Collective benefits in traffic during mega events via the use of information technologies
Yanyan Xu, Marta C. Gonzalez

TL;DR
This paper leverages big data and route strategies during mega events like the Olympics to optimize traffic flow and reduce congestion through collective information-driven decisions.
Contribution
It integrates diverse data sources to predict traffic impacts and proposes targeted route and mode changes to improve urban traffic during large events.
Findings
Route alternatives can significantly reduce collective travel time.
Switching a small proportion of drivers to public transit greatly decreases congestion.
Information technologies have positive value in managing event-related traffic.
Abstract
Information technologies today can inform each of us about the best alternatives for shortest paths from origins to destinations, but they do not contain incentives or alternatives that manage the information efficiently to get collective benefits. To obtain such benefits, we need to have not only good estimates of how the traffic is formed but also to have target strategies to reduce enough vehicles from the best possible roads in a feasible way. The opportunity is that during large events the traffic inconveniences in large cities are unusually high, yet temporary, and the entire population may be more willing to adopt collective recommendations for social good. In this paper, we integrate for the first time big data resources to quantify the impact of events and propose target strategies for collective good at urban scale. In the context of the Olympic Games in Rio de Janeiro, we…
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Taxonomy
TopicsHuman Mobility and Location-Based Analysis · Transportation Planning and Optimization · Urban Transport and Accessibility
