The present research aims to understand the safety over the midblock road sections and proposes a safety framework using the conventional Time to Collision (TTC) measure. In the present work, the safety framework underlines a supporting structure connecting the actions of the surrounding vehicles and assesses the collisions changes for a given subject vehicle. The Framework principally checks the likelihood of lateral overlap and the time gap between the subject vehicle and its surrounding vehicles. Later, for the trajectory data development, an automated trajectory data development tool is built with the help of image processing for generating the trajectory data from the study sections. In supporting the developed safety framework, the lateral movement of the vehicles is modeled precisely with the help of deep learning. Further, the conceptualized safety framework is tested with the developed trajectory data sets over the study sections. From the results, it is observed that, in mixed traffic, the collision points are over the entire geometry of the study section. In the case of homogeneous traffic, the collision instincts are clustered toward the median lanes. With the advancement of technology, trajectory data development can be a real-time exercise, and the safety framework can be implemented. By applying the study methodology, the critical spots over the road network can be flagged for better treatment and improve safety over the sections.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Modeling vehicle collision instincts over road midblock using deep learning


    Contributors:

    Published in:

    Publication date :

    2023-03-04


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Homing instincts

    Online Contents | 1997


    Modeling of Pedestrian Midblock Crossing Speed with Respect to Vehicle Gap Acceptance

    Jakym, Joseph / Kodsi, Sam / Attalla, Shady | SAE Technical Papers | 2013


    Midblock Pedestrian Signal Safety Effectiveness

    Fitzpatrick, Kay / Geedipally, Srinivas / Kutela, Boniphace et al. | Transportation Research Record | 2023


    Pedestrian Crosswalks at Midblock Locations

    Lu, George (Xiao-Zhao) / Noyce, David A. | Transportation Research Record | 2009