June 5, 2024, 4:44 a.m. | Jinwei Zeng, Chao Yu, Xinyi Yang, Wenxuan Ao, Jian Yuan, Yong Li, Yu Wang, Huazhong Yang

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.02126v1 Announce Type: cross
Abstract: Traffic signal control (TSC) is a promising low-cost measure to enhance transportation efficiency without affecting existing road infrastructure. While various reinforcement learning-based TSC methods have been proposed and experimentally outperform conventional rule-based methods, none of them has been deployed in the real world. An essential gap lies in the oversimplification of the scenarios in terms of intersection heterogeneity and road network intricacy. To make TSC applicable in urban traffic management, we target TSC coordination in …

abstract arxiv city control cost cs.ai cs.lg cs.ma cs.sy eess.sy efficiency infrastructure low reinforcement reinforcement learning scale signal them traffic transportation type universal universal model while world

Senior Data Engineer

@ Displate | Warsaw

Solution Architect

@ Philips | Bothell - B2 - Bothell 22050

Senior Product Development Engineer - Datacenter Products

@ NVIDIA | US, CA, Santa Clara

Systems Engineer - 2nd Shift (Onsite)

@ RTX | PW715: Asheville Site W Asheville Greenfield Site TBD , Asheville, NC, 28803 USA

System Test Engineers (HW & SW)

@ Novanta | Barcelona, Spain

Senior Solutions Architect, Energy

@ NVIDIA | US, TX, Remote