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 language | English (US) |
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Title of host publication | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4380-4385 |
Number of pages | 6 |
ISBN (Electronic) | 9781538670248 |
DOIs | |
State | Published - Oct 2019 |
Event | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand Duration: Oct 27 2019 → Oct 30 2019 |
Publication series
Name | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 |
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Conference
Conference | 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 |
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Country/Territory | New Zealand |
City | Auckland |
Period | 10/27/19 → 10/30/19 |
Bibliographical note
Publisher Copyright:© 2019 IEEE.