2017
Analysis of Trends in Data on Transit Bus Dwell Times
ISAAC K., Isukapati, Hana RUDOVÁ, Gregory BARLOW a Stephen SMITHZákladní údaje
Originální název
Analysis of Trends in Data on Transit Bus Dwell Times
Autoři
ISAAC K., Isukapati (356 Indie), Hana RUDOVÁ (203 Česká republika, garant, domácí), Gregory BARLOW (840 Spojené státy) a Stephen SMITH (840 Spojené státy)
Vydání
Transportation Research Record: Journal of the Transportation Research Board, 2017, 0361-1981
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Spojené státy
Utajení
není předmětem státního či obchodního tajemství
Odkazy
Impakt faktor
Impact factor: 0.695
Kód RIV
RIV/00216224:14330/17:00096436
Organizační jednotka
Fakulta informatiky
UT WoS
000413464000008
Klíčová slova anglicky
traffic signal control; bus dwell time; data analysis
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 18. 5. 2018 04:09, RNDr. Pavel Šmerk, Ph.D.
Anotace
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.