Modeling and Estimation for Transit On-time Performance Improvement

Transit agencies have the opportunity to improve the delivery of services by using data from Intelligent Transportation Systems (ITS). On-time performance is an important measure. The objective of this paper is to adjust the timetables so that the probability of on-time performance is maximized. For...

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Main Author: Wang, Xiaobo
Format: Others
Published: FIU Digital Commons 2011
Subjects:
Online Access:http://digitalcommons.fiu.edu/etd/494
http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=1601&context=etd
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spelling ndltd-fiu.edu-oai-digitalcommons.fiu.edu-etd-16012018-07-19T03:32:35Z Modeling and Estimation for Transit On-time Performance Improvement Wang, Xiaobo Transit agencies have the opportunity to improve the delivery of services by using data from Intelligent Transportation Systems (ITS). On-time performance is an important measure. The objective of this paper is to adjust the timetables so that the probability of on-time performance is maximized. For this purpose we analyze data distributions of travel time and also consider the general case that data distribution is unknown. Statistical procedures are presented to find scheduled time for some selected distributions. Monte Carlo simulation is introduced for the purpose of finding scheduled time when data distribution is not known. Simulation studies indicate that the on-time performance would increase using the proposed methodology. The contribution of this paper is to provide transit system a procedure to set up or update their timetables based on current ITS data and its distribution, and hence increase level of service. 2011-11-04T07:00:00Z text application/pdf http://digitalcommons.fiu.edu/etd/494 http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=1601&context=etd FIU Electronic Theses and Dissertations FIU Digital Commons Transit On-Time Performance Distributions
collection NDLTD
format Others
sources NDLTD
topic Transit
On-Time Performance
Distributions
spellingShingle Transit
On-Time Performance
Distributions
Wang, Xiaobo
Modeling and Estimation for Transit On-time Performance Improvement
description Transit agencies have the opportunity to improve the delivery of services by using data from Intelligent Transportation Systems (ITS). On-time performance is an important measure. The objective of this paper is to adjust the timetables so that the probability of on-time performance is maximized. For this purpose we analyze data distributions of travel time and also consider the general case that data distribution is unknown. Statistical procedures are presented to find scheduled time for some selected distributions. Monte Carlo simulation is introduced for the purpose of finding scheduled time when data distribution is not known. Simulation studies indicate that the on-time performance would increase using the proposed methodology. The contribution of this paper is to provide transit system a procedure to set up or update their timetables based on current ITS data and its distribution, and hence increase level of service.
author Wang, Xiaobo
author_facet Wang, Xiaobo
author_sort Wang, Xiaobo
title Modeling and Estimation for Transit On-time Performance Improvement
title_short Modeling and Estimation for Transit On-time Performance Improvement
title_full Modeling and Estimation for Transit On-time Performance Improvement
title_fullStr Modeling and Estimation for Transit On-time Performance Improvement
title_full_unstemmed Modeling and Estimation for Transit On-time Performance Improvement
title_sort modeling and estimation for transit on-time performance improvement
publisher FIU Digital Commons
publishDate 2011
url http://digitalcommons.fiu.edu/etd/494
http://digitalcommons.fiu.edu/cgi/viewcontent.cgi?article=1601&context=etd
work_keys_str_mv AT wangxiaobo modelingandestimationfortransitontimeperformanceimprovement
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