15,386 research outputs found
Keys to effective transit strategies for commuting
Commuting poses relevant challenges to cities\u2019 transport systems. Various studies have identified transit as a tool to enhance sustainability, efficiency and quality of the commute. The scope of this paper is to present strategies that increase public transport attractiveness and positively impact its modal share, looking at some case studies and underlining key success factors and possible elements of replica to be ultimately planned in some of the contexts of the Interreg project SMART-COMMUTING. The strategies analyzed in this paper concern prices and fares, service expansion, service improvements, usage of vehicle locators and other technology, changes to the built environment. Relevant gains in transit modal share are more easily achievable when considering integrations between various strategies, thus adapting and tailoring the planning process to the specific context
Estimating Uncertainty of Bus Arrival Times and Passenger Occupancies
Travel time reliability and the availability of seating and boarding space are important indicators of bus service quality and strongly influence users’ satisfaction and attitudes towards bus transit systems. With Automated Vehicle Location (AVL) and Automated Passenger Counter (APC) units becoming common on buses, some agencies have begun to provide real-time bus location and passenger occupancy information as a means to improve perceived transit reliability. Travel time prediction models have also been established based on AVL and APC data. However, existing travel time prediction models fail to provide an indication of the uncertainty associated with these estimates. This can cause a false sense of precision, which can lead to experiences associated with unreliable service. Furthermore, no existing models are available to predict individual bus occupancies at downstream stops to help travelers understand if there will be space available to board.
The purpose of this project was to develop modeling frameworks to predict travel times (and associated uncertainties) as well as individual bus passenger occupancies. For travel times, accelerated failure-time survival models were used to predict the entire distribution of travel times expected. The survival models were found to be just as accurate as models developed using traditional linear regression techniques. However, the survival models were found to have smaller variances associated with predictions. For passenger occupancies, linear and count regression models were compared. The linear regression models were found to outperform count regression models, perhaps due to the additive nature of the passenger boarding process. Various modeling frameworks were tested and the best frameworks were identified for predictions at near stops (within five stops downstream) and far stops (further than eight stops). Overall, these results can be integrated into existing real-time transit information systems to improve the quality of information provided to passengers
Mobility and Equity for New York's Transit-Starved Neighborhoods: The Case for Full-Featured Bus Rapid Transit
New York City's public transportation system moves millions of people every day. But an increasing number who live in outer borough neighborhoods are stuck with unreliable transit options and long travel times tracked in hours, not minutes.It does not have to be this way.Developed by the Pratt Center for Community Development and funded by the Rockefeller Foundation, this report highlights the limitations of New York City's current public transit system, the adverse effects those limitations have on our economy and quality of life, and the role Bus Rapid Transit (BRT) can play in remedying these transit inequities.BRT has transformed cities across the world from Mexico City to Barcelona to Cleveland. At a fraction of the cost to build just a mile of subway rail, BRT gives riders a reliable way to get where they need to go.BRT is effective. It is innovative. And it could be the solution for New York's transit-starved neighborhoods
Stochastic on-time arrival problem in transit networks
This article considers the stochastic on-time arrival problem in transit
networks where both the travel time and the waiting time for transit services
are stochastic. A specific challenge of this problem is the combinatorial
solution space due to the unknown ordering of transit line arrivals. We propose
a network structure appropriate to the online decision-making of a passenger,
including boarding, waiting and transferring. In this framework, we design a
dynamic programming algorithm that is pseudo-polynomial in the number of
transit stations and travel time budget, and exponential in the number of
transit lines at a station, which is a small number in practice. To reduce the
search space, we propose a definition of transit line dominance, and techniques
to identify dominance, which decrease the computation time by up to 90% in
numerical experiments. Extensive numerical experiments are conducted on both a
synthetic network and the Chicago transit network.Comment: 29 pages; 12 figures. This manuscript version is made available under
the CC-BY-NC-ND 4.0 license
https://creativecommons.org/licenses/by-nc-nd/4.0
Optimizing Sustainable Transit Bus Networks in Smart Cities
Urban mobility has been facing several challenges in the recent years due to the increasing populations and private vehicles ownership, which led to several negative environmental and social impacts in big cities. In this dissertation, we investigate how decision support systems can enhance the role of transit bus networks in the transition to more sustainable and convenient urban mobility
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Reliable routing in schedule-based transit networks
textA framework is proposed for determining the least expected cost path in a schedule-based time-expanded public transit network where travel times, and thus bus arrival and departure times at stops, are stochastic. Transfer reliability is incorporated in a label-correcting algorithm with a penalty function for the expected waiting time when transferring that reflects the likelihood of making a successful transfer. The algorithm is implemented in transit assignment on an Austin, Texas test network, using actual bus arrival and departure time distributions from vehicle location data. Assignment results are compared with those of a deterministic shortest path based on the schedule and from a calibrated transit assignment model. Simulations of the network and passenger paths are also conducted to evaluate the overall path reliability. The reliable shortest path algorithm is found to penalize transferring and provide paths with improved transfer and overall reliability. The proposed model is realistic, incorporating reliability measures from vehicle location data, and practical, given the efficient shortest path approach and application to transit assignment.Civil, Architectural, and Environmental Engineerin
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A decision support system to improve service quality in multimodal rapid rail systems: A bayesian perspective
Copyright @ 2011 International Conference on Computers and Industrial EngineeringIn this study, the accessibility of the rail transit stations in a multimodal network formed by a trunk line and its feeder lines are defined. Connectivity between lines and the accessibility of the nodes identify the overall spatial structure of the network. The factors influencing the access choices of rail transit stations and satisfaction of transit travelers in rapid rail transit systems are investigated in order to gain insights into the factors and their interrelationships. The quantitative indications of the relationships are produced and the complexity of evaluating the performance of transit services is exhibited. As the interrelationships are mainly stochastic, the problem on hand is treated as a Bayesian Belief Network (BBN). A BBN approach that presents a learning mechanism is employed and is used as an alternative decision making tool to analyze the rapid rail transit services and identify policies to improve the traveler’s level of service
A Multi-modal Trip Distribution Model
This paper presents a multimodal trip distribution function estimated and validated for the metropolitan Washington region. In addition, a methodology for measuring accessibility, which is used as a measure of effectiveness for networks, using the impedance curves in the distribution model is described. This methodology is applied at the strategic planning level to alternative HOV alignments to select alignments for further study and Right-of-Way preservation. .
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