Traffic Management for Automated Highway Systems Using Model-Based Predictive Control

Abstract

We present an integrated traffic management and control approach for automated highway systems (AHS). The AHS consist of interacting roadside controllers and intelligent vehicles that are organized in platoons with short intraplatoon distances and larger distances between platoons. All vehicles are assumed to be fully automated, i.e., throttle, braking, and steering commands are determined by an automated onboard controller. The proposed control approach is based on a hierarchical traffic control architecture for AHS, and it also takes the connection and transition between the nonautomated part of the road network and the AHS into account. In particular, we combine dynamic speed limits and lane allocation for the platoons on the AHS highways with access control for the on-ramps using ramp metering, and we propose a model-based predictive control approach to determine optimal speed limits and lane allocations, as well as optimal release times for the platoons at the on-ramps. To illustrate the potential of the proposed traffic control method, we apply it to a simple simulation example.