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This study aims to develop an autonomous vehicle to have the efficient lane change and path planning using GIS information. Segmentalizing the global path data, established in advance and adding information on roads to those segments would establish GIS data. GIS data should include information on road lanes, speed limits, traffic lights, crosswalks, speed bumps and traffic signs. Using GIS data,...
In this research, Auto-parking path planning system for an autonomous vehicle is developed. Reeds-Shepp curve algorithm make shortest path with the vehicle minimum turning radius and straight line from start point to goal point. In Reeds-Shepp curve algorithm total 48 path formulas are existed but these formulas are limited in actual parking lot. Because Reeds-Shepp curve path are valid in open environment,...
This paper is research about unmanned ground vehicle for path planning. based on global path to optimal path generating. The proposed algorithm was used to D* Lite and lateral avoidance algorithm. This algorithm used to global map and search obstacle. Presented safety avoidance path planning thought Velocity of autonomous vehicle. safety obstacle avoidance according to velocity. Current Autonomous...
In this research is began with an attempt to operate the Unmanned Ground Vehicle(UGV) in unknown environments. We present a heuristic-based path planning algorithm for generating smooth and optimal paths. UGV operating in outdoor environments must deal with new objects during traversal. Path planning in occupied area must be incremental to accommodate new information and must use efficient representations...
The existing path planning algoritms focus on creating only shortest path from the start position to the goal. As result of process, the path made by this algoritms doesn't consider moving characteristics of object. And it is hard to apply to unmanned ground vehicle(we abbreviate the word by ‘UGV’). We must consider vehicle's kinematic factors for path planning for car-like vehicle. So we suggest...
This paper describes urban driving system of unmanned ground vehicle. Urban driving system of UGV is important system for driving safety and stability. This system is consists of 2 component. One is laser system component and the other is vision system components. In this paper we introduce UGV system configuration and explain urban driving system using laser scanner and camera.
This paper introduces an optimal algorithm through analyzing and studying various algorithms used in DARPA Urban Challenge 2007 and making a numerical statement about each algorithm. The top eleven teams that passed the NQE (national qualifying event) used Dijkstra, A*, RRTs, and D*. Therefore, this research will focus on those algorithms and study a method to apply an optimal algorithm.
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