Stereo-based Free Space Computation in Complex Traffic Scenarios

Badino, Hernán; Mester, Rudolf; Vaudrey, Tobi; Franke, Uwe

doi:10.1109/ssiai.2008.4512317

Cited by 25 publications

(15 citation statements)

References 12 publications

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“…Larger offsets are conceivable. This places demands that the sensing component also performs a free space analysis [44], to verify that the automatic evasion maneuvre can indeed be safely performed. Being able to detect elements of the traffic infrastructure (e.g.…”

Section: Discussionmentioning

confidence: 99%

Active Pedestrian Safety by Automatic Braking and Evasive Steering

Keller

Dang

Fritz

et al. 2011

IEEE Trans. Intell. Transport. Syst.

173

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Abstract-Active safety systems hold great potential to reduce the accident frequency and severity, by warning the driver and/or exerting automatic vehicle control ahead of crashes. This paper presents a novel active pedestrian safety system, which combines sensing, situation analysis, decision making and vehicle control. The sensing component is based on stereo vision; it fuses two complementary approaches for added robustness: motion-based object detection and pedestrian recognition. The highlight of the system is the ability to decide within a split second whether to perform automatic braking or evasive steering, and to execute this maneuver reliably, at relatively high vehicle speeds (up to 50 km/h).We performed extensive pre-crash experiments with the system on the test track (22 scenarios with real pedestrians and a dummy). We obtained a significant benefit in detection performance and improved lateral velocity estimation by the fusion of motion-based object detection and pedestrian recognition. On a fully reproducible scenario subset, involving the dummy entering laterally into the vehicle path from behind an occlusion, the system executed in over 40 trials the intended vehicle action: automatic braking (if a full stop is still possible) or else, automatic evasive steering.

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Section: Discussionmentioning

confidence: 99%

Active Pedestrian Safety by Automatic Braking and Evasive Steering

Keller

Dang

Fritz

et al. 2011

IEEE Trans. Intell. Transport. Syst.

173

View full text Add to dashboard Cite

show abstract

“…Free-space computation [47] will be necessary to define the maximum lateral and frontal distance available to safely perform the avoidance maneuver. Other sensors, including V2V and V2I communications, will be included to better understand the specific traffic situation.…”

Section: Discussionmentioning

confidence: 99%

Autonomous Pedestrian Collision Avoidance Using a Fuzzy Steering Controller

Llorca

Milanés

Alonso

et al. 2011

IEEE Trans. Intell. Transport. Syst.

154

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Abstract-Collision avoidance is one of the most difficult and challenging automatic driving operations in the domain of intelligent vehicles. In emergency situations, human drivers are more likely to brake than to steer, although the optimal maneuver would, more frequently, be steering alone. This statement suggests the use of automatic steering as a promising solution to avoid accidents in the future. The objective of this paper is to provide a collision avoidance system (CAS) for autonomous vehicles, focusing on pedestrian collision avoidance. The detection component involves a stereo-vision-based pedestrian detection system that provides suitable measurements of the time to collision. The collision avoidance maneuver is performed using fuzzy controllers for the actuators that mimic human behavior and reactions, along with a high-precision Global Positioning System (GPS), which provides the information needed for the autonomous navigation. The proposed system is evaluated in two steps. First, drivers' behavior and sensor accuracy are studied in experiments carried out by manual driving. This study will be used to define the parameters of the second step, in which automatic pedestrian collision avoidance is carried out at speeds of up to 30 km/h. The performed field tests provided encouraging results and proved the viability of the proposed approach.

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“…In [4], the road extraction is based on road borders extraction using texture classification. If the road can be considered as the dominant plane, 3D vision methods like Inverse Perspective Mapping [5], Homography estimation [6], Omnidirectional Images and optical flow [7] or active contours [8], and stereo vision [9], [10], [11].…”

Section: Introductionmentioning

confidence: 99%

Fast road detection from color images

Wang

Frémont

2013

2013 IEEE Intelligent Vehicles Symposium (IV)

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Abstract-In this paper, we present a method for drivable road detection by extracting its specular intrinsic feature from an image. The resulting detection is then used in a stereo vision-based 3D road parameters extraction algorithm. A substantial representation of the road surface, called axis-calibration, is represented as an angle in logchromaticity space. This feature provides an invariance to road surface under illuminant conditions with shadow or not. We also add a sky removal function in order to eliminate the negative effects of sky light on axiscalibration result. Then, a confidence interval calculation helps the pixels' classification to speed up the detection processing. At last, the approach is combined with a stereovision based method to filter out false detected pixels and to obtain precise 3D road parameters. The experimental results show that the proposed approach can be adapted for real-time ADAS system in various driving conditions.

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Stereo-based Free Space Computation in Complex Traffic Scenarios

Cited by 25 publications

References 12 publications

Active Pedestrian Safety by Automatic Braking and Evasive Steering

Active Pedestrian Safety by Automatic Braking and Evasive Steering

Autonomous Pedestrian Collision Avoidance Using a Fuzzy Steering Controller

Fast road detection from color images

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