most citedReducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning

22 citations · 49 across the 6 of their papers we have counts for

collaborators

8 papers

math.OC20213 cited

Cooperation Method of Connected and Automated Vehicles at Unsignalized Intersections: Lane Changing and Arrival Scheduling

Chaoyi Chen, Mengchi Cai, Jiawei Wang +4

The cooperation of connected and automated vehicles (CAVs) has shown great potential in improving traffic efficiency during intersection management. Existing research mainly focuse…

eess.SY2021

Multi-lane Unsignalized Intersection Cooperation with Flexible Lane Direction based on Multi-vehicle Formation Control

Mengchi Cai, Qing Xu, Chaoyi Chen +4

Unsignalized intersection cooperation of connected and automated vehicles (CAVs) is able to eliminate green time loss of signalized intersections and improve traffic efficiency. Mo…

cs.RO20218 cited

Formation Control with Lane Preference for Connected and Automated Vehicles in Multi-lane Scenarios

Mengchi Cai, Chaoyi Chen, Jiawei Wang +4

Multi-lane roads are typical scenarios in the real-world traffic system. Vehicles usually have preference on lanes according to their routes and destinations. Few of the existing s…

cs.LG202122 cited

Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning

Jiawei Wang, Lijun Sun

The bus system is a critical component of sustainable urban transportation. However, due to the significant uncertainties in passenger demand and traffic conditions, bus operation…

eess.SY2021

Formation Control for Connected and Automated Vehicles on Multi-lane Roads: Relative Motion Planning and Conflict Resolution

Mengchi Cai, Qing Xu, Chaoyi Chen +4

Multi-vehicle coordinated decision making and control can improve traffic efficiency while guaranteeing driving safety. Formation control is a typical multi-vehicle coordination me…

math.OC20216 cited

A Graph-based Conflict-free Cooperation Method for Intelligent Electric Vehicles at Unsignalized Intersections

Chaoyi Chen, Qing Xu, Mengchi Cai +6

Electric, intelligent, and network are the most important future development directions of automobiles. Intelligent electric vehicles have shown great potentials to improve traffic…