01152453

Component

https://doi.org/10.3141/2188-09

http://scholar.google.com...+Guo&publication_year=2010

Travel time reliability has received much attention from researchers and practitioners because it not only affects driver route choice behavior but also is used in the assessment of transportation system performance. Current state-of-the-art travel time reliability research assumes that roadway travel times follow a unimodal distribution. Specifically, a Weibull, exponential, lognormal, or normal distribution is used within the context of travel time reliability modeling. However, field observations demonstrate that roadway travel times are multimodal, especially during peak periods. This paper demonstrates that the multimodes observed in field data are a result of temporal variations in travel times both between and within days. This study evaluates the potential for generating multimodal travel times by using INTEGRATION software and investigates the underlying traffic states that result in these multimodes. The study validates the two-state model proposed in an earlier study and demonstrates the robustness of model parameter estimates under varying stochastic traffic congestion levels and sampling techniques.

01329026

10-1289

English

pp 74-84

2010

Transportation Research Record: Journal of the Transportation Research Board

9780309160629

Print

Figures (7) ; References (25) ; Tables (3)

Calibration; Mathematical models; Peak hour traffic; State of the art; Traffic congestion; Travel time

INTEGRATION (Computer model)

Bimodal distributions; Field data; Multimodal distributions; Travel time reliability

Highways; Operations and Traffic Management; I71: Traffic Theory

TRIS, TRB, ATRI

Jan 25 2010 10:34AM

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• Cellular Automata Model for Work Zone Traffic
• Effect of Visible Light Transmission from Vehicle Windows on Traffic Flow of Car-Following
• Effects of Merging and Diverging on Freeway Traffic Oscillations: Theory and Observation
• Empirical Analysis of Merging Behavior at Freeway On-Ramp
• Empirical Results of Effects of Various Causal Factors on Car-Following Behavior
• Generic Calibration Framework for Joint Estimation of Car-Following Models by Using Microscopic Data
• Hybrid Extended Kalman Filtering Approach for Traffic Density Estimation Along Signalized Arterials: Use of Global Positioning System Data
• Identification and Calibration of Site-Specific Stochastic Freeway Breakdown and Queue Discharge
• Lagrangian Formulation of Multiclass Kinematic Wave Model
• Likelihood and Duration of Flow Breakdown: Modeling the Effect of Weather
• Macroscopic Characteristics of Lane-Changing Traffic
• Mental Workload, Longitudinal Driving Behavior, and Adequacy of Car-Following Models for Incidents in Other Driving Lane
• Mesoscopic Modeling of Bus Public Transportation
• Modeling Vehicular Merging Behavior Under Heterogeneous Traffic Conditions
• Multistate Model for Travel Time Reliability
• Onset of Congestion from Low-Speed Merging Maneuvers Within Free-Flow Traffic Stream: Analytical Solution
• Using Trajectory Data to Analyze Intradriver Heterogeneity in Car-Following