Optimizing Signalized Intersections Performance Under Conventional and Automated Vehicles Traffic
Automated vehicles or AVs (i.e., those that have the ability to operate without a driver and can communicate with the infrastructure) may transform the transportation system. This study integrates AV trajectory planning and signal phase and timing (SPaT) optimization at an isolated intersection. The...
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Veröffentlicht in: | IEEE transactions on intelligent transportation systems 2020-07, Vol.21 (7), p.2864-2873 |
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creator | Pourmehrab, Mahmoud Elefteriadou, Lily Ranka, Sanjay Martin-Gasulla, Marilo |
description | Automated vehicles or AVs (i.e., those that have the ability to operate without a driver and can communicate with the infrastructure) may transform the transportation system. This study integrates AV trajectory planning and signal phase and timing (SPaT) optimization at an isolated intersection. The proposed control algorithm functions under mixed traffic of AVs and conventional vehicles (CNVs) in real-time. The proposed system aims to achieve coordination among incoming vehicles and SPaT through joint optimization. The input to the algorithm includes vehicles arrival data, and the output consists of optimized trajectories and SPaT commands to the AVs and the signal controller, respectively, to be implemented. Comparison of the algorithm to operations with a fully actuated signal control shows 38%-52% reduction in average travel time. |
doi_str_mv | 10.1109/TITS.2019.2921025 |
format | Article |
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subjects | Algorithms automated vehicle Automation Bars Computational modeling Control algorithms Control theory Intersections Lead mixed traffic Optimization Real-time systems Signalized intersection Timing Trajectory Trajectory optimization Trajectory planning Transportation systems Travel time |
title | Optimizing Signalized Intersections Performance Under Conventional and Automated Vehicles Traffic |
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