Towards an Evaluation Methodology for the Environment Perception of Automotive Sensor Setups

To read the file of this research, you can request a copy directly from the authors.


With increasing degree of automation, vehicles require more and more perception sensors to observe their surrounding environment. Car manufacturers are facing the challenge of defining a suitable sensor setup that covers all requirements. Besides the sensors’ performance and field of view coverage, other factors like setup costs, vehicle integration and design aspects need to be taken into account. Additionally, a redundant sensor arrangement and the sensors’ sensitivity to environmental influences are of crucial importance for safety. It is not feasible to explore every possible sensor combination in test drives. This paper presents a new simulation-based evaluation methodology, which allows the configuration of arbitrary sensor setups and enables virtual test drives within specific scenarios to evaluate the environmental perception in early development phases with metrics and key performance indicators. This evaluation suite is an important tool for researchers and developers to analyze setup correlations and to define optimal setup solutions.

No file available

Request Full-text Paper PDF

To read the file of this research,
you can request a copy directly from the authors.

... It is not feasible to execute time-consuming and costly test drives to assess the overall performance of many different setup variations in this early concept phase to determine the best setup solution. Therefore, we established a suitable simulation framework and evaluation tool, which assists the procedure of evolving an optimal sensor setup for vehicle concepts [3]. 6 illustrates the simulation workflow of our evaluation tool as part (B) of the overall development process of perception systems (A)-(E), which is described in the following. ...
Full-text available
Conference Paper
Autonomous driving has the potential to disruptively change the automotive industry as we know it today. For this, fail-operational behavior is essential in the sense, plan, and act stages of the automation chain in order to handle safety-critical situations by its own, which currently is not reached with state-of-the-art approaches.The European ECSEL research project PRYSTINE realizes Fail-operational Urban Surround perceptION (FUSION) based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. This paper showcases some of the key results (e.g., novel Radar sensors, innovative embedded control and E/E architectures, pioneering sensor fusion approaches, AI controlled vehicle demonstrators) achieved until year 2.
Conference Paper
Automotive sensor systems play an essential role for highly and fully automated driving by enabling environmental perception. Besides improving the sensors’ performance, the data quality and information processing, the arrangement of the vehicular surround sensors is crucial. The conceptual design of robust and reliable sensor systems is a complex task since they comprise a high number of different sensors, each with diverse, adjustable parameters. At this early vehicle concept phase, it is not possible to examine the performance of all system variations in field tests. Thus, we established a simulation-based evaluation methodology to investigate the interaction of multiple sensors as a system and the effects of particular sensor arrangements on object detection and vehicle’s surround-view coverage. This paper highlights the considerations while designing sensor systems and analyzes the impact of different sensor positions, especially by systematically altering the mounting height.
ResearchGate has not been able to resolve any references for this publication.