Autonomous Cruise Path Planning Method for Autonomous Driverless Vehicles
The temporal error of the local positioning node information and the anchor node information results in that the information on the same node coordinate position cannot be unified,which causes serious vehicle path planning trajectory deviation.Therefore,an autonomous cruise path planning method for driverless tractor was proposed.Through the Monte Carlo node positioning of the driverless tractor and the positioning information collected by multi-area distributed sensors,the coordi-nate parameters were quantified.Then Monte Carlo localization algorithm was introduced into parameter optimization,and the location distance between the node and the target anchor node in the effective localization area was obtained by measuring the distance of the location points in the path planning.After the optimization model of route cruise planning parameters was constructed and the node position data was solved,the optimal autonomous cruise path of the driverless tractor was outputted.The simulation results show that the path planning is accurate,the index values meet the test standards,and the path plan-ning node coverage is high.
Monte Carlo positioning algorithmunmanned drivingtractorautonomous cruisepath planning
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