Lane-Change Detection Using a Computational Driver Model
Intelligent transportation systems (ITS) need the ability to infer driver intentions and detect intended maneuvers. This study introduces a robust, real-time system for detecting driver lane changes. Using a "model tracing" methodology, the proposed system simulates a set of possible driver intentions and their resulting behaviors using a simplification of a previously validated computational model of driver behavior. The system compares the model's simulated behavior with a driver's actual observed behavior and thus continually infers the driver's unobservable intentions from her or his observable actions. For data collected in a driving simulator, the system detects 82% of lane changes within 0.5 s of maneuver onset (assuming a 5% false alarm rate), 93% within 1 s, and 95% before the vehicle moves one fourth of the lane width laterally. For data collected from an instrumented vehicle, the system detects 61% within 0.5 s, 77% within 1 s, and 84% before the vehicle moves one-fourth of the lane width laterally. This proposed model-tracing system shows promise for incorporation into the next generation of ITS. It demonstrates both high accuracy over the course of a lane change with respect to time and lateral movement as well as high sample-by-sample accuracy at low false alarm rates.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/1329271
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Authors:
- Salvucci, Dario D
- Mandalia, Hiren M
- Kuge, Nobuyuki
- Yamamura, Tomohiro
- Publication Date: 2007-6
Language
- English
Media Info
- Media Type: Print
- Features: Figures; References;
- Pagination: pp 532-542
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Serial:
- Human Factors
- Volume: 49
- Issue Number: 3
- Publisher: Sage Publications, Incorporated
- ISSN: 0018-7208
- EISSN: 1547-8181
- Serial URL: http://hfs.sagepub.com/
Subject/Index Terms
- TRT Terms: Accuracy; Behavior; Drivers; Intelligent transportation systems; Lane changing; Mathematical models; Methodology; Real time information; Simulation
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Safety and Human Factors; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01053658
- Record Type: Publication
- Files: TRIS, ATRI
- Created Date: Jul 8 2007 9:39PM