Zero-Collision Models for Urban Mobility: A Data-Driven Technological Framework

Authors: Simran Sethi

DOI: https://doi.org/10.5281/zenodo.14945107

Short DOI: https://doi.org/g86n7q

Country: USA

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Abstract: The last few years there has been an effort to eradicate traffic collisions termed for North American cities under “Vision Zero.” It seems that removing infrastructure advancements and policies will always be crucial, but at some point in the future, data driven technology will dominate the urban mobility space. This paper presents a real time analytics driven collision mitigation system with focus on data from connected and autonomous vehicles alongside simulation platforms. We analyze literature that documents these claims, particularly how computation of large datasets, simulation engines, and safety rules for self-driving vehicles can significantly diminish or completely eliminate traffic collisions. Further, we demonstrate a proof of concept case of a city hackathon, stationed “VANquish Collisions,” in Vancouver, Canada, which can facilitate the development of working prototype tools. This paper claims that with the marriage of intelligent infrastructure, data pipelines, and automation in vehicles, cities can truly start to work towards actionably reducing collision incidents to zero.

Keywords: Zero-Collision, Vision Zero, Data Analytics, Autonomous Vehicles, Simulation, Urban Mobility

Paper Id: 232170

Published On: 2023-12-05

Published In: Volume 11, Issue 6, November-December 2023

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