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The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. The simulations are designed to verify the parameters of the path planning algorithm.The method is implemented on autonomous vehicle and verified against many outdoor scenes. https://doi.org/10.1108/IR-11-2016-0301 Download as . These positive externalities may justify some form of subsidy.The report also explores policy issues, communications, regulation and standards, and liability issues raised by the technology; and concludes with some tentative guidance for policymakers, guided largely by the principle that the technology should be allowed and perhaps encouraged when it is superior to an average human driver.A lawsuit between Uber and Waymo, Google’s self-driving car project, settled in February 2018 illustrates the fierce battle to develop driverless car technology.Many cars already employ semi-autonomous technology, such as parking assistance and lane monitoring.Leveraging techniques from machine learning, computer vision, probabilistic sensor fusion, and optimization, our researchers are actively pursuing improvements in semantic scene understanding, object segmentation and tracking, sensor calibration, localization, vehicle control, and path planning.We frequently publish our results at conferences including RSS, ICRA, IROS, and ISER so that the community at large can benefit from our efforts.GRNN-FSVM can reduce the effects of outliers and maximize the safety margin for driving, the generated path is smooth and safe, while satisfying the constraint of vehicle kinematic. Eerie as it may seem to drive alongside a car with no one behind the wheel, autonomous vehicles are poised to hit the roads in the next few years.