Multi-Intersection Traffic Management for Autonomous Vehicles via Distributed Mixed Integer Linear Programming

2020-07-13

This paper extends our previous work in [1],[2], on optimal scheduling of autonomous vehicle arrivals at intersections, from one to a grid of intersections. A scalable distributed Mixed Integer Linear Program (MILP) is devised that solves the scheduling problem for a grid of intersections. A computational control node is allocated to each intersection and regularly receives position and velocity information from subscribed vehicles. Each node assigns an intersection access time to every subscribed vehicle by solving a local MILP. Neighboring intersections will coordinate with each other in real-time by sharing their solutions for vehicles' access times with each other. Our proposed approach is applied to a grid of nine intersections and its positive impact on traffic flow and vehicles' fuel economy is demonstrated in comparison to conventional intersection control scenarios.

📄 PDF Abstract BibTeX arXiv:2007.06639

Code (0)

등록된 구현이 없습니다.

Tasks

Autonomous Vehicles ManagementPositionScheduling

Intelligent Autonomous Intersection Management

2022-02-09 · Udesh Gunarathna, Shanika Karunasekara, Renata Borovica-Gajic, Egemen Tanin

Connected Autonomous Vehicles will make autonomous intersection management a reality replacing traditional traffic signal control. Autonomous intersection management requires time and speed adjustment of vehicles arrivin…

Autonomous Vehicles Management Q-Learning Reinforcement Learning (RL)+1

Trajectory planning for autonomous intersection management of connected vehicles

2018-10-05 · Simulation Modelling Practice and Theory 90 (2019) 16–30 2018 10 · Bing Liua, Qing Shia, Zhuoyue Song⁎, B 외

This paper proposes a cooperative scheduling mechanism for autonomous vehicles passing through an intersection, called TP-AIM. The main objective of this research is to ensure safe driving while minimizing delay in an …

Autonomous Vehicles Management Scheduling Trajectory Planning

Trajectories and Platoon-forming Algorithm for Intersections with Heterogeneous Autonomous Traffic

2023-11-13 · P. C. Joshi, M. A. A. Boon, S. C. Borst

The anticipated launch of fully autonomous vehicles presents an opportunity to develop and implement novel traffic management systems. Intersections are one of the bottlenecks for urban traffic, and thus offer tremendous…

Autonomous Vehicles Management

Traffic Management of Autonomous Vehicles using Policy Based Deep Reinforcement Learning and Intelligent Routing

2022-06-28 · Anum Mushtaq, Irfan Ul Haq, Muhammad Azeem Sarwar, Asifullah Khan 외

Deep Reinforcement Learning (DRL) uses diverse, unstructured data and makes RL capable of learning complex policies in high dimensional environments. Intelligent Transportation System (ITS) based on Autonomous Vehicles (…

Autonomous Vehicles Deep Reinforcement Learning Management Reinforcement Learning (RL)

A Distributed Approach to Autonomous Intersection Management via Multi-Agent Reinforcement Learning

2024-05-14 · Matteo Cederle, Marco Fabris, Gian Antonio Susto

Autonomous intersection management (AIM) poses significant challenges due to the intricate nature of real-world traffic scenarios and the need for a highly expensive centralised server in charge of simultaneously control…

Autonomous Vehicles Management Multi-agent Reinforcement Learning Navigate