We present a simulation-based approach to assess the safety impacts of vehicles equipped with Automated Driving Systems (ADS) in mixed traffic with Human-driven Vehicles (HV). Specifically, we compare two generic longitudinal strategies of ADS to handle a cut-in: Reactive ADS acting only when the cut-in vehicle crosses the target lane boundary, and Predictive ADS acting at the onset of the cut-in manoeuvre. We identify their distinctive effects on the traffic safety under cut-in maneuvers of adjacent human-driven vehicles at highway merges. We employ a microscopic traffic flow simulator that describes the lane changing process with high detail, accounting for the vehicle interaction and consequent trajectory updates. These high-resolution trajectories are post-processed to estimate a set of relevant surrogate measures of safety. By analyzing these measures, we find that the predictive ADS significantly outperforms the reactive ADS in aspects such as temporal proximity to crash, expected crash severity and the driving risk (combining the two aspects), and the number of aborted lane changes by HV. The negative safety impact of reactive ADS becomes prominent at penetration rate >10%. The major difference between the two ADS approaches appears in the dynamics of risk during the lane changing. When a vehicle cuts in ahead of Reactive ADS, the risk peaks approximately halfway through the maneuver; whereas with Predictive ADS the risk remains marginal throughout. This work demonstrates the potential of simulation-based safety assessment to differentiate the safety impacts of automation functionalities at an early stage of product development.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Comparative Safety Assessment of Automated Driving Strategies at Highway Merges in Mixed Traffic


    Contributors:


    Publication date :

    2022-04-01


    Size :

    2225200 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Persuasive strategies to increase traffic safety in automated driving

    Hock, Philipp / Universität Ulm | TIBKAT | 2021

    Free access

    Evaluation of automated driving safety in urban mixed traffic environments

    Sangjae Lee / Young Jo / Aram Jung et al. | DOAJ | 2024

    Free access

    SOCIALLY-COMPLIANT AUTOMATED DRIVING IN MIXED TRAFFIC

    DONG YONGQI / ZHANG LI / FARAH HANEEN et al. | European Patent Office | 2025

    Free access

    Rule based control for merges: Assessment and case study

    Subraveti, Hari Hara Sharan Nagalur / Knoop, Victor L. / van Arem, Bart | IEEE | 2018


    Trajectory Prediction for Safety Critical Maneuvers in Automated Highway Driving

    Wissing, Christian / Nattermann, Till / Glander, Karl-Heinz et al. | IEEE | 2018