arXiv:2607. 09741v1 Announce Type: cross Abstract: Accurate trajectory prediction in autonomous driving hinges on modeling dynamic and context-dependent interactions among traffic agents.
By Chengyue Wang, Bin Rao, Haicheng Liao, Bonan Wang, Chengzhong Xu, Zhenning Li
Traffic prediction is a core task in intelligent transportation systems, supporting applications such as adaptive signal control, route guidance, and ride-hailing dispatch. Deep learning models, including graph convolutional networks, recurrent networks, and Transformers, achieve strong results on standard benchmarks, but their architectures are designed by hand, requiring significant expert effort and producing models that often generalize poorly across cities and datasets.
arXiv:2604. 07126v2 Announce Type: replace-cross Abstract: Predicting vehicle trajectories plays an important role in autonomous driving, transportation safety analysis, traffic operations, etc.
By Diyi Liu, Zihan Niu, Tu Xu, Xingchen Zhang, Lishan Sun
arXiv:2607. 26467v1 Announce Type: new Abstract: Traffic prediction is a core task in intelligent transportation systems, supporting applications such as adaptive signal control, route guidance, and ride-hailing dispatch.
By Truong Giang Vu, Li Yang, Richard W. Pazzi
arXiv:2608. 15929v1 Announce Type: new Abstract: Pedestrian path prediction is crucial for enhancing the safety of autonomous vehicles and advanced driver-assistance systems.
By \v{S}imon Sukup, Ariyan Bighashdel, Pavol Jancura
The paper presents a comparative study of motion planning methods from major autonomous driving benchmarks—CARLA, nuPlan, and the Waymo Open Dataset—using CARLA Leaderboard v2.1 as a unified evaluation platform. Eight representative planners (TF++, InterFuser, TCP, PDM‑Lite, MTR+MPC, CaRL, PlanT 2.0, Diffusion planner) are evaluated to highlight their strengths, weaknesses, prevailing trends, and common challenges in motion planning research.
By Merve Atasever, Alfredo Reina Corona, Zhuochen Liu, Qingpei Li, Akshay Hitendra Shah, Hans Walker, Jyotirmoy V. Deshmukh, Rahul Jain