Development of online scalable approach for identifying secondary crashes

Hong Yang, Kaan Ozbay, Ender Faruk Morgul, Bekir Bartin, Kun Xie

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Secondary crashes are some of the most critical incidents occurring on highways. Such crashes can induce extra traffic delays and affect highway safety performance. Transportation agencies are interested in understanding the mechanism of the occurrence of secondary crashes and implementing appropriate counter measures. However, no well- established procedure identifies secondary crashes; this deficiency in turn impedes the possibility of investigating the underlying mechanism of their occurrence. The intent of this study was to develop an online scalable approach for helping to identify secondary crashes for the large number of highways with insufficient traffic surveillance units to collect the continuous traffic data required to classify such crashes accurately. The developed approach consisted of two major components: (a) acquisition of open source traffic data and (b) identification of secondary crashes through the use of these data. Unlike existing approaches based on static thresholds, queuing models, or infrastructure-based sensor data, the developed approach took advantage of various open-source data to identify traffic conditions in the presence of incidents. This study proposed to develop virtual sensors collecting traffic data from private traffic information providers such as Bing Maps, Google Maps, and MapQuest. The availability of such data greatly expands the ability of transportation agencies to cover more highways without installing infrastructure sensors. The virtual-sensor output provides the basic input to run the developed automatic identification algorithm for identifying secondary crashes. The algorithm is described step by step to provide a readily deployable approach for transportation agencies interested in identifying secondary crashes on their highway networks.

Original languageEnglish (US)
Title of host publicationTransportation Research Record
PublisherNational Research Council
Pages24-33
Number of pages10
ISBN (Electronic)9780309295666
DOIs
StatePublished - 2014

Publication series

NameTransportation Research Record
Volume2470
ISSN (Print)0361-1981

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Development of online scalable approach for identifying secondary crashes'. Together they form a unique fingerprint.

Cite this