Various Data, Including Mobile Phones, Lodging Services, Navigation App, and Transit Info Were Used to Estimated Travel Time and Speed Benefits by Route and Traffic Mode Changes for the Rio Olympics.
During major events, traffic disruptions can intensify significantly. Information technologies could be effective in such cases to urge the crowds as they may be more willing to adopt collective recommendations and use a certain travel mode that can potentially benefit the traffic and reduce travel times collectively. This study evaluated a demand management that involved informed mode change strategy for travelers during peak hours that may help reduce congestion, in the context of the Summer Olympic Games in Rio de Janeiro in 2016. This study forecasted the traffic surge due to the Olympic games, integrated data from various sources such as mobile phones, lodging services, navigation app, and transit info with game schedules and expected venue attendance. Based on the data, route choices during peak hours were evaluated and the most congestion-contributing trips that could be transitioned from vehicles to public transit were identified.
The study first estimated the travel demand of the local population and their fraction in private vehicles. The data resources used for this task were: mobile phone data, private navigation application data, camera data, online short-term house rental data, hotel data, the Olympic game schedules and information of venues. Then tourists’ travel mode splits were estimated for four mobility modes: 1) walking and metro/ bus rapid transit (BRT), 2) bike and metro/BRT, 3) taxi, and 4) bus. Then traffic demand assignment was performed to estimate the travel time and volume on each road segment. This study tested an informed mode change strategy that targeted a selected fraction of travelers to change their modes from driving to the metro and BRT. The selection of the travelers for mode change was based on the estimated travel time (marginal cost) savings of others after removing one vehicle from the road system. (i.e., larger marginal cost indicate more collective travel time would be saved). The study only considered the trips in which both origins and destinations (OD) were located close to the metro or BRT stations, which meant travelers could switch to public transport rather than driving. As a benchmark, the study kept the same number of total reduced trips but uniformly distributed them to all OD pairs near Metro and BRT stations to be able to evaluate the effectiveness of the informed mode change strategy.
- Compared to the uniform benchmark, the informed mode change strategy based on marginal costs was five times more effective. For example, reducing 60 percent of the flow from the selected 5,000 OD pairs at the range of two kilometers (1.24 miles) from the transit stations represented 1.14 percent of the total vehicle flows. In that case, the percentage reduction in the collective travel time was more than 10 percent with informed mode change strategy, and only two percent with the uniform benchmark case.
- Reducing 60 percent of the flow from the selected 6,000 OD pairs at the range of two kilometers from the transit stations represented limiting 1.4 percent of the total car demand. In that case, the percentage reduction in the collective travel time was 10.6 percent with the informed mode change strategy, with an added benefit of 7.7 percent increase in speeds (from 37.08 to 39.94 km per hour).