Lane-Change Detection Using a Computational Driver Model
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
Tài liệu tham khảo
Barfield, W., 1997, Human factors in intelligent transportation systems
Chovan, J.D., 1994, Examination of lane change crashes and potential IVHS countermeasures (Tech. Rep. No. DOT-HS-808-701/DOT-VNTSC-NHTSA-93-2)
Frederiksen, J.R. & White, B.Y. (1990). Intelligent tutors as intelligent testers. In N. Frederiksen, R. Glaser, A. Lesgold, & M. G. Shafto (Eds.), Diagnostic monitoring of skill and knowledge acquisition (pp. 1-25). Hillsdale, NJ : Erlbaum.
Hetrick, S., 1997, Examination of driver lane change behavior and the potential effectiveness of warning onset rules for lane change or "side" crash avoidance systems
Horvitz, E., Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence
Kuge, N., Proceedings of the Society of Automotive Engineers World Congress 2000
Lee, S.E., 2004, A comprehensive examination of naturalistic lane changes (Tech. Rep. DOT-HS-809-702)
Mandalia, H.M., Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting
McCall, J., IEEE Transactions on Intelligent Transportation Systems
Michon, J. A., 1993, Generic intelligent driver support system
Olsen, E.C.B., 2003, Modeling slow lead vehicle lane changing
Salvucci, D.D., Proceedings of the Human Factors Ergonomics Society 48th Annual Meeting
Salvucci, D.D., Proceedings of the 25th Annual Conference of the Cognitive Science Society
Tijerina, L., Proceedings of the 84th Annual Meeting of the Transportation Research Board [CD-ROM]
Waibel, A., 1990, Readings in speech recognition