In this contribution, we introduce an algorithm that allows the estimation of a transformation between two sensor systems. The primary system consists of non-imaging sensors like for example lidar and radar or even a fused combination of these. A camera always represents the secondary system. The algorithm aims at automating the process of calibration entirely during driving. This way, much flexibility and robustness are guaranteed. Changing the placement of the camera remains possible without the need to do a cumbersome manual calibration.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Online Calibration of a Camera System in Road Traffic Scenarios for the Validation of Automated Driving Functionalities


    Contributors:

    Conference:

    AmE 2018 – Automotive meets Electronics - 9. GMM-Fachtagung ; 2018 ; Dortmund, Deutschland



    Publication date :

    2018-01-01


    Size :

    6 pages



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Semantic Classification of Pedestrian Traffic Scenarios for the Validation of Automated Driving

    Hartjen, Lukas / Schuldt, Fabian / Friedrich, Bernhard | IEEE | 2019



    Semantic classification of urban traffic scenarios for the validation of automated driving systems

    Hartjen, Lukas / Technische Universität Braunschweig | TIBKAT | 2023

    Free access

    Cooperative Automated Driving for Various Traffic Scenarios: Experimental Validation in the GCDC 2016

    Dolk, Victor / Ouden, Jos den / Steeghs, Sander et al. | IEEE | 2018


    Automated Tool to Test Traffic Signal Controller Functionalities

    National Research Council (U.S.) | British Library Conference Proceedings | 2005