Making public transportation schedule information consumable for improved decision making

2012 ◽  
Author(s):  
Raj Gupta ◽  
Biplav Srivastava ◽  
Srikanth Tamilselvam
Keyword(s):  
Decision Making ◽  
Public Transportation ◽  
Transportation Schedule

scholarly journals DESIGNING A DATA VISUALISATION AND ANALYSIS TOOL FOR SUPPORTING DECISION-MAKING WITH PUBLIC TRANSPORTATION NETWORK

2021 ◽  
Vol 1 ◽  
pp. 1093-1102
Author(s):  
Flore Vallet ◽  
Mostepha Khouadjia ◽  
Ahmed Amrani ◽  
Juliette Pouzet
Keyword(s):  
Decision Making ◽  
Public Transportation ◽  
Transportation Network ◽  
Visual Exploration ◽  
Problem Solution ◽  
Analysis Tool ◽  
Complex Data ◽  
Data Visualisation ◽  
Ex Post ◽  
Passenger Flows

AbstractMassive data are surrounding us in our daily lives. Urban mobility generates a very high number of complex data reflecting the mobility of people, vehicles and objects. Transport operators are primary users who strive to discover the meaning of phenomena behind traffic data, aiming at regulation and transport planning. This paper tackles the question "How to design a supportive tool for visual exploration of digital mobility data to help a transport analyst in decision making?” The objective is to support an analyst to conduct an ex post analysis of train circulation and passenger flows, notably in disrupted situations. We propose a problem-solution process combined with data visualisation. It relies on the observation of operational agents, creativity sessions and the development of user scenarios. The process is illustrated for a case study on one of the commuter line of the Paris metropolitan area. Results encompass three different layers and multiple interlinked views to explore spatial patterns, spatio-temporal clusters and passenger flows. We join several transport network indicators whether are measured, forecasted, or estimated. A user scenario is developed to investigate disrupted situations in public transport.

scholarly journals Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Sen Liu ◽  
Zhilan Song ◽  
Shuqi Zhong
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Public Transportation ◽  
Group Decision ◽  
Numerical Study ◽  
Hub Location ◽  
Hub Location Problem ◽  
The Public ◽  
Multiple Attribute ◽  
Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

Developing Management Systems for Statewide Transportation Planning: Early Lessons

1996 ◽  
Vol 1552 (1) ◽  
pp. 66-70 ◽  
Author(s):  
Steven J. Kish ◽  
Michael D. Meyer
Keyword(s):  
Decision Making ◽  
Public Transportation ◽  
Implementation Strategy ◽  
Information Needs ◽  
Decision Makers ◽  
Management Systems ◽  
Department Of Transportation ◽  
Transportation Management ◽  
Organizational Planning ◽  
Decision Making Processes

The implementation of two management systems, the intermodal and public transportation management systems, in the Georgia Department of Transportation is examined. Early experience with this implementation suggests that key elements of an implementation strategy are characteristic of success in such an organizational environment. These include establishing organizational responsibilities, establishing guidance principles, assessing the organizational planning and decision-making processes, assessing the environmental context for the management system, establishing an implementation strategy that has tangible intermediate results, and identifying an agency “champion” for implementation. The challenge of implementing management systems within any organization is understanding the decision-making process and the information needs of the agency decision makers.

A Public Transportation Decision-Making Model within a Metropolitan Area

2016 ◽  
Vol 47 (6) ◽  
pp. 1048-1072 ◽  
Author(s):  
Rebecca A. Scott ◽  
Benjamin T. George ◽  
Victor R. Prybutok
Keyword(s):  
Decision Making ◽  
Metropolitan Area ◽  
Public Transportation ◽  
Decision Making Model

scholarly journals Decision-making on Public Transportation Services Based on the Socio-economic, Psychological, and Environmental Concern Factors

2020 ◽  
Vol 14 (1) ◽  
pp. 22-31
Author(s):  
Nattanin Ueasin
Keyword(s):  
Decision Making ◽  
Public Transportation ◽  
Environmental Concern ◽  
Service Selection ◽  
Well Being ◽  
Environmental Conservation ◽  
Transport Systems ◽  
Border Area ◽  
Transportation Services ◽  
The Impact

Aim: This research aims to study the socio-economic, psychological, and environmental factors which affect the decision making of passengers with regard to the use of public transportation route from Nong Khai province, which is considered as the border area of Thailand and Laos, to many destinations. Methods: The study was initially carried out by collecting data from 450 passengers using two public transportation services and 200 passengers using private cars. An analysis was conducted by means of descriptive statistics, factor analysis and binary logistic regression. Results: The results showed that the status, age, domicile, self-satisfaction and accomplishment, safety of life and property, and self-consciousness and environmental conservation practice influenced the choice of both the alternatives. Conclusion: To develop a service model, a variety of bus and van services must be provided to match the varied demand of passengers with different levels of purchasing power. It is also important to consider the impact of various factors that affect the public bus service selection, which may result in improved public transport systems. As a consequence, the well-being of border area citizens can be improved.

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