A Virtual Co-Driver for Improved Driving Safety on Country Roads


2022
Author(s):Adelberger D.
Year:2022
Abstract:
Safety is a topic of huge importance in road traffic. A key component in preventing potentially fatal accidents is a correct perception of the vehicle environment, including other traffic participants, which subsequently enables a safe interaction. This applies to human drivers as well as to Advanced Driver Assistance Systems (ADAS) and, also, to fully Autonomous Vehicles (AVs) that may become available in the future. Different environments present different challenges as far as safety is concerned. Therefore, the development of well-tailored safety concepts for specific environments promises a more significant impact than a one-for-all solution. In Austria, country roads contribute at the largest extent to the fatality rate in traffic. This is mostly due to high (relative) velocities, bidirectional traffic and narrow curves which not only restrict the observable range but also the permissible forces acting on a vehicle. In this thesis, a Virtual Co-Driver (VCD) which improves traffic safety on country roads is proposed. It exploits available data of the environment, analyzes the behavior of other traffic participants, and identifies the role of the vehicle in the scenario as well as its options to remain in a global safe state. A global safe state is defined as a state where a collision can be avoided in any case. The system is designed to either communicate the safety of available maneuver options to a driver or to take over control if the intended action of the responsible driver, ADAS, or AV tends to result in an accident. Efficient ways to assure the safety of states and transitions within an environment are developed, and the system is validated on various traffic situations in simulation as well as by application on actual measured drives along a country road. The evaluation of basic maneuver options by the VCD yields sensible outcomes, and the system intervenes accordingly at critical occasions when applied to real-world driving data. Hence, an improvement of driving safety on country roads is clearly given by the VCD developed within this thesis.
 
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