Combining model- and template-based vehicle tracking for autonomous convoy driving

Fries, Carsten; Luettel, Thorsten; Wuensche, Hans-Joachim

doi:10.1109/ivs.2013.6629600

Cited by 16 publications

(11 citation statements)

References 14 publications

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“…The behavior of formation convoy in self-driving, cooperating cars provides vehicle a safe, predictable and fast driving condition [3]. The navigation based on the communication can help the vehicle master enough path information to make a better driving route [4].…”

Section: The Analysis Of Self-driving Cooperating Carsmentioning

confidence: 99%

The Assessment of Traffic with Self-driving, Cooperating Cars

Wang¹,

Huang²,

Sha³

2017

Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

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Abstract. Based on the NaSch traffic model, we propose a mixing traffic flow model for a multilane system. In this model, the characteristic of Self-driving, Cooperating Cars are abstracted as rules, to make the traffic model can be applied to the traffic with Self-driving, Cooperating Cars. Through the simulation in the model, we found that the Self-driving, Cooperating Cars have a great influence on the capabilities of expressway, and have a decisive action on waiting time before traffic light.

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Section: The Analysis Of Self-driving Cooperating Carsmentioning

confidence: 99%

The Assessment of Traffic with Self-driving, Cooperating Cars

Wang¹,

Huang²,

Sha³

2017

Proceedings of the 2nd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2017)

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“…1). It is an extension of our tracking system which was successfully demonstrated during daylight conditions [3], [4]. Compared to the previous version, the main improvements are:…”

Section: Introductionmentioning

confidence: 99%

“…Most authors use one sensor [7]- [12]. Some combine (different) sensors to achieve an increased measurement accuracy and robustness against varying weather conditions [3], [4], [13], [14]. Typically used sensors are daylight and infrared cameras, RADARs and LiDARs.…”

Section: Introductionmentioning

confidence: 99%

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Autonomous convoy driving by night: The vehicle tracking system

Fries

Wuensche

2015

2015 IEEE International Conference on Technologies for Practical Robot Applications (TePRA)

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Previous publications of our institute describe a robust vehicle tracking system for daylight conditions. This paper presents an improved vehicle tracking system which is able to detect and track the convoy leader also by twilight and night. The primary sensor equipment consists of a daytime camera, a LiDAR and an inertial navigation system. An expansion with a thermal and a lowlight camera was necessary to be robust against any illumination conditions. The system is capable of estimating the relative 3D position and orientation, the velocity and the steering angle of a convoy leader precisely in real-time. This makes it possible to follow the convoy leader's track. Another novelty is coupling a Kalman filter with a particle filter for higher stability and accuracy in vehicle tracking. The tracking system shows excellent functionality while driving more than 50 km fully autonomously in urban-and unstructured environments at night.978-1-4799-8757-3/15/$31.00 ©2015 IEEE

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“…A tracking system for vehicles in urban and unstructured environments was implemented by [3]. Their approach deploys one monocular visible light camera and makes extensive use of features such as Haar-like, local binary pattern and HOG, utilizing about 30,000 training images to acquire robust classifiers.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of PCA, LDA and Fisherfaces in Appearance-based Object Detection in Thermal Infra-red Images with Incomplete Data

Spulak

Otrebski

Kubinger

2015

Procedia Engineering

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Object detection in outdoor environments is a challenging task. One is not only confronted with the problem of acquiring a sufficient amount of training images, but also the issue of huge variation in the objects appearance due to changing weather and light conditions. When using appearance-based object detection algorithms, such as in this paper, dimensional reduction of input data is an integral component to reduce computational costs and improve reliability. Based on the probabilistic classification method of Gaussian classifiers this paper examines the effect different dimensional reduction approaches have on the classification performance of thermal infra-red object images with respect to incomplete training data. It is shown that in the detection task at hand, which is to find the rear end of a truck in a thermal infra-red image, a reduction approach that combines principal component analysis (PCA) and linear discriminant analysis (LDA) is less sensitive to missing data.

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Combining model- and template-based vehicle tracking for autonomous convoy driving

Cited by 16 publications

References 14 publications

The Assessment of Traffic with Self-driving, Cooperating Cars

The Assessment of Traffic with Self-driving, Cooperating Cars

Autonomous convoy driving by night: The vehicle tracking system

Evaluation of PCA, LDA and Fisherfaces in Appearance-based Object Detection in Thermal Infra-red Images with Incomplete Data

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