Autonomous Vehicles Research Papers

Autonomous Vehicles Research Papers-7
In the second step, the authors use a learning approach based on radial basis function kernel FSVM to maximize the safety margin for driving, and the fuzzy membership is designed based on GRNN which can help to resolve the problem that the traditional path planning method is easily influenced by noises or outliers.In the third step, the Bezier interpolation algorithm is used to smooth the path.

In the second step, the authors use a learning approach based on radial basis function kernel FSVM to maximize the safety margin for driving, and the fuzzy membership is designed based on GRNN which can help to resolve the problem that the traditional path planning method is easily influenced by noises or outliers.In the third step, the Bezier interpolation algorithm is used to smooth the path.

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For the past hundred years, innovation within the automotive sector has created safer, cleaner, and more affordable vehicles, but progress has been incremental.

The industry now appears close to substantial change, engendered by autonomous, or "self-driving," vehicle technologies.

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.

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 .

Navigating in off-road environments is a huge challenge for autonomous vehicles, due to the safety requirement, the effects of noises and non-holonomic constraints of vehicle.

This paper aims to describe a path planning method based on fuzzy support vector machine (FSVM) and general regression neural network (GRNN) that is able to provide a solution path for the autonomous vehicle navigating in the off-road environments.

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