Off-Ramp Intention Generation Model for Automated Vehicles on Freeways
In recent years, the automatic driving has become a hot topic and attracted worldwide attention. This paper focuses on the off-ramp intention generation (OIG) problem of automated vehicles. When an automated vehicle driving on a freeway intends to leave the freeway by a chosen off-ramp, it needs to generate an off-ramp intention first at an appropriate distance from the off-ramp. The OIG has a significant impact on the subsequent freeway-leaving path of automated vehicles, and the model of the OIG is critical for the safety and efficiency of automated vehicles in the freeway-leaving process. However, the significance of the OIG position for the freeway-leaving path of automated vehicles have not be recognized by researchers. Therefore, for the first time, this paper aims to propose an OIG model for automated vehicles on freeways. Field data is collected to validate the proposed model. The results display that the proposed model can reflect the OIG process of vehicles on freeway and can generate an optimal OIG point for automated vehicles.
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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:
Transportation Research Board
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Authors:
- Yang, Da
- Zheng, Shiyu
- Lyu, Meng
- Jia, Bingmei
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Conference:
- Transportation Research Board 98th Annual Meeting
- Location: Washington DC, United States
- Date: 2019-1-13 to 2019-1-17
- Date: 2019
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 19p
Subject/Index Terms
- TRT Terms: Highway safety; Intelligent vehicles; Mathematical models; Off ramps; Vehicle trajectories
- Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment;
Filing Info
- Accession Number: 01698045
- Record Type: Publication
- Report/Paper Numbers: 19-06042
- Files: TRIS, TRB, ATRI
- Created Date: Mar 1 2019 3:51PM