Abstract

We present an approach for validation of advanced driver assistance systems, based on randomized algorithms. The new method consists of an iterative randomized simulation using adaptive importance sampling. The randomized algorithm is more efficient than conventional simulation techniques. The importance sampling pdf is estimated by a kernel density estimate, based on the results from the previous iteration. The concept is illustrated with a simple adaptive cruise control problem.

Abstract

In-vehicle systems that assist the driver with his driving task are developed and introduced to the market at increasing rate. Drivers may be supported during congested traffic conditions by a so-called Congestion Assistant consisting of a mix of informing, assisting and controlling functions. This paper describes the impacts of the Congestion Assistant on the driver in terms of driving behaviour and acceptance. Thirty-seven participants took part in a driving simulator study. The observed driving behaviour showed promising improvements in traffic safety when approaching the traffic jam. Moreover, positive effects of the system on traffic efficiency can be expected in the jam. The participants stated to appreciate the Congestion Assistant, although not all functions were equally rated. To increase the performance and acceptance of the total system, some refinements were suggested. Keywords: Congestion Assistant; Driving simulator; Integrated system; Driving behaviour; Acceptance