Abstract

Pushbutton control is ideal for midblock crossings with low pedestrian and vehicle demand, but it causes significant interruptions to traffic flow with frequent pedestrian crossing requests. Therefore, we propose an adaptive midblock crossing control (AMCC) that minimizes the impact of the pushbutton on traffic flow while maintaining a reasonably short pedestrian wait time (PWT). We regard the midblock crossing and two adjacent intersections as an integrated system and propose two types of AMCCs—AMCC-band and AMCC-vehicle—based on different types of real-time information. AMCC-band seeks the best PWT at the midblock crossing to minimize the green band loss with downstream intersections using the signal control status of adjacent intersections. Alternatively, AMCC-vehicle leverages real-time vehicle location information [e.g., obtained from vehicle-to-infrastructure (V2I) communication, connected vehicles (CVs), or advanced sensors] to minimize the estimated number of affected vehicles. Our study tests AMCC in the software Simulation of Urban MObility (SUMO) with a two-intersection traffic network. Results show that using AMCC at a midblock crossing significantly reduces vehicle delay under a wide range of traffic conditions compared to using a fixed phase and timing (Fixed) control or a pedestrian light-controlled (Pelican) crossing. The average pedestrian delay of AMCC is slightly above Pelican but much lower than Fixed. In addition, the two types of AMCCs work equally well in reducing vehicle delay, but the AMCC-vehicle has a considerably lower pedestrian delay. The results demonstrate the advantages of AMCC in reducing vehicle and pedestrian delay and vehicle stops, improving traffic efficiency at the arterial. Furthermore, the sensitivity analysis shows that the AMCC approach is adaptive to a broad range of traffic demands. Our method extends the application scope of common pushbutton control methods. We conclude that AMCC contributes to a more traffic-efficient, more pedestrian-friendly, and safer transportation system.

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Data Availability Statement

All data, models, and code generated or used during the study appear in the published article. Detailed code is available at https://github.com/Lucky-Fan/AMCCs.

Acknowledgments

This research is supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada Industrial Research Chairs (IRC) grants.

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 148Issue 4April 2022

History

Received: Jun 21, 2021
Accepted: Dec 14, 2021
Published online: Feb 4, 2022
Published in print: Apr 1, 2022
Discussion open until: Jul 4, 2022

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Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton, AB, Canada T6G 1H9. ORCID: https://orcid.org/0000-0001-6220-8323. Email: [email protected]
Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton, AB, Canada T6G 1H9. ORCID: https://orcid.org/0000-0001-6346-3158. Email: [email protected]
Ph.D. Student, Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton, AB, Canada T6G 1H9. Email: [email protected]
Ph.D. Candidate, Dept. of Civil Engineering, McGill Univ., Montreal, QC, Canada H3A 0C3. ORCID: https://orcid.org/0000-0003-4770-4702. Email: [email protected]
Tony Z. Qiu [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton, AB, Canada T6G 1H9 (corresponding author). Email: [email protected]

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