Lane Change Strategy for Autonomous Vehicle

Recently, people’s demand for smart vehicles continues to improve. As the core of smart driving, driverless vehicle becomes the most concerned technology. Lane change, the most common behavior in driverless situation, greatly affect the road efficiency. Fast and safe lane change operations have very practical significance in reducing traffic accidents. This paper uses driverless vehicle as research object, and the pathing planning and pathing tracking for lane change situation are studied. An efficient path planning method and trajectory tracking controller are designed and simulated. The main content contains the three following aspects: (1) A set of comprehensive lane change strategy is designed for different working conditions. Then path planning for lane change is researched based on mass point model and an efficient path planning method based on polynomial is proposed and optimized. (2) Kinematic model and 3 DOFs dynamic model of driverless vehicle based on magic tire model are established using SIMULINK. Several simulation and test are done to verify the rationality of the model. (3) The trajectory -tracking control system based on PID controller is designed. Then run simulation based on the model established and according to the results, the trajectory -tracking control system can track the lane-changing path accurately and analysis is made. Key word: Driverless vehicle, Lane change, Path planning, Trajectory tracking contro

Subsea cable tracking by an unmanned surface vehicle

Subsea cable localisation is a demanding task that requires a lot of time, effort and expense. In the present paper the authors propose a methodology that is automated and inexpensive, based on magnetic detection from a small unmanned surface vehicle (USV) and the use of a batch particle filter (BPF) algorithm. A dynamic path planning algorithm for the USV is also developed so that adequate samples of the magnetic field readings can be gathered for processing by the BPF. All of these elements work together online as the cable is tracked, which was demonstrated in a simulated mission

Smooth 3D Path Planning by Means of Multiobjective Optimization for Fixed-Wing UAVs

[EN] Demand for 3D planning and guidance algorithms is increasing due, in part, to the increase in unmanned vehicle-based applications. Traditionally, two-dimensional (2D) trajectory planning algorithms address the problem by using the approach of maintaining a constant altitude. Addressing the problem of path planning in a three-dimensional (3D) space implies more complex scenarios where maintaining altitude is not a valid approach. The work presented here implements an architecture for the generation of 3D flight paths for fixed-wing unmanned aerial vehicles (UAVs). The aim is to determine the feasible flight path by minimizing the turning effort, starting from a set of control points in 3D space, including the initial and final point. The trajectory generated takes into account the rotation and elevation constraints of the UAV. From the defined control points and the movement constraints of the UAV, a path is generated that combines the union of the control points by means of a set of rectilinear segments and spherical curves. However, this design methodology means that the problem does not have a single solution; in other words, there are infinite solutions for the generation of the final path. For this reason, a multiobjective optimization problem (MOP) is proposed with the aim of independently maximizing each of the turning radii of the path. Finally, to produce a complete results visualization of the MOP and the final 3D trajectory, the architecture was implemented in a simulation with Matlab/Simulink/flightGear.The authors would like to acknowledge the Spanish Ministerio de Ciencia, Innovacion y Universidades for providing funding through the project RTI2018-096904-B-I00 and the local administration Generalitat Valenciana through projects GV/2017/029 and AICO/2019/055. 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A Real-Time local path planning method based on SVM for UGV

Path planning is one of essentials of unmanned ground vehicle (UGV). For the case of poor lighting and weather, traditional vision based methods can not extract effective route boundaries to generate reasonable path stably in unstructured road. By ta king advantage of distance-sensing technology (e.g. 64-beam LiDAR), th is paper proposes an efficient real-time path planning approach. In this approach, given grid map fro m 64-bea m LiDAR, obstacles on both sides of the road are regarded as two classes fed to Support Vector Machine (SVM) to generate an initial safe path. During driving, a time weight based least square fitting is adopted to refine path fro m mu ltiple safe paths which will be described by quartic polynomial, providing stable driving route. Co mbined with UGV's state, controls points from the refined path are adopted to generate the final path through Bezier curve fitting. Experiments on real UGV under different road scenario are conducted, showing that the proposed method can obtain stable and reasonable path with promising performance