Harnessing Digital Twin Technology for Adaptive Traffic Signal Control: Improving Signalized Intersection Performance and User Satisfaction
Sagar Dasgupta, Mizanur Rahman, Ph.D., and Steven Jones, Ph.D

TL;DR
This paper introduces two digital twin-based adaptive traffic signal control algorithms that significantly improve intersection performance and user satisfaction by reducing delays across varying traffic demands.
Contribution
The study develops and evaluates two novel digital twin algorithms for adaptive traffic signal control, demonstrating superior performance over baseline methods across different traffic conditions.
Findings
DT1 reduces control delay by up to 52% at low demands
DT1 outperforms baseline in moderate demands with 3-19% delay reduction
Both DT1 and DT2 improve user satisfaction by better delay distribution
Abstract
In this study, a digital twin (DT) technology based Adaptive Traffic Signal Control (ATSC) framework is presented for improving signalized intersection performance and user satisfaction. Specifically, real-time vehicle trajectory data, future traffic demand prediction and parallel simulation strategy are considered to develop two DT-based ATSC algorithms, namely DT1 (Digital Twin 1) and DT2 (Digital Twin 2). DT1 uses the delay experienced by each vehicle from all approaches connected to the subject intersection, while DT2 uses the delay of each vehicle that occurred in all the approaches connected to the subject intersection as well as immediate adjacent intersection. To demonstrate the effectiveness of these algorithms, the DT-based ATSC algorithms are evaluated with varying traffic demands at intersection, and individual user level. Evaluation results show that both DT1 and DT2…
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Taxonomy
TopicsTraffic control and management · Traffic Prediction and Management Techniques · Vehicle emissions and performance
