Flexible Car-Following Models on Mixed Traffic Trajectory Data
Intelligent transportation systems require detailed car-following models that could represent driving behavior in an efficient way. Moving towards autonomous vehicles, models should be able to reflect heterogeneity in driving behaviour and traffic networks. While many driving behavior models have been developed over the years, there are still aspects that remain unsolved. Most existing studies focus on driving behavior using trajectory data of vehicles moving in lanes. However, modeling driving behavior in mixed traffic streams is still a challenge. A heterogoneous mixture of vehicle types and a violation of lane discipline are common characteristics of cities in the developing world. This research explores the feasibility and the benefits of using an existing flexible car-following model on mixed traffic trajectory data, which have been collected in India and are freely available at http://toledo.net.technion.ac.il/downloads. The proposed model is based on data-driven methods, which are increasingly used in transportation applications in recent years. In addition, a conventional car-following model, the Gipps’ model, is used as a reference benchmark in order to monitor and evaluate the effectiveness of the proposed method. Flexibility of data-driven methods allows a more robust and reliable representation of driving behavior.
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Supplemental Notes:
- This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.
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Corporate Authors:
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Authors:
- Papathanasopoulou, Vasileia
- Antoniou, Constantinos
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Conference:
- Transportation Research Board 96th Annual Meeting
- Location: Washington DC, United States
- Date: 2017-1-8 to 2017-1-12
- Date: 2017
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 16p
- Monograph Title: TRB 96th Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Car following; Intelligent transportation systems; Traffic models; Trajectory; Vehicle mix
- Uncontrolled Terms: Heterogeneity (Traffic)
- Geographic Terms: India
- Subject Areas: Data and Information Technology; Highways; Planning and Forecasting;
Filing Info
- Accession Number: 01628908
- Record Type: Publication
- Report/Paper Numbers: 17-06671
- Files: TRIS, TRB, ATRI
- Created Date: Mar 15 2017 5:15PM