Traffic Signal Phase and Timing Estimation based on Mobile Crowdsourcing 


Vol. 44,  No. 2, pp. 299-309, Feb.  2019
10.7840/kics.2019.44.2.299


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  Abstract

Intelligent transportation systems, signal phase and timing (SPaT) In this paper, we present a novel signal phase and timing estimation (SPaT) algorithm using mobile crowdsourcing platform (MCP). In the MCP, driver’s CrowdNavi app detects the traffic light by running a deep-learning and a region-of-interest (ROI) algorithm based on the public data on the location and type of traffic light. It also determines the signal phase using linear regression of light color and the relative position and shape of traffic light, and then sends the phase intervals to the MCP server. We also propose a few estimation algorithms of MCP server that estimate not only the cycle period and the type of signal pattern, but also the timing information of each phase. The experimental results at the intersection in front of Pusan National University main gate show that the proposed estimation algorithms can accurately estimate the cycle period, signal pattern, and the timining of each phase. stimation, mobile crowdsouring, public data, navigation.

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  Cite this article

[IEEE Style]

J. Park and H. Jeong, "Traffic Signal Phase and Timing Estimation based on Mobile Crowdsourcing," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 2, pp. 299-309, 2019. DOI: 10.7840/kics.2019.44.2.299.

[ACM Style]

Jae-Hyun Park and Han-You Jeong. 2019. Traffic Signal Phase and Timing Estimation based on Mobile Crowdsourcing. The Journal of Korean Institute of Communications and Information Sciences, 44, 2, (2019), 299-309. DOI: 10.7840/kics.2019.44.2.299.

[KICS Style]

Jae-Hyun Park and Han-You Jeong, "Traffic Signal Phase and Timing Estimation based on Mobile Crowdsourcing," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 2, pp. 299-309, 2. 2019. (https://doi.org/10.7840/kics.2019.44.2.299)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880