Efficient Collection of Connected Vehicles Data with Precision Guarantees

Negin Alemazkoor, Hadi Meidani

Research output: Contribution to journalArticlepeer-review

Abstract

Connected vehicles disseminate detailed data, including their position and speed, at a very high frequency. Such data can be used for accurate real-time analysis, prediction and control of transportation systems. The outstanding challenge for such analysis is how to continuously collect and process extremely large volumes of data. To address this challenge, efficient collection of data is critical to prevent overburdening the communication systems and overreaching computational and memory capacity. In this work, we propose an efficient data collection scheme that selects and transmits only a small subset of the data to alleviate data transmission burden. As a demonstration, we have used the proposed approach to select the data points to be transmitted from 10,000 connected vehicles trips available in the Safety Pilot Model Deployment dataset. The presented results show that collection ratio can be as small as 0.05 depending on the required precision. Moreover, a simulation study was performed to evaluate the travel time estimation accuracy using the proposed data collection approach. Results show that the proposed data collection approach can significantly improve travel time estimation accuracy.

Original languageEnglish (US)
Article number8856217
Pages (from-to)4637-4645
Number of pages9
JournalIEEE Transactions on Intelligent Transportation Systems
Volume21
Issue number11
DOIs
StatePublished - Nov 2020

Keywords

  • connected vehicles
  • data compression
  • Efficient data collection
  • intelligent transportation systems

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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