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The adaptive signal control technology (ASCT) is a Transportation Systems Management and Operations (TSM&O) strategy that automatically and dynamically adjusts the signal timing parameters to optimize corridor performance based on real-time traffic demand. This study quantifies the mobility benefits of the ASCT using a Bayesian switch-point regression (BSR) model. The analysis was based on a 3.3-mile corridor along Mayport Road in Jacksonville, Florida. The results revealed that ASCT increases travel speeds by 4% on mid-week days (Tuesday, Wednesday, and Thursday) in the northbound direction. However, mixed results were observed in the southbound direction, which may be attributed to congestion and higher driveway density. The BSR model results revealed that there is a significant difference in the operating characteristics between the with and without ASCT scenarios. These findings may provide researchers and practitioners with an effective means for conducting an economic appraisal of the ASCT strategy, a key consideration for transportation agencies when planning future ASCT deployments.

This paper was sponsored by TRB committee AED60 Standing Committee on Statistical Methods.

TRBAM-21-03279

English

21p

2021

Transportation Research Board 100th Annual Meeting

Web

Figures; References; Tables

Adaptive control; Bayes' theorem; Mobility; Quantitative analysis; Regression analysis; Speed; Traffic signal controllers; Traffic signal timing; Transportation system management

Transportation systems management and operations (TSMO)

Jacksonville (Florida)

Highways; Operations and Traffic Management

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-03279

TRIS, TRB, ATRI

Dec 23 2020 11:23AM