Lane-Change Detection Using a Computational Driver Model

Human Factors - Tập 49 Số 3 - Trang 532-542 - 2007
Dario D. Salvucci1, Hiren M. Mandalia2, Nobuyuki Kuge3, Tomohiro Yamamura3
1Department of Computer Science, Drexel University, 3141 Chestnut St., Philadelphia, PA 19104, USA. [email protected]
2Drexel University, Philadelphia, Pennsylvania
3Nissan Motor Company, Atsugi, Japan

Tóm tắt

Objective: This paper introduces a robust, real-time system for detecting driver lane changes. Background: As intelligent transportation systems evolve to assist drivers in their intended behaviors, the systems have demonstrated a need for methods of inferring driver intentions and detecting intended maneuvers. Method: Using a “model tracing” methodology, our 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. Results: 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. Conclusion: The model-tracing system is the first system to demonstrate high sample-by-sample accuracy at low false alarm rates as well as high accuracy over the course of a lane change with respect to time and lateral movement. Application: By providing robust real-time detection of driver lane changes, the system shows good promise for incorporation into the next generation of intelligent transportation systems.

Từ khóa


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Thông tin xuất bản

Human Factors

Tập 49 Số 3

532-542

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