A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles

Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation. Safety-critical tasks that must be executed by a self-driving vehicle include planning of motions through a dynamic environment shared with other vehicles and pedestrians, and their robust executions via feedback control. The objective of this paper is to survey the current state of the art on planning and control algorithms with particular regard to the urban setting. A selection of proposed techniques is reviewed along with a discussion of their effectiveness. The surveyed approaches differ in the vehicle mobility model used, in assumptions on the structure of the environment, and in computational requirements. The side by side comparison presented in this survey helps to gain insight into the strengths and limitations of the reviewed approaches and assists with system level design choices.

I. Introduction

The last three decades have seen steadily increasing research efforts, both in academia and in industry, towards developing driverless vehicle technology. These developments have been fueled by recent advances in sensing and computing technology together with the potential transformative impact on automotive transportation and the perceived societal benefit: In 2014 there were 32 675 traffic related fatalities, 2.3 million injuries, and 6.1 million reported collisions [1]. Of these, an estimated 94% are attributed to driver error with 31% involving legally intoxicated drivers, and 10% from distracted drivers  [2]. Autonomous vehicles have the potential to dramatically reduce the contribution of driver error and negligence as the cause of vehicle collisions. They will also provide a means of personal mobility to people who are unable to drive due to physical or visual disability. Finally, for the 86% of the US work force that commutes by car, on average 25 minutes (one way) each day  [3], autonomous vehicles would facilitate more productive use of the transit time, or simply reduce the measurable ill effects of driving stress [4].