Innovative Practices for Transit Planning at Small to Mid-Sized Agencies

2021 ◽  
Author(s):  
Kelly Blume ◽  
James Cardenas ◽  
Ipek Sener ◽  
Will Rodman ◽  
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Keyword(s):  
Author(s):  
Keji Wei ◽  
Vikrant Vaze ◽  
Alexandre Jacquillat

With the soaring popularity of ride-hailing, the interdependence between transit ridership, ride-hailing ridership, and urban congestion motivates the following question: can public transit and ride-hailing coexist and thrive in a way that enhances the urban transportation ecosystem as a whole? To answer this question, we develop a mathematical and computational framework that optimizes transit schedules while explicitly accounting for their impacts on road congestion and passengers’ mode choice between transit and ride-hailing. The problem is formulated as a mixed integer nonlinear program and solved using a bilevel decomposition algorithm. Based on computational case study experiments in New York City, our optimized transit schedules consistently lead to 0.4%–3% system-wide cost reduction. This amounts to rush-hour savings of millions of dollars per day while simultaneously reducing the costs to passengers and transportation service providers. These benefits are driven by a better alignment of available transportation options with passengers’ preferences—by redistributing public transit resources to where they provide the strongest societal benefits. These results are robust to underlying assumptions about passenger demand, transit level of service, the dynamics of ride-hailing operations, and transit fare structures. Ultimately, by explicitly accounting for ride-hailing competition, passenger preferences, and traffic congestion, transit agencies can develop schedules that lower costs for passengers, operators, and the system as a whole: a rare win–win–win outcome.


Author(s):  
Andrew Guthrie ◽  
Yingling Fan ◽  
Kirti Vardhan Das

Accessibility analysis can have important implications for understanding social equity in transit planning. The emergence and the increasingly broad acceptance of the general transit feed specification (GTFS) format for transit route, stop, and schedule data have revolutionized transit accessibility research by providing researchers with a convenient, publicly available source of data interoperable with common geographic information system (GIS) software. Existing approaches to GTFS-based transit analysis, however, focus on currently operating transit systems. With major transit expansions across the nation and around the world increasing in number and ambition, understanding the accessibility impacts of proposed projects in their early planning stages is crucial to achieving the greatest possible social benefit from these massive public investments. This paper describes the development of a hypothetical transit network based on current GTFS data and proposed 2040 transit improvements for the Twin Cities region of Minneapolis–Saint Paul, Minnesota, as well as its use as a sketch planning tool in exploring the proposed system’s impacts on access to job vacancies from historically disadvantaged areas. This research demonstrates the importance of accessibility analysis in planning a transit system that increases opportunity for marginalized workers and concludes by calling for broader, easier access to accessibility analysis for practitioners and community groups to refine the early stages of the transit planning process and democratize an increasingly crucial transit planning tool.


Transportation planning is an area of public policy that is increasingly recognized for having a significant impact on human health and well-being. Passengers all across the world are choosing bus transit as one of the most cost-effective ways of transportation. The number of passengers who use this mode of transportation is steadily increasing. According to statistics, the bus was India's most popular mode of transportation in 2014. A bus was viewed as a mode of transportation by 66 percent of families in rural areas and 62 percent of households in urban areas. With increased demand, there is a concern about efficiently organizing this service. Because a lack of planning can generate major problems in the real world, such as traffic jams and high operating expenses, it is a source of concern for corporate and government entities who provide this service. In this paper, a review on various bus transit planning approaches and stages and methodologies used in each stage of the customized bus planning strategy is presented. This study will assist bus service organizing entities, whether private or public, in efficiently organizing bus service


2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yindong Shen ◽  
Wenliang Xie ◽  
Jingpeng Li

The timetabling problem (TTP) and vehicle scheduling problem (VSP) are two indispensable problems in public transit planning process. They used to be solved in sequence; hence, optimality of resulting solutions is compromised. To get better results, some integrated approaches emerge to solve the TTP and VSP as an integrated problem. In the existing integrated approaches, the passenger comfort on bus and the uncertainty in the real world are rarely considered. To provide better service for passengers and enhance the robustness of the schedule to be compiled, we study the integrated optimization of TTP and VSP with uncertainty. In this paper, a novel multiobjective optimization approach with the objectives of minimizing the passenger travel cost, the vehicle scheduling cost, and the incompatible trip-link cost is proposed. Meanwhile, a multiobjective hybrid algorithm, which is a combination of the self-adjust genetic algorithm (SGA), large neighborhood search (LNS) algorithm, and Pareto separation operator (PSO), is applied to solve the integrated optimization problem. The experimental results show that the approach outperforms existing approaches in terms of service level and robustness.


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