  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 first predict the expected
increase in traffic. To that end, we integrate data from: mobile phones,
Airbnb, Waze, and transit information, with game schedules and information of
venues. Next, we evaluate the impact of the Olympic Games to the travel of
commuters, and propose different route choice scenarios during the peak hours.
Moreover, we gather information on the trips that contribute the most to the
global congestion and that could be redirected from vehicles to transit.
Interestingly, we show that (i) following new route alternatives during the
event with individual shortest path can save more collective travel time than
keeping the routine routes, uncovering the positive value of information
technologies during events; (ii) with only a small proportion of people
selected from specific areas switching from driving to public transport, the
collective travel time can be reduced to a great extent. Results are presented
on-line for the evaluation of the public and policy makers.
