Rapid advancements in driver assistance technology will lead to the integration of fully autonomous vehicles on our roads that will interact with other road users. To address the problem that driverless vehicles make interaction through eye contact impossible, we describe a framework for estimating the crossing intentions of pedestrians in order to reduce the uncertainty that the lack of eye contact between road users creates. The framework was deployed in a real vehicle and tested with three experimental cases that showed a variety of communication messages to pedestrians in a shared space scenario. Results from the performed field tests showed the feasibility of the presented approach.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Autonomous Driving: Framework for Pedestrian Intention Estimation in a Real World Scenario




    Publication date :

    2020-10-19


    Size :

    2278563 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    AUTONOMOUS DRIVING: FRAMEWORK FOR PEDESTRIAN INTENTION ESTIMATION IN A REAL WORLD SCENARIO

    Morales-Alvarez, Walter / Moreno, Francisco Miguel / Sipele, Oscar et al. | British Library Conference Proceedings | 2020


    Autonomous Driving: Framework for Pedestrian Intention Estimationin a Real World Scenario

    Alvarez, Walter Morales / Moreno, Francisco Miguel / Sipele, Oscar et al. | ArXiv | 2020

    Free access

    A Framework for Driving Intention Estimation in Real-World Scenarios

    Huang, He / Zeng, Zheni / Shangguan, Yifan et al. | ASCE | 2020


    A Framework for Driving Intention Estimation in Real-World Scenarios

    Huang, He / Zeng, Zheni / Shangguan, Yifan et al. | TIBKAT | 2020


    Pedestrian Detection with YOLOv5 in Autonomous Driving Scenario

    Jin, Xianjian / Li, Zhiwei / Yang, Hang | IEEE | 2021