Search Results

This paper presents an autonomous cruise control for battery electric vehicles. The presented approach is based on the usage of predictive route data which is extracted out of a digital map and a wide range radar system in order to capture vehicles in front. By using the predictive route data and the information of the radar system, the autonomous cruise control can control the vehicle's speed over a wide range of driving situations without any driver interaction. The main aim of the presented autonomous cruise control is to optimize the battery electric vehicle's energy consumption. The main idea is to use predictive route data in order to calculate a consumption optimal vehicle speed trajectory by means of online optimization. The benefits of the autonomous cruise control are shown by means of real test drives and measured data evaluation.

In recent years the automotive companies are developing their self-driving technology very rapidly. Most of them want to launch their self-driving vehicles with SAE level 4 at the beginning of 2020. The main goal of the development of self-driving cars is to reduce accidents caused by driver errors. But there are some technological challenges to solve such as increasing of the safety and availability in order to get the acceptance from the customers. The purpose of this research is to investigate the possible fail-operational safety architectures for both conventional systems as powertrain and the entire ADAS processing chain.