Citation

Yang HF, Ling Y, Kopca C, Ricord S, Wang Y. Transp. Res. C Emerg. Technol. 2022; 145: e103896.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.trc.2022.103896

PMID

unavailable

Abstract

Information and communication technology has many promising benefits including improvement the traffic network capacity, efficiency, and stability. However, to date, most of the improvements in signal management and interactions in connected vehicle environments focus solely on the vehicular side. This has led to a massive gap for non-motorized users and vulnerable road users. Specifically, deficit perception capability, inconsistent dissemination, obsolescent acquisition techniques, and ignorance of equality make the current experience of the active non-motorized users inconvenient and risky, especially for those with disabilities. To serve the users in an unbiased and automated way, a novel cooperated signal phase and timing (SPaT) services infrastructure -- Vision Enhanced Non-motorized Users Services (VENUS) smart node is proposed. With customized up-to-date computer vision algorithms and artificial intelligence pipelines on the edge, VENUS smart node can collect necessary active-user information (including location, class, pose direction and mobility status), and generate directional crossing request for every pedestrian and cyclist in real time. Meanwhile, the improved communication system makes the VENUS node a reliable information hub to share the SPaT messages and carry interactions to/from the signal controller, connected vehicles and user personal information devices (i.e., cell phones, wearable devices) through various protocols. Based on extensive experimentation, 1076 testing users from six intersections, the VENUS sensing achieves 90.24% accuracy on directional-aware crossing trigger generation and 89.87% accuracy on mobility status estimation for normal users and four types of disabled persons. Furthermore, the VENUS smart node is fully compatible with the connected vehicles environment, and improves the signal system at low cost, mainly due to its flexibility and adaptability with existing infrastructure. The VENUS smart node is the first connected infrastructure architecture that integrates traffic sensing, data processing and information dissemination together for the self-operating indistinguishable signal services based on edge computing.

Language: en

Keywords

Computer vision; Connected vehicle; Disability user; Edge computing; Signal Phase and Timing (SPaT); Smart infrastructure