Autonomous driving on vehicle test tracks: overview, implementation and vehicle diagnosis

Abstract

This article describes the implementation of the project ,,Autonomous Driving" which was introduced earlier [7]. Furthermore, it shows the concept of the vehicle diagnosis in detail. The vehicle diagnosis monitors a test car on a proving ground and substitutes the surveillance of a human test driver. Therefore, the human diagnostics capabilities have to be replaced by measuring equipment in order to automate the detection of malfunctions. The components of the vehicle diagnosis system and its operating principle will be shown here. Two test vehicles were equipped with sensors, computers and actuators (driving robots). The vehicles can be driven by a robot while the sensor system observes the entire surroundings in order to be able to avoid obstacles. Furthermore, the vehicle control can be overruled by an electronic copilot in case of an emergency.

Automatic Generation of Safety-Critical Test Scenarios for Collision Avoidance of Road Vehicles

“…It is thus of great importance to automatically generate interesting test cases. These test cases can either be applied to the above-mentioned simulation environments, on proving grounds [15], or in a mixed reality, where some vehicles are real and others are added virtually [16].…”

An Improved Technique for Vision Based Path Tracking Robot

“…In recent years, concept of visual path following has been applied on autonomous robot navigation using sophisticated techniques like Kalman filters, Voronoi diagrams for feature extraction from the image and accurate determination of the kinematics of robot [1][2] [3]. Some of the advanced approaches are EYEBOT robots at University of Western Australia and ALVINN project at Carnegie Mellon University which make use of advanced image processing in coordination with neural networks [4] [5].…”