Evolving the Controller of Automated Steering of a Car in Slippery Road Conditions

Natalia Alekseeva,Ivan Tanev,Katsunori Shimohara

doi:10.3390/a11070108

Abstract

The most important characteristics of autonomous vehicles are their safety and their ability to adapt to various traffic situations and road conditions. In our research, we focused on the development of controllers for automated steering of a realistically simulated car in slippery road conditions. We comparatively investigated three implementations of such controllers: a proportional-derivative (PD) controller built in accordance with the canonical servo-control model of steering, a PID controller as an extension of the servo-control, and a controller designed heuristically via the most versatile evolutionary computing paradigm: genetic programming (GP). The experimental results suggest that the controller evolved via GP offers the best quality of control of the car in all of the tested slippery (rainy, snowy, and icy) road conditions.

Highlights

Since the 1930s, the authors of science fiction books have envisioned the advent of self-driving cars, and constructing such cars has been a challenge for the Artificial Intelligence (AI) community since the1960s [1]
We believe that the automation should abstain from unconditionally ceding the control of the car to the human driver, especially in heavy traffic situations or in challenging road conditions due to the major drawback of this transfer: the reduced cognitive load of the human driver might result in a rough transition of control between the automation and the human [5]
We considered the first and third subtasks to be beyond the scope of our current work; instead, we focused on the second one—in challenging, slippery road conditions—which could be solved by an appropriate steering of the car

Summary

Introduction

Since the 1930s, the authors of science fiction books have envisioned the advent of self-driving cars, and constructing such cars has been a challenge for the Artificial Intelligence (AI) community since the1960s [1]. The currently available—up to level 3 (of the six levels, 0–5) of autonomous driving, as defined in 2014 by the Society of Automotive Engineers—industrial applications of semi-autonomous vehicles require that the drivers keep their hands on the steering wheel all the time during the operation of the “auto-pilot” [3]. In a case of an unforeseen traffic situation or road condition, the control might have to be transferred to the presumably more dependable human driver [4]. We believe that the automation should abstain from unconditionally ceding the control of the car to the human driver, especially in heavy traffic situations or in challenging (such as, for example, slippery) road conditions due to the major drawback of this transfer: the reduced cognitive load of the (passive) human driver might result in a rough transition of control between the automation and the human [5]

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