2010 IEEE Intelligent Vehicles Symposium 2010
DOI: 10.1109/ivs.2010.5548085
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Bézier curve based path planning for autonomous vehicle in urban environment

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Cited by 117 publications
(62 citation statements)
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“…The NHTSA conducted a study concluding that 94% of accidents are due to human errors, where a great amount of these crashes (33%) is related to wrong decisions during driving process [1]. In 2009, 2.4% of fatalities in the United States were related to a common problem for drivers, i.e., drowsiness [2]. Considering these points, automated driving technology promises a great reduction in crash incidents, adding efficiency in fuel consumption, reduction of parking spaces (ride-sharing), and inclusion of elderly and people with disabilities [3].…”
Section: Introductionmentioning
confidence: 99%
“…The NHTSA conducted a study concluding that 94% of accidents are due to human errors, where a great amount of these crashes (33%) is related to wrong decisions during driving process [1]. In 2009, 2.4% of fatalities in the United States were related to a common problem for drivers, i.e., drowsiness [2]. Considering these points, automated driving technology promises a great reduction in crash incidents, adding efficiency in fuel consumption, reduction of parking spaces (ride-sharing), and inclusion of elderly and people with disabilities [3].…”
Section: Introductionmentioning
confidence: 99%
“…Moreover, in urban environment -with frequent turns 90 degrees bends-the trend is to use clothoid-circle-clothoid [8], [11] concatenations, which results in a more complex tracking of the generated trajectory. For this reason, others authors have used others metrics for real time implementations, suc as splines [12], or Bezier Curves [5].…”
Section: Introductionmentioning
confidence: 99%
“…Several works have been done in this aim, for instance, the Toyota Technological Institute have tested Bezier curve based path planner in a single-seater electronic vehicle with an anti-collision system [11]. Here, the authors generate an alternative path for avoiding the obstacle, however, the curvature, jerk or lateral acceleration have been despised in the path generation.…”
Section: Introductionmentioning
confidence: 99%
“…There are still other path planning algorithm presented, which is mainly used for on-road driving, such as [12]- [14]. Most of the aforementioned methods try to find a path which is usually best for one specific scenario, and are lack of generality.…”
Section: Introductionmentioning
confidence: 99%