Model-based control strategy for oversaturated traffic regimes based on the LWR-IM traffic model

Abstract

Model-based optimal control strategies were capable of handling saturated traffic regimes with the ability to maintain optimised network performance. However, the upstream queue spillback which was not considered by these strategies renders an inefficient handling of oversaturated traffic regime. Hence, oversaturated situations needs both traffic flow coordination and queue spillback regulation. Here, the author aims to regulate oversaturated regimes with model-based control strategy (MCS) based on the Lighthill-Whitham-Richards–integrated model (LWR-IM) traffic model. A traffic simulator which was developed in a previous work is further extended with the proposed MCS. The MCS comprised of a rolling horizon network prediction and control algorithms at both the network and intersection levels. Based on future predictions of platoon sizes, arrival times, and queues; phase durations are adjusted at the intersection level by employing a proportionate methodology in responding to the incoming platoons and a regulation strategy to handle queue spillback. The proposed MCS was tested on real-world traffic via simulations to assess its performance compared to existing fixed-time system. The MCS improved the average delays and network throughput significantly and manage to keep queues from spilling back upstream. In addition, the strategy is feasible for real-time implementation.