Detailed Information on Publication Record
2017
Analysis of Trends in Data on Transit Bus Dwell Times
ISAAC K., Isukapati, Hana RUDOVÁ, Gregory BARLOW and Stephen SMITHBasic information
Original name
Analysis of Trends in Data on Transit Bus Dwell Times
Authors
ISAAC K., Isukapati (356 India), Hana RUDOVÁ (203 Czech Republic, guarantor, belonging to the institution), Gregory BARLOW (840 United States of America) and Stephen SMITH (840 United States of America)
Edition
Transportation Research Record: Journal of the Transportation Research Board, 2017, 0361-1981
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 0.695
RIV identification code
RIV/00216224:14330/17:00096436
Organization unit
Faculty of Informatics
UT WoS
000413464000008
Keywords in English
traffic signal control; bus dwell time; data analysis
Tags
International impact, Reviewed
Změněno: 18/5/2018 04:09, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
Transit vehicles create special challenges for urban traffic signal control. Signal timing plans are typically designed for the flow of passenger vehicles, but transit vehicles, with frequent stops and uncertain dwell times, may have very different flow patterns that fail to match these plans. Transit vehicles stopping on urban streets can also restrict or block other traffic on the road. This results in increased overall wait times and delays throughout the system for transit vehicles and other traffic. Transit signal priority (TSP) systems are often used to mitigate some of these issues, primarily addressing delay to the transit vehicles. However, existing TSP strategies give unconditional priority to transit vehicles, exacerbating quality of service for other modes. In networks where transit vehicles have significant effects on traffic congestion, particularly urban areas, using more realistic models of transit behavior in adaptive traffic signal control could reduce delay for all modes. Estimating the arrival time of a transit vehicle at an intersection requires an accurate model of transit stop dwell times. As a first step toward developing a model for predicting bus arrival times, this paper analyzes trends in automatic vehicle location (AVL) data collected over a two-year period, allowing several inferences to be drawn about the statistical nature of dwell times, particularly for use in real-time control and transit signal priority. Based on this trend analysis, we argue that an effective predictive dwell time distribution model must treat independent variables as random or stochastic regressors.