Combining map-based inference and crowd-sensing for detecting traffic regulators

Fatemeh Saremi, Tarek Abdelzaher

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Intelligent transportation systems serve as important technologies to improve traffic safety, mobility, cost and environmental sustainability. Towards that end, a variety of applications and driver advisory tools have been developed. To work efficiently, many require knowledge of not only street maps but also elements affecting traffic flow. The most obvious elements are traffic lights and stop signs, which we shall henceforth call traffic regulators. Unfortunately, information on traffic regulators is not widely available in public databases such as Open Street Map (OSM). Prior work described crowd-sourcing solutions to predict regulator type and locations. In this paper, we improve the prediction by offering a combination of map-based modeling and crowd-sensing solutions. The modeling component reverse engineers rules for placement of traffic regulators, allowing it to predict their locations and type based on map information. Where available, crowd-sourced vehicular GPS traces are incorporated into the prediction function to improve the results. The approach is evaluated across multiple cities and is shown to outperform both crowd-sourcing alone and map-based modeling alone. It achieves a prediction accuracy level above 97% in detecting the existence and determining the type of traffic regulators in the cities considered.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-153
Number of pages9
ISBN (Electronic)9781467391009
DOIs
StatePublished - Dec 28 2015
Event12th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015 - Dallas, United States
Duration: Oct 19 2015Oct 22 2015

Publication series

NameProceedings - 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015

Other

Other12th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015
CountryUnited States
CityDallas
Period10/19/1510/22/15

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Keywords

  • crowd-sensing
  • intelligent transportation
  • street maps
  • traffic regulators

ASJC Scopus subject areas

  • Instrumentation
  • Computer Networks and Communications
  • Signal Processing

Cite this

Saremi, F., & Abdelzaher, T. (2015). Combining map-based inference and crowd-sensing for detecting traffic regulators. In Proceedings - 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015 (pp. 145-153). [7366927] (Proceedings - 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, MASS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MASS.2015.18