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Combined dynamic traffic assignment and control framework for multi-class disordered traffic
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AI
DOI：10.1080/19427867.2026.2632962.png)
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Abstract
En 中文
The traffic flow patterns in a network and traffic signal optimization are mutually coupled. The conventional traffic signal optimization methods disregard the spatiotemporal variation in network flows. In multi-class disordered traffic, these network flows depend on the vehicle-class-specific characteristics. The study proposes a control strategy combined with dynamic traffic assignment, incorporating the features of multi-class disordered traffic. The Combined Dynamic Traffic Assignment and Control (CDTAC) model is applied to test cases simulated with smaller and larger vehicles, for different levels of congestion, and various proportions of smaller vehicles. Results showed that, in congestion, links with a greater number of smaller vehicles require less green time, and vice versa in the uncongested case. This is because the class-specific speed dominates in congestion over the free-flow speed in determining optimum traffic signal parameters. The proposed CDTAC model yields lower system travel time than fixed control benchmarks that neglect class-specific dynamics.
Keywords:
Multi-class traffic
signal control
two-wheelers
DTA
traversable distance
Journal
T
IF:
3.3
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901
Citations:
2.1K