Urban Transit Network Design with Distinct Passenger Groups: Model and Application

The design of public transportation networks usually focuses on maximizing total welfare, under resource and operation constraints and the assumption of average trip characteristics for a typical user. Nevertheless, there exist different passenger groups (such as current and choice travelers), whose needs may vary and should be prioritized in the planning stage. This paper proposes a model for designing a public transportation network, which considers the needs of different passenger groups. A mathematical programming model is formulated for that purpose and solved using a hybridized Genetic Algorithm based procedure. An application of the model for Mandl’s benchmark network is presented and results show that prioritizing captive users may be achieved with minimum impact to the service quality of the public transportation network. (Image: 7-line Result Network)

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Effects of Bus Stop Spacing in Public Transportation Performance: An Analysis of Parallel Corridors in Chicago

Bus stop spacing is a crucial element in providing a balance between efficiency and coverage in a public transportation network. Having large distances between subsequent stops ensures shorter travel times and higher reliability, mainly because the total dwell time is short and the possibility of potential delays and bus bunching is low. On the other hand, having small distances ensures good area coverage and access, given that the service area of a stop is defined by a walking distance threshold. Achieving a balance between efficiency and coverage can boost ridership, but is a challenge that requires the consideration of many factors, including accessibility and performance policies. In the city of Chicago, the average stop spacing policy is 0.125 miles, or 8 stops per mile. This distance provides reasonable access to bus stops, but at the same time creates issues with high travel times and, in corridors with frequent service, bus bunching. CTA has been studying the possibility of increasing stop spacing; on Ashland Avenue, half of the stops were eliminated for route 9, while at the same time the express route X9 skips stops along the corridor. Chicago is a great candidate for a study of the effects of bus stop spacing in route travel time and ridership, because of the grid network and the variety in stop spacing along routes. The study focuses on parallel corridors, including Halsted, Ashland, Damen and Western. A review is also be conducted on stop spacing patterns and coverage potential to complement the initial analysis. (Image Source: Chicago Transit Authority)

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Feasibility of the Transition to a Battery Electric Fleet in Public Transit

Public transportation systems nowadays struggle to cover their operation and maintenance expenses in an environment of continuously decreasing ridership. Fare revenue covers no more than 50% of the total operation costs, while funding from federal and state governments is incapable of closing the gap of revenues and expenses. These funding issues cause difficulties in maintaining current assets, so it is even more difficult to fund improvements to the system, replacement of vehicles that have exceeded their useful life and building renovations. The limited funding created the need to include transportation asset management in public transit. The Federal Transit Administration (FTA) provides frameworks and software packages (Transit Economic Requirements Model, TERM) to make asset management accessible to transit agencies. In fact, FTA requires all agencies to create Asset Management plans, in order to be eligible for federal funding towards State of Good Repair improvements. This project aims at researching the vehicle replacement problem while taking advantage of the available new technologies in electric mobility. The project examines a variety of replacement alternatives, including the transition to a full battery electric bus fleet by the end of the study period. The analysis is made on the Chicago Transit Authority’s bus fleet; only vehicle-related costs are considered and investments in charging facilities are not included. (Image source: Proterra)

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