ITrip: Traffic signal prediction using smartphone based community sensing

Junhao Zheng, Jiannong Cao, Zongjian He, Xuefeng Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Providing drivers with traffic signal scheduling information in advance can enable many novel applications, such as optimal speed advisory and shortest trip planning. Existing solutions employ either infrastructure (e.g. wireless transmitter) or vision (e.g. cameras) based approaches. However, these solutions may be limited by high infrastructure cost or low air visibility. In this paper, we propose iTrip, a novel community sensing service that only utilizes smartphone accelerometer to detect and predict accurate traffic signal schedules. In iTrip, on-vehicle smartphones detect and report vehicle's events, such as start and stop moving, to the server. Using the collected data contributed by a group of vehicles, iTrip can predict the traffic signal in near future by estimating the traffic signal schedule. We conduct extensive simulation under different traffic scenarios. Results show our proposed method is able to efficiently estimate the schedule with accuracy less than 1 second in a few signal cycles.
Original languageEnglish
Title of host publication2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
PublisherIEEE
Pages2944-2949
Number of pages6
ISBN (Electronic)9781479960781
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014 - Qingdao, China
Duration: 8 Oct 201411 Oct 2014

Conference

Conference2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014
CountryChina
CityQingdao
Period8/10/1411/10/14

ASJC Scopus subject areas

  • Computer Science Applications
  • Automotive Engineering
  • Mechanical Engineering

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