Traffic State Estimation Based on Kalman Filter Technique using Connected Vehicle V2V Basic Safety Messages

Rongsheng Chen, Michael W. Levin

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

Abstract

In the near future, vehicles will be equipped to receive and broadcast Basic Safety Messages (BSMs), which includes the vehicle position, speed, heading, and acceleration, to effectively avoid potential road collisions. This data with high resolution can be used to provide road information for traffic operation and management. This study proposed an algorithm using BSM data to estimate traffic states, including flow, density, and speed, based on the Kalman Filter and cell transmission model (CTM). The algorithm was tested using vehicle trajectory data generated by a CTM-based simulator. The result showed that the algorithm performed well with known parameters and had poor performance when parameter values were unknown, and the parameters were hard to be calibrated with the data from the CTM-based simulator.

Original languageEnglish (US)
Title of host publication2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4380-4385
Number of pages6
ISBN (Electronic)9781538670248
DOIs
StatePublished - Oct 2019
Event2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand
Duration: Oct 27 2019Oct 30 2019

Publication series

Name2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

Conference

Conference2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
CountryNew Zealand
CityAuckland
Period10/27/1910/30/19

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Chen, R., & Levin, M. W. (2019). Traffic State Estimation Based on Kalman Filter Technique using Connected Vehicle V2V Basic Safety Messages. In 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 (pp. 4380-4385). [8917343] (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2019.8917343