Time-Optimal Coordination for Connected and Automated Vehicles at Adjacent Intersections

Decentralized Coordination of Autonomous Vehicles at intersections

In this paper, the decentralized coordination of point-mass autonomous vehicles at intersections using navigation functions is considered. As main contribution, the inertia of the vehicles is taken into account to enable on-board energy optimization for crossing. In such a way, heavier vehicles that need more energy and time for acceleration or breaking are given an indirect priority at interse...

Optimal cooperative motion planning for vehicles at intersections

We consider the problem of cooperative intersection management. It arises in automated transportation systems for people or goods but also in multi-robots environment. Therefore many solutions have been proposed to avoid collisions. The main problem is to determine collision-free but also deadlockfree and optimal algorithms. Even with a simple definition of optimality, finding a global optimum ...

Network-wide adaptive tolling for connected and automated vehicles

Optimizing Signalized Intersections Performance under Conventional and Automated Vehicles Traffic

Automated vehicles, or AVs (i.e. those that have the ability to operate without a driver and can communicate with the infrastructure) may transform the transportation system. This study develops and simulates an algorithm that can optimize signal control simultaneously with the AV trajectories under undersaturated traffic flow of AV and conventional vehicles. This proposed Intelligent Intersect...

Focus: Managing Autonomous Vehicles at Intersections

Since 1970, centralized traffic-control systems have been installed to meet the demand of increasing mobility. Thus, roads can be used much more flexibly. Nevertheless, resources for centralized systems lack scalability, and the maintenance of such systems involves high cost and much effort. The significant and rapidly increasing improvements in communication and information technology, as well...