Evaluation of different quality functions for road course estimation using imaging radar

Sarholz, Frederik; Klappstein, Jens; Diewald, Fabian; Dickmann, Juergen; Radig, Bernd

doi:10.1109/ivs.2011.5940536

Cited by 10 publications

(2 citation statements)

References 7 publications

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“…The prediction of the driving lane is another key technology. This has to work also in bad weather like snow [13,14]. This is useful information to verify map data.…”

Section: Cut-in Collisionmentioning

confidence: 99%

"Present research activities and future requirements on automotive radar from a car manufacturer´s point of view"

Dickmann

Klappstein

Hahn

et al. 2015

2015 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)

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Automotive Radar has already found its way into nearly all car manufacturers portfolio, even for small car platforms. Over the decades, the performance requirements increased steadily from simple detector tasks in blind spot monitoring systems to multi range smart environment perception sensors. The utmost push in performance requirement is initiated with the trend towards highly automated driving. Future automotive radar systems have to provide imaging like capabilities and have to interact in radar networks, which allow for highly comprehensive perception tasks. The paper will provide an overview on state of the art automotive radar usage on the basis of the DAIMLER car platforms, will give an outline on future requirements for highly automated driving and will present recent approaches in radar based environmental perception.

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“…The prediction of the driving lane is another key technology. This has to work also in bad weather like snow [13,14]. This is useful information to verify map data.…”

Section: Cut-in Collisionmentioning

confidence: 99%

"Present research activities and future requirements on automotive radar from a car manufacturer´s point of view"

Dickmann

Klappstein

Hahn

et al. 2015

2015 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM)

Self Cite

View full text Add to dashboard Cite

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“…The main sensing devices that have been proposed for lane detection and tracking include radars [13–15], laser range finders [16,17], active infrared sensors that detect lane crossings by measuring the IR LED light reflected by the road markings [18,19], and standard visible spectrum perspective cameras [10,12]. Although radar and laser based sensors are very good at detecting the road boundaries (curbs, berms) as well as other vehicles, regardless of the illumination conditions, their major drawbacks are their elevated cost compared with the alternative sensing modalities and the fact that lane markings only have color information and no 3D structure that could be obtained by the volume measuring sensors.…”

Section: Existing Approachesmentioning

confidence: 99%

Robust Lane Sensing and Departure Warning under Shadows and Occlusions

Tapia-Espinoza

Torres-Torriti

2013

Sensors

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A prerequisite for any system that enhances drivers' awareness of road conditions and threatening situations is the correct sensing of the road geometry and the vehicle's relative pose with respect to the lane despite shadows and occlusions. In this paper we propose an approach for lane segmentation and tracking that is robust to varying shadows and occlusions. The approach involves color-based clustering, the use of MSAC for outlier removal and curvature estimation, and also the tracking of lane boundaries. Lane boundaries are modeled as planar curves residing in 3D-space using an inverse perspective mapping, instead of the traditional tracking of lanes in the image space, i.e., the segmented lane boundary points are 3D points in a coordinate frame fixed to the vehicle that have a depth component and belong to a plane tangent to the vehicle's wheels, rather than 2D points in the image space without depth information. The measurement noise and disturbances due to vehicle vibrations are reduced using an extended Kalman filter that involves a 6-DOF motion model for the vehicle, as well as measurements about the road's banking and slope angles. Additional contributions of the paper include: (i) the comparison of textural features obtained from a bank of Gabor filters and from a GMRF model; and (ii) the experimental validation of the quadratic and cubic approximations to the clothoid model for the lane boundaries. The results show that the proposed approach performs better than the traditional gradient-based approach under different levels of difficulty caused by shadows and occlusions.

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Radar for Autonomous Driving – Paradigm Shift from Mere Detection to Semantic Environment Understanding

et al. 2019

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Evaluation of different quality functions for road course estimation using imaging radar

Cited by 10 publications

References 7 publications

"Present research activities and future requirements on automotive radar from a car manufacturer´s point of view"

"Present research activities and future requirements on automotive radar from a car manufacturer´s point of view"

Robust Lane Sensing and Departure Warning under Shadows and Occlusions

Radar for Autonomous Driving – Paradigm Shift from Mere Detection to Semantic Environment Understanding

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