Re-Routing Strategy of Connected and Automated Vehicles Considering Coordination at Intersections

TL;DR

This paper introduces a re-routing strategy for connected and automated vehicles at intersections that optimizes overall travel time by coordinating vehicles and balancing computational efficiency with system performance.

Contribution

It presents a novel coordination-based re-routing approach for CAVs that achieves near-optimal solutions with reduced computational complexity.

Findings

The proposed method improves total travel time in simulations.

Coordination at intersections enhances traffic flow efficiency.

The approach balances optimality and computational feasibility.

Abstract

In this paper, we propose a re-routing strategy for connected and automated vehicles (CAVs), considering coordination and control of all the CAVs in the network. The objective for each CAV is to find the route that minimizes the total travel time of all CAVs. We coordinate CAVs at signal-free intersections to accurately predict the travel time for the routing problem. While it is possible to find a system-optimal solution by comparing all the possible combinations of the routes, this may impose a computational burden. Thus, we instead find a person-by-person optimal solution to reduce computational time while still deriving a better solution than selfish routing. We validate our framework through simulations in a grid network.