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Lane-change detection using a computational driver model
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/2590
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| Title: | Lane-change detection using a computational driver model |
| Authors: | Salvucci, Dario D.
Mandalia, Hiren M.
Kuge, Nobuyuki
Yamamura, Tomohiro |
| Issue Date: | Jun-2007 |
| Publisher: | Human Factors & Ergonomics Society |
| Citation: | Human Factors, 49(3): pp. 532-542. |
| 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 realtime
detection of driver lane changes, the system shows good promise for incorporation
into the next generation of intelligent transportation systems. |
| URI: | http://dx.doi.org/10.1518/001872007X200157
http://hdl.handle.net/1860/2590 |
| Appears in Collections: | Faculty Research and Publications (Comp Sci)
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