Citation

Liu C, Yang H, Ke R, Sun W, Wang J, Wang Y. Transp. Res. Rec. 2023; 2677(9): 652-668.

Copyright

(Copyright © 2023, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981231160174

PMID

unavailable

Abstract

Numerous sensors were introduced to intelligent transportation systems (ITS) in the past decade. Consequently, new sensing technologies and the generated data attracted more and more attention, which brought new challenges, such as redundant sensors, huge maintenance costs, and data explosion, to ITS. To satisfy the core demands of traffic agencies in a more effective and efficient way, therefore, this paper proposes the idea of "Sensing as a Service" (SaaS) and implements it in the Cooperative and Comprehensive Smart Edge Node for Sensing and OpeRation (COCO SENSOR) system for practical deployments. COCO SENSOR is an innovative multi-task sensing system, which was developed to address key practical applications, including real-time vehicle counting and recognition, road-surface-condition classification, visibility estimation, and live communication among traffic controllers and road users in a single unit. COCO SENSOR introduced customized cooperative sensing and a parallel computation mechanism to increase perception accuracy and efficiency with limited computation resources on the edge device. In collaboration with the Washington State Department of Transportation and the City of Bellevue, a field experiment was conducted to test the system's performance. The results of the experiment show that the COCO SENSOR effectively fills the gap between sensing and traffic services and that it successfully executed four practical applications, including traffic-volume counting by vehicle type, traffic-status detection, road-visibility estimation, and road-surface-condition classification, with high accuracy. Additionally, a mobile app was developed for both traffic managers and users to access comprehensive traffic information and live warning messages.

Language: en