The objective of this paper is to propose a systematic analysis of the sensor coverage of automated vehicles. Due to an unlimited number of possible traffic situations, a selection of scenarios to be tested must be applied in the safety assessment of automated vehicles. This paper describes how phenomenological sensor models can be used to identify system-specific relevant scenarios. In automated driving, the following sensors are predominantly used: camera, ultrasonic, Radar and Lidar. Based on the literature, phenomenological models have been developed for the four sensor types, which take into account phenomena such as environmental influences, sensor properties and the type of object to be detected. These phenomenological models have a significantly higher reliability than simple ideal sensor models and require lower computing costs than realistic physical sensor models, which represents an optimal compromise for systematic investigations of sensor coverage. The simulations showed significant differences between different system configurations and thus support the system-specific selection of relevant scenarios for the safety assessment of automated vehicles.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Systematic Analysis of the Sensor Coverage of Automated Vehicles Using Phenomenological Sensor Models*


    Contributors:


    Publication date :

    2019-06-01


    Size :

    1619302 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    SENSOR COVERAGE ANALYSIS FOR AUTOMATED DRIVING SCENARIOS INVOLVING INTERSECTIONS

    GRAY JEREMY P / SOREMEKUN GRANT A / MAITLEN DANIEL S | European Patent Office | 2021

    Free access

    Sensor coverage analysis for automated driving scenarios involving intersections

    GRAY JEREMY P / SOREMEKUN GRANT A / MAITLEN DANIEL S | European Patent Office | 2023

    Free access


    Phenomenological, Measurement Based LiDAR Sensor Model

    Schmitt, Jakob / Robel, Christopher / Bäker, Bernard | Springer Verlag | 2021


    Sensor fusion for localization of automated vehicles

    Merfels, Christian / Rheinische Friedrich-Wilhelms-Universität Bonn, Institut für Geodäsie und Geoinformation / Rheinische Friedrich-Wilhelms-Universität Bonn | TIBKAT | 2020

    Free access