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Towards an Evaluation Methodology for the Environment Perception of Automotive Sensor Setups
Abstract
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.
... Although many companies are introducing AVs with numerous sensors, not only do the sensor setups differ significantly but there is also no information on the process behind the design choices for their sensor setup [4]. The contributions [5], [6], [7] address the problem of sensor setup definition and introduce an evaluation framework for sensor setup evaluation. They use simulation tools to generate ground truth data and object detections using probabilistic sensor models. ...
... The constraints (7), (8) ensure that the coverage and redundancy in all areas a i is greater than the specified requirements. The constraints ensure that only sensors from the predefined set are used (9) and that the placement of each sensor is in proximity to the vehicle body (6). It is also possible to incorporate constraints originating from mechanical mounting, integration, or design considerations. ...
... 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. ...
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.
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.
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