Key result
Enhanced multi-path progression models (M-1 and M-2) achieved lower average delays and fewer stops compared to BANDTOP and MULTIPATH, particularly under near-saturated traffic conditions.
Why the study?
Current arterial signal coordination models only target through traffic, resulting in local traffic issues.
Enhanced multi-path progression models incorporating queue clearance and length constraints improve traffic flow and reduce delays compared to traditional models.
Models may optimize arterial progression for local traffic; extends bandwidth methods but leaves open real-world validation.
The current arterial signal coordination models only target through traffic, resulting in local traffic issues. To address these issues, two enhanced multi-path progression models are proposed in this study. The first model (M-1) treats each road segment as the basic coordination unit and relaxes the uniform bandwidth constraint in traditional models. Building on this, the second model (M-2) incorporates the impact of vehicle queues. The spatial-temporal evolution of the queueing process at a signalized arterial road is modeled. The queue clearance and queue length constraints are established to enhance the continuity of coordinated traffic-flows and prevent queue spillover. Numerical results demonstrate that the proposed models effectively increase green bandwidth on critical paths. Simulation comparisons further show that, relative to BANDTOP and MULTIPATH, the models achieve lower average delays and fewer stops, with the advantages of M-2 being particularly significant under near-saturated traffic conditions.
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Wu et al. (2026) studied Traffic signal coordination. Enhanced multi-path progression models (M-1 and M-2) vs. BANDTOP and MULTIPATH was evaluated on Average delays and number of stops. Enhanced multi-path progression models (M-1 and M-2) achieved lower average delays and fewer stops compared to BANDTOP and MULTIPATH, particularly under near-saturated traffic conditions.
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