NDLI: Driver Behavior and Situation Aware Brake Assistance for Intelligent Vehicles

Content Provider	IEEE Xplore Digital Library
Author	McCall, J.C. Trivedi, M.M.
Copyright Year	1963
Abstract	This paper deals with the development of Human-Centric Intelligent Driver Assistance Systems. Rear-end collisions account for a large portion of traffic accidents. To help mitigate this problem, predictive braking systems and adaptive cruise control systems have been developed. However, these types of systems usually rely solely on the vehicle and vehicle surround sensors, either ignoring the human component of driving or learning the driver's control behavior using only these sensors. As with all human-computer interfaces, this has the potential to work against the driver, distract the driver further, or even annoy the driver so that the driver ignores or disables the system. It is, therefore, important to directly take the driver's intended actions into account when designing a driver assistance system. By using a probabilistic model for the system, warnings and preventative measures can be constructed based on varying levels of situational severity and driver attentiveness and intent. The research is based upon carefully conducted experimental trials involving a human subjects driving in natural manner and on typical freeways in the USA. The experiments, designed by inputs from cognitive scientist, were conducted in a specially designed instrumented vehicle to record important cues associated with driver's behavior, vehicle state, and vehicle surround in a synchronized manner. Quantitative results and analysis of the experimental trials are presented to show the feasibility and promise of this framework to predict the driver's intent to brake, the need for braking given the current situation, and at what level the driver should be warned
Sponsorship	IEEE Publication
Starting Page	374
Ending Page	387
Page Count	14
File Size	1456039
File Format	PDF
ISSN	00189219
Volume Number	95
Issue Number	2
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-02-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent vehicles Vehicle driving Intelligent sensors Road accidents Control systems Sensor systems Humans Intelligent systems Collision mitigation Adaptive systems vehicle safety Bayesian learning human-centric driver assistance intent analysis sensor fusion
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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