Sensors and Data Driven Approaches in Transport

Mohammad Sadrani, Constantinos Antoniou

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Sensors play an important role in collecting real-time information for transportation systems. Nowadays, several different sensor technologies, ranging from traditional ones to mobile sensors in smartphones, are being used to collect a massive data volume on the real-time location and dynamics of users. For example, most of the modern smartphones are equipped with multiple motion sensors, such as accelerometer and magnetometer sensors, which can provide an unprecedented opportunity for the monitoring of the motion status of mobile phone users. On the other hand, there are a wide variety of data mining and prediction techniques, which can support transportation researchers in analyzing raw travel data collected from sensor technologies. This article provides a review of various applications of sensor technologies in transport networks, including travel time estimation, origin–destination matrices estimation, safety analysis, driver behavior monitoring, and transportation mode inference.

Original languageEnglish
Title of host publicationInternational Encyclopedia of Transportation
Subtitle of host publicationVolume 1-7
PublisherElsevier
Pages426-431
Number of pages6
Volume6
ISBN (Electronic)9780081026724
ISBN (Print)9780081026717
DOIs
StatePublished - 1 Jan 2021

Keywords

  • Driver behavior monitoring
  • Machine learning methods
  • Origin–destination matrices estimation
  • Safety analysis
  • Sensor fusion approaches
  • Sensors
  • Smartphone-based sensors
  • Traffic data
  • Traffic network surveillance
  • Transportation mode inference
  • Travel time estimation

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