Lane keeping, path planning and decision making are the most important features of self-driving cars. Cooperative adaptive cruise control and platooning are notable applications in autonomous cars. It expands the use of street foundation assets through composed control and platooning of individual vehicles with the capability of improving both traffic wellbeing and productivity. In this study, end-to-end lane keeping and path planning are explored. Self-driving cars are presently recognised as the core of industry research because of its multi-faceted quality vehicle benefits which includes advanced security, reduced blocking, minor manufacturing and improved mobility. When transporting people or commodities from one location to another, motion planning methods include locating a track to follow, avoiding roadblocks and designing the optimum route that ensures security, ease and effectiveness. The purpose of this study is to review present approaches and evaluate the different techniques for the motion planning of self-directed on-road driving that consists of locating a lane, finding for the safest manoeuvre and shaping the main possible route. The study demonstrates a critical evaluation of each of these processes in terms of their benefits and drawbacks.


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    Title :

    Motion Planning and Manoeuvring in Self Driving Cars


    Additional title:

    Studies in Systems, Decision and Control




    Publication date :

    2022-02-24


    Size :

    23 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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