Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

McCall, J.C.; Wipf, David; Trivedi, Mohan M.; Rao, Bhaskar D.

doi:10.1109/tits.2007.902640

Cited by 236 publications

(142 citation statements)

References 16 publications

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“…In prior intent prediction research [1], [7], [8], head dynamics, which is a derivative of head pose, has been proposed as a pertinent cue. While robust monocular in-vehicle head pose estimation systems have been developed [9]- [11], it may be argued that head pose is not a sufficient estimate of true gaze.…”

Section: ) Awarenessmentioning

confidence: 99%

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On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes

Doshi

Trivedi

2009

IEEE Trans. Intell. Transport. Syst.

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Abstract-Driver behavioral cues may present a rich source of information and feedback for future intelligent advanced driver-assistance systems (ADASs). With the design of a simple and robust ADAS in mind, we are interested in determining the most important driver cues for distinguishing driver intent. Eye gaze may provide a more accurate proxy than head movement for determining driver attention, whereas the measurement of head motion is less cumbersome and more reliable in harsh driving conditions. We use a lane-change intent-prediction system Index Terms-Driver-assistance systems, driver behavior, driver intent inference, intelligent vehicles, machine vision, sparse Bayesian learning.

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Section: ) Awarenessmentioning

confidence: 99%

“…In this paper, we use a lane-change intent-prediction system [1] to determine the relative usefulness of eye gaze and head dynamics data. Our comparative experiments are designed to distinguish the merits of the two cues and compare their importance.…”

Section: ) Awarenessmentioning

confidence: 99%

On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes

Doshi

Trivedi

2009

IEEE Trans. Intell. Transport. Syst.

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247

124

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“…lane estimation and tracking, aids in localizing the ego-vehicle motion, which is the one of the very first and primary steps in most IDAS like lane departure warning (LDW), lane change assistance etc. [12,7]. Next, lane analysis is also shown to aid other vehicle surround analysis modules.…”

Section: Role Of Lane Analysis In Idasmentioning

confidence: 99%

“…For example in [10] lanes are used to detect vehicles more robustly because vehicles are assumed to be localized to their ego lanes. Similarly lane detection is shown to play a significant role in predicting driver intentions before lane changes occur [12,7] etc.…”

Section: Role Of Lane Analysis In Idasmentioning

confidence: 99%

Vision-Based Lane Analysis: Exploration of Issues and Approaches for Embedded Realization

Satzoda

Trivedi

2013

2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops

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“…However, vision-based detection systems are restricted from difficult environmental conditions like illumination, weather and road pavement conditions. This consequently causes the problem that most of systems [9], [10] are limited to the road with well-maintained pavement and markers.…”

Section: Introductionmentioning

confidence: 99%

Predictive Lane Detection by Interaction with Digital Road Map

Wang

Chapuis

2012

Journal of Information Processing

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This paper presents a robust hybrid approach to Predictive Lane Detection -PLD, which utilizes information from digital map to improve efficiency and accuracy to vision-based lane detector. Traditional approaches are mostly designed for well maintained and simple road conditions like motorway or interstate road with clear lane markers, to solve out the estimation problems of coming road shape as well as vehicle's position and ego-state, which however becomes ambiguous or unavailable in the complicated road environment and under difficult weather or illumination conditions. In this paper, the proposed approach refers to vehicle localization on digital map for road geometry estimation, which gives strong cues for vision-based detector to limit the search region of road candidates and suppress noise. In addition, other information from digital map like lane marker painting color and categories is utilized in the high level of data fusion on road geometry estimation. Real and synthesized road experiment results verified the effectiveness and efficiency of our approach.

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Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

Abstract: In this paper we demonstrate a driver intent inference system (DIIS)

Cited by 236 publications

References 16 publications

On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes

On the Roles of Eye Gaze and Head Dynamics in Predicting Driver's Intent to Change Lanes

Vision-Based Lane Analysis: Exploration of Issues and Approaches for Embedded Realization

Predictive Lane Detection by Interaction with Digital Road Map

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