Lane-change detection using a computational driver model.
Hum Factors
; 49(3): 532-42, 2007 Jun.
Article
in En
| MEDLINE
| ID: mdl-17552315
ABSTRACT
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.
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Collection:
01-internacional
Database:
MEDLINE
Main subject:
Automobile Driving
/
Cognition
/
Models, Psychological
Type of study:
Diagnostic_studies
Limits:
Humans
Language:
En
Journal:
Hum Factors
Year:
2007
Document type:
Article
Affiliation country:
United States