This paper presents an algorithm for estimating the shape of the road ahead of a host vehicle equipped with the following onboard sensors: a camera, a radar, and vehicle internal sensors. The aim is to accurately describe the road geometry up to 200 m ahead in highway scenarios. This purpose is accomplished by deriving a precise clothoid-based road model for which we design a Bayesian fusion framework. Using this framework, the road geometry is estimated using sensor observations on the shape of the lane markings, the heading of leading vehicles, and the position of roadside radar reflectors. The evaluation on sensor data shows that the proposed algorithm is capable of capturing the shape of the road well, even in challenging mountainous highways.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Long-Range Road Geometry Estimation Using Moving Vehicles and Roadside Observations




    Publication date :

    2016




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English



    Classification :

    BKL:    55.84 Straßenverkehr / 55.24 / 55.84 / 55.24 Fahrzeugführung, Fahrtechnik



    Long-Range Road Geometry Estimation Using Moving Vehicles and Roadside Observations

    Hammarstrand, Lars / Fatemi, Maryam / Garcia-Fernandez, Angel F. et al. | IEEE | 2016



    Road geometry estimation using a precise clothoid road model and observations of moving vehicles

    Fatemi, Maryam / Hammarstrand, Lars / Svensson, Lennart et al. | IEEE | 2014


    Road geometry estimation for vehicles

    LEAH ADAM / FU JUNSHENG / HAMMARSTRAND LARS | European Patent Office | 2025

    Free access

    Vehicle-road cooperation roadside system

    NING CHENHE / YANG LIANBAO / YAN ZHENGXIANG et al. | European Patent Office | 2024

    Free access