Characterizing corridor-level travel time distributions based on stochastic flows and segment capacities

Hao Lei, Xuesong Zhou, George F. List, Jeffrey Taylor

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for corridors that contain multiple bottlenecks. A set of analytical equations are used to calculate the number of queued vehicles ahead of a probe vehicle and further capture many important factors affecting travel times: the prevailing congestion level, queue discharge rates at the bottlenecks, and flow rates associated with merges and diverges. Based on multiple random scenarios and a vector of arrival times, the lane-by-lane delay at each bottleneck along the corridor is recursively estimated to produce a route-level travel time distribution. The model incorporates stochastic variations of bottleneck capacity and demand and explains the travel time correlations between sequential links. Its data needs are the entering and exiting flow rates and a sense of the lane-by-lane distribution of traffic at each bottleneck. A detailed vehicle trajectory data-set from the Next Generation SIMulation (NGSIM) project has been used to verify that the estimated distributions are valid, and the sources of estimation error are examined.

Original languageEnglish (US)
Article number990672
JournalCogent Engineering
Volume2
Issue number1
DOIs
StatePublished - Dec 31 2015

Fingerprint

Travel time
Flow rate
Stochastic models
Error analysis
Trajectories

Keywords

  • queue model
  • stochastic capacity
  • stochastic demand
  • travel time reliability

ASJC Scopus subject areas

  • Computer Science(all)
  • Chemical Engineering(all)
  • Engineering(all)

Cite this

Characterizing corridor-level travel time distributions based on stochastic flows and segment capacities. / Lei, Hao; Zhou, Xuesong; List, George F.; Taylor, Jeffrey.

In: Cogent Engineering, Vol. 2, No. 1, 990672, 31.12.2015.

Research output: Contribution to journalArticle

@article{a3aa897e6d8048129700acfe6a7695cb,
title = "Characterizing corridor-level travel time distributions based on stochastic flows and segment capacities",
abstract = "Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for corridors that contain multiple bottlenecks. A set of analytical equations are used to calculate the number of queued vehicles ahead of a probe vehicle and further capture many important factors affecting travel times: the prevailing congestion level, queue discharge rates at the bottlenecks, and flow rates associated with merges and diverges. Based on multiple random scenarios and a vector of arrival times, the lane-by-lane delay at each bottleneck along the corridor is recursively estimated to produce a route-level travel time distribution. The model incorporates stochastic variations of bottleneck capacity and demand and explains the travel time correlations between sequential links. Its data needs are the entering and exiting flow rates and a sense of the lane-by-lane distribution of traffic at each bottleneck. A detailed vehicle trajectory data-set from the Next Generation SIMulation (NGSIM) project has been used to verify that the estimated distributions are valid, and the sources of estimation error are examined.",
keywords = "queue model, stochastic capacity, stochastic demand, travel time reliability",
author = "Hao Lei and Xuesong Zhou and List, {George F.} and Jeffrey Taylor",
year = "2015",
month = "12",
day = "31",
doi = "10.1080/23311916.2014.990672",
language = "English (US)",
volume = "2",
journal = "Cogent Engineering",
issn = "2331-1916",
publisher = "Cogent OA",
number = "1",

}

TY - JOUR

T1 - Characterizing corridor-level travel time distributions based on stochastic flows and segment capacities

AU - Lei, Hao

AU - Zhou, Xuesong

AU - List, George F.

AU - Taylor, Jeffrey

PY - 2015/12/31

Y1 - 2015/12/31

N2 - Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for corridors that contain multiple bottlenecks. A set of analytical equations are used to calculate the number of queued vehicles ahead of a probe vehicle and further capture many important factors affecting travel times: the prevailing congestion level, queue discharge rates at the bottlenecks, and flow rates associated with merges and diverges. Based on multiple random scenarios and a vector of arrival times, the lane-by-lane delay at each bottleneck along the corridor is recursively estimated to produce a route-level travel time distribution. The model incorporates stochastic variations of bottleneck capacity and demand and explains the travel time correlations between sequential links. Its data needs are the entering and exiting flow rates and a sense of the lane-by-lane distribution of traffic at each bottleneck. A detailed vehicle trajectory data-set from the Next Generation SIMulation (NGSIM) project has been used to verify that the estimated distributions are valid, and the sources of estimation error are examined.

AB - Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for corridors that contain multiple bottlenecks. A set of analytical equations are used to calculate the number of queued vehicles ahead of a probe vehicle and further capture many important factors affecting travel times: the prevailing congestion level, queue discharge rates at the bottlenecks, and flow rates associated with merges and diverges. Based on multiple random scenarios and a vector of arrival times, the lane-by-lane delay at each bottleneck along the corridor is recursively estimated to produce a route-level travel time distribution. The model incorporates stochastic variations of bottleneck capacity and demand and explains the travel time correlations between sequential links. Its data needs are the entering and exiting flow rates and a sense of the lane-by-lane distribution of traffic at each bottleneck. A detailed vehicle trajectory data-set from the Next Generation SIMulation (NGSIM) project has been used to verify that the estimated distributions are valid, and the sources of estimation error are examined.

KW - queue model

KW - stochastic capacity

KW - stochastic demand

KW - travel time reliability

UR - http://www.scopus.com/inward/record.url?scp=84995426743&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84995426743&partnerID=8YFLogxK

U2 - 10.1080/23311916.2014.990672

DO - 10.1080/23311916.2014.990672

M3 - Article

VL - 2

JO - Cogent Engineering

JF - Cogent Engineering

SN - 2331-1916

IS - 1

M1 - 990672

ER -