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For the purposes of on-line control, e.g., in an automatic driving system, or of closed-loop directional control simulation, an optimal preview artificial neural network (ANN) driver model based on error elimination algorithm(EEA) is built. Then the optimal preview times are discussed in high frequency range in this system. The simulation results of optimal preview ANN driver model and Error Elimination Algorithm driver model are compared under the condition of different vehicle speeds and paths, which shows that the proposed approach is efficient and reliable enough, particularly for driver-vehicle closed-loop system.

In partially automated and conditionally automated vehicles, a part of the work of human drivers is replaced by the system, and the main source of safety risks is no longer system failures, but non-failure risks caused by insufficient system function design. The absence of unreasonable risk due to hazards resulting from functional insufficiencies of the intended functionality or by reasonably foreseeable misuse by persons, is referred to as the Safety Of The Intended Functionality. Drivers have the responsibility to supervise the automated driving system. When they don't agree with the operation behavior of the system, they will interfere with the instructions. However, this may lead to potential risks.