Adaptive person based signal control system in isolated connected vehicle junction

Abstract

Urban person delay and congestion have becoming an increasing important issues. Connected vehicle (CV) technologies offer opportunities for managing urban traffic efficiently to reduce vehicle delays. The adaptive signal controls in CV environments are vehicle based controls, ignoring the importance of reducing person delay and improving person mobility in urban areas. This paper proposes an innovative Adaptive Person Based Signal Control Algorithm (APBSCA) to minimize person delay at isolated urbans. APBSCA is able to explore flexible phase combinations and stage sequences to find optimal signal timing solutions in certain prediction horizon. The vehicle information including positions, speeds and occupancy levels are collected through CV technology as data sources. A three-level dynamic programming approach is adopted in APBSCA to update the predictive departure time of every vehicle surrounding junctions, which is affected by network environments and signal decisions. APBSCA figures out optimal signal timing parameters that yield highest person delay saving values indicators at isolated junction over the prediction period and implement the corresponding signal timings. The results indicate that APBSCA have better results in reducing average person delay in vehicle in terms of high occupancy vehicles. APBSCA offers significantly average person delay reduction up to 55%. The proposed APBSCA indicates that person based controls have potential benefits in reducing person delay to consistent the future urban goals of improving person mobility over vehicle based controls by better utilizing CV data incorporating occupancy levels.

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Identifiers

ORCID for Ben Waterson: orcid.org/0000-0001-9817-7119

ORCID for Bani Anvari: orcid.org/0000-0001-7916-7636

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