Discovering phase timing information of traffic light systems by stop-go shockwaves

Yi Ta Chuang, Tsi-Ui Ik*, Yu-Chee Tseng, Chia Sheng Nian, Chia Hao Ching

*Corresponding author for this work

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

The cycle lengths and signal transition time of Traffic Light Systems (TLS's), or known as the Phase Timing Information (PTI), play a key role in modern transportation systems. However, such information is not always available to the public. In this paper, we propose a crowdsourcing approach to solve this problem by exploiting the stop and go events, abbreviated by SG events, of vehicles on roads happening in front of target traffic lights. The PTI discovery problem is formulated by allowing only part of the vehicles participating in the discovery process. The proposed framework starts with discovering SG events, followed by collapsing these events over multiple signal cycles into one and calculating PTI information through a shockwave technique. The crowdsourcing part may be directly implemented on smartphones. The proposed framework was verified via field trials and simulations. Our simulation results showed that, even with a low penetration rate around 3:8 percent, the root mean square errors of the cycle length, green light and red light signal transition time of a TLS are 0:04, 1:3 and 5:8 seconds, respectively. The achieved accuracy can be helpful in many PTIenabled applications.

Original languageEnglish
Article number6802433
Pages (from-to)58-71
Number of pages14
JournalIEEE Transactions on Mobile Computing
Volume14
Issue number1
DOIs
StatePublished - 1 Jan 2015

Keywords

  • crowdsourcing
  • green computing
  • intelligent transportation
  • location-based service
  • Traffic light system

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