Details:

Creators:
Margiotta, Richard ; Cohen, H. S. (Harry S.) ; DeCorla-Souza, Patrick
Margiotta, Richard ; Cohen, H. S. (Harry S.) ; DeCorla-Souza, Patrick Less -
Subject/TRT Terms:
[+]
Bottlenecks Congestion Management Equations Free Flow Speeds Highway Capacity Mathematical Prediction Prediction Models QSIM Queuing Theory Speed And Delay Studies Stochastic Processes Traffic Congestion Traffic Estimation Traffic Flow Transportation Planning Travel Forecasting
DOI:
https://doi.org/10.21949/1403576
Resource Type:
Research Paper
Geographical Coverage:
United States
TRIS Online Accession Number:
00780089
NTL Classification:
NTL-PLANNING AND POLICY-PLANNING AND POLICY;NTL-OPERATIONS AND TRAFFIC CONTROLS-Congestion;NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Flow;
Abstract:
Estimation of vehicle speed and delay is fundamental to many forms of

transportation planning analyses including air quality, long-range travel

forecasting, major investment studies, and congestion management systems.

However, existing planning-level techniques do a poor job of estimating the

duration and extent of congestion. To improve the state of the practice, a

simplified queuing-based model, QSIM, was developed. QSIM incorporates several

features including: the use of temporal distributions as a basis for developing

hourly traffic estimates; estimation of "peak spreading"; accounting for daily

variation in traffic by allowing hourly traffic estimates to vary stochastically;

for freeways, the inclusion of a capacity drop after flow has broken down (i.e.,

after the onset of queuing) to model the growth and dissipation of queues; for

arterials, considering the effects of signal density and progression; separate

functions to estimate speeds in queuing and free-flow conditions based on

relationships developed with microscopic traffic simulation models; use of the

concept of highway capacity to determine when traffic operates under free-flow

and queuing conditions as well as a basis for estimating free-flow speeds and

the extent of queuing on the test link; and estimating delay rather than speed

as the predictive variable. (Speed is then developed as a function of delay and

free-flow speed.) The model was used to develop a dataset from which a series

of predictive equations were developed. The equations use only a few, readily

available independent variables. Application of the new procedure shows that

under congested conditions, it predicts substantially more delay than do

traditional methods. Future work includes field validation of the models and

extending them to cover a variety of bottleneck conditions.


Format:
PDF
Collection(s):
US Transportation Collection
Main Document Checksum:
[+]
urn:sha256:a4c469f08b4650761a27fcaaf8ceb117e47c62507a237f82aa013ce113e7dc96
Download URL:
https://rosap.ntl.bts.gov/view/dot/12936/dot_12936_DS1.pdf
File Type:

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