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Journal Article

Citation

Niroumand R, Tajalli M, Hajibabai L, Hajbabaie A. Transp. Res. C Emerg. Technol. 2020; 116: e102659.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.trc.2020.102659

PMID

unavailable

Abstract

This study develops a novel mixed-integer non-linear program to control the trajectory of mixed connected-automated vehicles (CAVs) and connected human-driven vehicles (CHVs) through signalized intersections. The trajectory of CAVs is continuously optimized via a central methodology, while a new "white" phase is introduced to enforce CHVs to follow their immediate front vehicle. The movement of CHVs is incorporated in the optimization framework utilizing a customized linear car-following model. During the white phase, CAVs lead groups of CHVs through an intersection. The proposed formulation determines the optimal signal indication for each lane-group in each time step. We have developed a receding horizon control framework to solve the problem. The case study results indicate that the proposed methodology successfully controls the mixed CAV-CHV traffic under various CAV market penetration rates and different demand levels. The results reveal that a higher CAV market penetration rate induces more frequent white phase indication compared to green-red signals. The proposed program reduces the total delay by 19.6%-96.2% compared to a fully-actuated signal control optimized by a state-of-practice traffic signal timing optimization software.


Language: en

Keywords

Connected and automated vehicle; Mixed-autonomy traffic; Selfdriving vehicles; White phase

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