Uncertainty Estimation of Location Information under Vehicle-Vehicle Cooperative Control
With the rapid development of vehicle intelligence and communication technology, vehicle-vehicle cooperative technology plays an increasingly important role in intelligent transportation systems. The core of vehicle-vehicle cooperative technology is the vehicle movement state data collection and interaction. In traditional vehicle data processing, global positioning system (GPS) data is mostly filtered, and the output is a single set value. In this study, an extended Kalman filter was used to filter out the uncertainty of vehicle’s motion state data, except for a single determinant, and the approximate distribution of the data was obtained. Through these distributions, the Monte Carlo method is used to calculate the safety evaluation indexes including time to collision, time headway, and safety margin. Fitting the evaluation index with the common distribution, the results show that the safety evaluation index is subject to the Burr distribution.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
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Supplemental Notes:
- © 2018 American Society of Civil Engineers.
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Zhai, Junda
- Lu, Guangquan
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Conference:
- 18th COTA International Conference of Transportation Professionals
- Location: Beijing , China
- Date: 2018-7-5 to 2018-7-8
- Publication Date: 2018-7
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 66-75
- Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility
Subject/Index Terms
- TRT Terms: Connected vehicles; Highway safety; Information processing; Kalman filtering; Location data; Uncertainty
- Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01870394
- Record Type: Publication
- ISBN: 9780784481523
- Files: TRIS, ASCE
- Created Date: Jan 23 2023 12:22PM