Management of Potential Conflicts between Pedestrians and Autonomous Vehicles
Increase in the population caused by rapid Urbanization, especially with the introduction of autonomous vehicles, enhances the problems regarding the pedestrian safety. One of the major challenges for the operation of the AVs in an urban environment is non-motorized road users. The successful operation of AVs can only be carried out by the thorough understanding of pedestrian conflicts existing in the areas of interest.
So, the main objective of this research is the identification of the potential conflicts between pedestrian and vehicular traffic at the signalized and non-signalized intersections and to suggest relevant mitigation measures to increase the pedestrian safety. The main method of doing this is the questionnaire surveys as well as with the field measurements at the selected localities. Through these surveys following conflict types will be measured and investigated:
• Conflicts between pedestrian and vehicles;
o when suddenly brakes are applied by the vehicles or
o pedestrian jumps backward/forward to avoid the collision
o disturbance and delay caused by this collision to the surrounding traffic.
• Vehicles Stopping ahead of the Signal Line:
• Pedestrians crossing at the red light
• Pedestrian crossing before/after the pedestrians crossing
o Illegal pedestrian movements
o Pedestrians crossing between the stopped vehicles
o Pedestrians doing J walking across the intersection
The results of this survey will highlight the conflicted areas and pedestrian trajectories over the selected localities for the improvement to be carried out in terms of road geometry, information management, enforcement etc. This will help to determine management strategies and actions for the efficient operation of AVs in the same areas by making suitable recommendations to the autonomous vehicle industries and the government departments/ agencies to carry out the corresponding improvements to pedestrian infrastructure. So, these industries should be focused on the inclusion of these factors while programming their AVs.