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Analysis of Trends in Data on Transit Bus Dwell Times

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00096436" target="_blank" >RIV/00216224:14330/17:00096436 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.3141/2619-07" target="_blank" >https://doi.org/10.3141/2619-07</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3141/2619-07" target="_blank" >10.3141/2619-07</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Analysis of Trends in Data on Transit Bus Dwell Times

  • Popis výsledku v původním jazyce

    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.

  • Název v anglickém jazyce

    Analysis of Trends in Data on Transit Bus Dwell Times

  • Popis výsledku anglicky

    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.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2017

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Transportation Research Record: Journal of the Transportation Research Board

  • ISSN

    0361-1981

  • e-ISSN

  • Svazek periodika

    2619

  • Číslo periodika v rámci svazku

    2619

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    11

  • Strana od-do

    64-74

  • Kód UT WoS článku

    000413464000008

  • EID výsledku v databázi Scopus

    2-s2.0-85033780713