Socioeconomic, Community-Based Approach for Developing Integrated Mass Transit Systems: Application to City of Baltimore, Maryland

2002 ◽  
Vol 1793 (1) ◽  
pp. 71-79 ◽  
Author(s):  
Claudia Goetz Phillips ◽  
Hazel Ruth Edwards
Keyword(s):  
Mass Transit ◽  
Community Based ◽  
Transit Systems

scholarly journals Using Data Mining to Analyze Dwell Time and Nonstop Running Time in Road-Based Mass Transit Systems

Proceedings ◽  
2018 ◽  
Vol 2 (19) ◽  
pp. 1217
Author(s):  
Teresa Cristóbal ◽  
Gabino Padrón ◽  
Alexis Quesada ◽  
Francisco Alayón ◽  
Gabriel de Blasio ◽  
...  
Keyword(s):  
Data Mining ◽  
Travel Time ◽  
Dwell Time ◽  
Mass Transit ◽  
Transit Systems ◽  
Running Time ◽  
Bus Stop ◽  
Transport Line ◽  
Using Data

Travel Time plays a key role in the quality of service in road-based mass transit systems. In this type of mass transit systems, travel time of a public transport line is the sum of the dwell time at each bus stop and the nonstop running time between pair of consecutives bus stops of the line. The aim of the methodology presented in this paper is to obtain the behavior patterns of these times. Knowing these patterns, it would be possible to reduce travel time or its variability to make more reliable travel time predictions. To achieve this goal, the methodology uses data related to check-in and check-out movements of the passengers and vehicles GPS positions, processing this data by Data Mining techniques. To illustrate the validity of the proposal, the results obtained in a case of use in presented.

Assessment of energy-saving techniques in direct-current-electrified mass transit systems

2014 ◽  
Vol 38 ◽  
pp. 85-100 ◽  
Author(s):  
Álvaro J. López-López ◽  
Ramón R. Pecharromán ◽  
Antonio Fernández-Cardador ◽  
A. Paloma Cucala
Keyword(s):  
Energy Saving ◽  
Direct Current ◽  
Mass Transit ◽  
Transit Systems

Forging the Way to a Better Axle

2005 ◽  
Author(s):  
Amy L. Miller ◽  
David S. Strayer ◽  
Todd Williams
Keyword(s):  
Finite Element Analysis ◽  
Mass Transit ◽  
The United States ◽  
Design Criteria ◽  
Element Analysis ◽  
Transit Systems ◽  
Industry Standard ◽  
Final Design ◽  
And Performance ◽  
Innovative Concept

Historically, rail “axles” for the center truck of Low Floor Mass Transit Cars have been manufactured and supplied by European companies. The industry standard is a fabricated assembly comprised of forged ends welded to a structural steel center of various shapes. Several factors have enticed one domestic supplier to look for a better way to manufacture the axle in the United States. The word axle will be used in this paper, although technically the word “support” is more valid as an “axle” is assumed to rotate and this “support” does not. Currently, Penn Machine is producing its latest support, a one piece forged axle with the properties of the previous welded assembly. Many considerations, including material type, manufacturability, stress and deflection, weight, and dimensional fit, were made prior to approval of the final design. Because previous models were designed and manufactured overseas, European design criteria and materials had to be considered, and in some cases modified for the domestic market. The analysis approach began with a European calculation method. Additional analysis was performed to evaluate modifications. Finite Element Analysis was conducted to refine the design and to investigate material reducing options. The proposed paper outlines the design process used in bringing this new and innovative concept off the boards and into reality. It is the hope of the authors that others will recognize domestic opportunities by observance of the process used to create the new axle. To date, the new axle is being proposed for use on two new transit systems. The cars will be tested with the new axle to insure safety and performance.

scholarly journals A Study on the Behavior of Clustering Techniques for Modeling Travel Time in Road-Based Mass Transit Systems

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 18
Author(s):  
Cristóbal ◽  
Padrón ◽  
Quesada-Arencibia ◽  
Alayón ◽  
Blasio ◽  
...  
Keyword(s):  
Travel Time ◽  
Behavior Pattern ◽  
Large Data ◽  
Mass Transit ◽  
Clustering Methods ◽  
Knowledge Modeling ◽  
Activity Data ◽  
Transit Systems ◽  
Clustering Techniques ◽  
Key Factor

In road-based mass transit systems, the travel time is a key factor affecting quality of service. For this reason, to know the behavior of this time is a relevant challenge. Clustering methods are interesting tools for knowledge modeling because these are unsupervised techniques, allowing hidden behavior patterns in large data sets to be found. In this contribution, a study on the utility of different clustering techniques to obtain behavior pattern of travel time is presented. The study analyzed three clustering techniques: K-medoid, Diana, and Hclust, studying how two key factors of these techniques (distance metric and clusters number) affect the results obtained. The study was conducted using transport activity data provided by a public transport operator.

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