Advanced Driver Assistance Systems (ADAS) has gained an enormous interest in the past decade with growing complexity in systems software and hardware. One of the most challenging ADAS features to develop is lane change as it requires full awareness of the objects surrounding the Ego vehicle as well as performing safe and convenient maneuvers. This paper discusses a camera-based lane change approach that is designed to improve the driver’s safety and comfort with the help of LiDAR object detection. The forward-facing camera is capable of detecting the Ego and adjacent lane lines as well as the moving objects in the camera’s field of view. A Graphical User Interface (GUI) was also developed for the driver to interact with the lane change feature by visualizing the sensor data and optionally request the vehicle to change lanes when the system suggests that it is safe to do so. Path planning and following algorithms were developed to plan the path between the center of the Ego lane and the center of the right/left adjacent lanes. The developed algorithms were implemented on FEV’s Smart Vehicle Demonstrator and tested on highway roads. The test results show that the vehicle was able to successfully achieve the lane change by following the planned path and adjusting its speed based on the surrounding objects and curvature of the road.


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    Title :

    Interactive Lane Change with Adaptive Vehicle Speed


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE WCX Digital Summit ; 2021



    Publication date :

    2021-04-06




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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