions through per-resolution batch normalization, enabling runtime selection of an ideal input scale under a latency budget, as well as resolution retargeting, which allows multi-resolution training without access to the original training dataset. We implement and evaluate our multi-resolution end-to-end CNN in CARLA to explore the latency-safety frontier. Results show consistent improvements in per-route safety metrics - lane invasions, red-light infractions, and collisions - relative to fixed-resolution baselines.

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Latest papers 146