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In the last century road transport has completely changed our life, nowadays mobility is a social need. Thanks to the recent revolution of science and technology, road vehicles have more automated features or systems. Initially the main motivation was to make driving easier or more comfortable, but world megatrends have oriented the development towards to lower fuel consumption, higher traffic safety and reduced environmental impact. To reach these future objectives it is necessary to increase the level of automation of road vehicles. Automated vehicles will overcome today’s cars in safety, efficiency, comfort, velocity and traffic density.
Driving a road vehicle is a very complex controlling task, substituting the human driver with a computer is a real challenge also from the technical side. In connected and automated vehicles the control algorithm has several steps. An important step is, when the vehicle plans its own trajectory. The inputs of the trajectory planning are the purpose of the passengers and the environment of the vehicle (through the environmental perception system of the vehicle). The trajectory planning process has several parts for instance the geometry of the path-curve or the speed during the way. Furthermore the traffic situation also can determine many other parameters in the planning process.
This paper presents a basic approach for trajectory design. The inputs will be target points on a 2D field which represents a smaller flat area with various roads. The 2D field are going to be a binary matrix, where the roads will be defined by ones, the obstacles will be defined by zeros. The aim is to make an algorithm which can find the shortest and a suitable way for vehicles between the start and the target point. The vehicle speed will be assumed slow enough to ignore the dynamical properties of the vehicle. The research is the first step to realise automated parking features in a self-drive car.
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ISO: International standard road vehicles - functional safety. International Organization for Standardization, Geneva, Switzerland, ISO26262
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Nyerges, Á., Szalay, Z.: A new approach for the testing and validation of connected and automated vehicles. In: Paper Presented at 34th International Colloquium on Advanced Manufacturing and Repairing Technologies in Vehicle Industry, 17–19 May 2017, Visegrád, Hungary (2017)
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Chebly, A., Tagne, G., Talj, R., Charara, A.: Local trajectory planning and tracking for autonomous vehicle navigation using clothoid tentacles method. HAL Id: hal-01139316 (2015)
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MathWorks: Graph and Network Algorithms Toolbox: User’s Guide (R2015b) (2015). www.mathworks.com/help/pdf_doc/. Accessed 10 Dec 2017
MathWorks: Curve Fitting Toolbox: User’s Guide (R2015b) (2015). www.mathworks.com/help/pdf_doc/. Accessed 10 Dec 2017
- Trajectory Planning for Automated Vehicles – A Basic Approach
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