Uber and Lyft are popular on-demand ways to travel, but does that mean trains and buses are a thing of the past? Travelers prefer different modes of transportation at different times. So how can all of these patterns coexist and do so successfully? New research in INFORMS transportation sciences He created a model and algorithm to reallocate transportation resources based on passenger preferences resulting in savings of millions.
“Based on case study experiences in New York City, our continuously improved transportation schedules result in a system-wide cost reduction of 0.4%-3%. This means millions of dollars saved in rush hour daily, while reducing costs on passengers and transportation at the same time,” Vikrant said. He won from Dartmouth College.
“Improving transit planning in light of riding competition and traffic congestion,” Vaze wrote along with Keji Wei also of Dartmouth, as well as Alexandre Jacquillat of MIT.
This study attempts to understand what would happen if a public transportation agency were to explicitly consider passenger selection factors and what that would do for transportation when designing their schedules.
Travelers choose transportation based on travel comfort, prices, travel times and traffic congestion. The authors found that the opposite is also true – their choice in turn alters traffic patterns and travel times.
The authors note that by considering both points, they can better align available transportation options with commuter preferences—by reallocating public transportation resources where they provide the strongest societal benefits.
“In the interest of the overall urban ecosystem, the transport operator must critically assess the types of trips and travel needs that transit is better equipped to serve and at the same time, what are some areas where it might be better to scale down and reduce let on-demand operators take a larger proportion of trips A thoughtful reconfiguration can benefit diverse stakeholders simultaneously,” continued Vaze, a professor at the Thayer School of Engineering at Dartmouth. “What we’ve found is that this results in better schedules for passengers, better for transportation operators, and better for the city as a whole, which is a rare win for both sides.”
Impact of COVID-19 behavioral inertia on reopening strategies to cross New York City
Keiji Wei et al., Improving transit planning under competition and traffic congestion, transportation sciences (2021). DOI: 10.1287 / trsc.2021.1068
Presented by the Institute for Operations Research and Management Sciences
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