Stable Road Lane Model Based on Clothoids

Gackstatter, Christina; Heinemann, Patrick; Thomas, Sven; Klinker, Gudrun

doi:10.1007/978-3-642-16362-3_14

Cited by 22 publications

(8 citation statements)

References 6 publications

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“…Additionally, curvature detection algorithm that incorporates with lane marker and lane texture is introduced. Moreover, Gackstatter et al 11 presented a lane tracking algorithm also using Kalman filter and proposed an algorithm to recover the clothoid parameters using numerical optimization. Southall and Taylor 12 conducted a feasibility study of the lane tracking algorithm using particle filter, which runs around 10 frames per second.…”

Section: Introductionmentioning

confidence: 99%

Robust lane tracking algorithm for forward target detection of automated driving vehicles

Song

Kim

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part D:

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Detection of a primary forward target is one of the most important factors in a longitudinal control system of automated driving vehicles. If there is no special event such as a lane change, a lane detected by a vision sensor can be deemed as a predicted driving path of the ego vehicle. Based on this, it is possible to determine the state of the primary forward target vehicle accurately using the detected lanes. However, malfunction of vision sensors can induce unrecognized and misrecognized lane detection problems on account of internal/external environment factors. Furthermore, if a detection point is getting farther from the subject vehicle, the detection accuracy is getting lower because of inaccuracy of lane model parameters. To solve these problems, a novel method of lane tracking has been investigated. First, an integrated sensor module that combines a virtual sensor and a vision sensor has been developed. The virtual sensor is combined kinematic and dynamic vehicle model to be used in the full-speed range. Second, a lane estimator to improve lane detection accuracy at a long distance has been developed. The lane width in the public road can be assumed to be constant in the same road type. Based on this assumption, the clothoid parameters can be restored and consequently improve the lane detection accuracy. The performance of the proposed algorithm was verified by actual vehicle tests on public roads with manual driving and on proving ground with an automated driving system. The proposed algorithm has been compared with a conventional method which is based on in-vehicle yaw rate sensor. The test results have shown significant improvement of lane tracking performance over the conventional method.

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Section: Introductionmentioning

confidence: 99%

Robust lane tracking algorithm for forward target detection of automated driving vehicles

Song

Kim

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…The main advantages of the method are ease of implementation and efficiency. Compared with the recent RBC method [19], our method achieves similar error and 11 times shorter computation time so that it can be used to enable online use of existing clothoid-based algorithms, such as path planning [21], or for other time-critical real-time clothoid applications [23], [24].…”

Section: Discussionmentioning

confidence: 86%

“…Computational simplicity of the proposed method enables that all alternative paths are smoothed in real time and that the one which provides the fastest reaching the goal position is chosen as the best one. Further, the proposed algorithm can be used for design of other time critical real-time clothoid applications, e.g., shape completion problem in computer vision [23], where a nonlinear system of equations involving Fresnel Integrals is solved, or tracking of road lanes based on clothoids [10], [24]. Application where algorithm precision is of particular importance include robot soccer, e.g., in simulator leagues [25] where a small initial robot position error may multiply by a huge factor and result in a big error at the end of ball trajectory.…”

mentioning

confidence: 99%

Real-time Approximation of Clothoids With Bounded Error for Path Planning Applications

2014

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We present a method for real-time computation of clothoid coordinates that guarantees bounded approximation error over a wide range of clothoid parameters provided that the clothoid's orientation change and length are bounded. It is shown that coordinates of clothoid with any parameters can be computed from those of a single clothoid (with fixed parameters), using appropriate geometrical transformations. A comprehensive analysis is given on how to determine a required set of clothoids and, based on this, how to sample a clothoid in a lookup table in order to achieve required approximation precision. The algorithm is computationally very efficient and therefore suitable for real-time path planning, as well as for other applications that benefit from fast clothoid computation.

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“…Several researchers [36], [37] assume that the shape of the road as clothoid, which is defined by the initial curvature, the constant curvature change rate, and its total length. Clothoid can be approximated by a third-order polynomial and used to avoid abrupt changes in steering angle when driving from straight to circular roads.…”

Section: A Lane Modelingmentioning

confidence: 99%

Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios

et al. 2020

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As one of the most important tasks in autonomous driving systems, ego-lane detection has been extensively studied and has achieved impressive results in many scenarios. However, ego-lane detection in the missing feature scenarios is still an unsolved problem. To address this problem, previous methods have been devoted to proposing more complicated feature extraction algorithms, but they are very time-consuming and cannot deal with extreme scenarios. Different from others, this paper exploits prior knowledge contained in digital maps, which has a strong capability to enhance the performance of detection algorithms. Specifically, we employ the road shape extracted from OpenStreetMap as lane model, which is highly consistent with the real lane shape and irrelevant to lane features. In this way, only a few lane features are needed to eliminate the position error between the road shape and the real lane, and a search-based optimization algorithm is proposed. Experiments show that the proposed method can be applied to various scenarios and can run in real-time at a frequency of 20 Hz. At the same time, we evaluated the proposed method on the public KITTI Lane dataset where it achieves state-of-the-art performance. Moreover, our code will be open source after publication. INDEX TERMS Ego-lane detection, missing feature, OpenStreetMap, parameter estimation.

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Stable Road Lane Model Based on Clothoids

Cited by 22 publications

References 6 publications

Robust lane tracking algorithm for forward target detection of automated driving vehicles

Robust lane tracking algorithm for forward target detection of automated driving vehicles

Real-time Approximation of Clothoids With Bounded Error for Path Planning Applications

Map-Enhanced Ego-Lane Detection in the Missing Feature Scenarios

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