TY - GEN
T1 - A comparative methodology for estimating the capacity of a freeway section
AU - Ozbay, Kaan
AU - Ozguven, Eren Erman
PY - 2007
Y1 - 2007
N2 - The random characteristics of the traffic flow make it essential to have a random component and therefore add a stochastic meaning to the deterministic parameters. This paper aims to improve the conventional deterministic approach to the freeway capacity by estimating parameters of the various probability distribution functions that are likely to represent the probabilistic nature of freeway traffic capacity. Firstly, Maximum Likelihood Estimation method is applied to estimate the capacity distribution function. Then, confidence intervals for the capacity distribution function are calculated using Bayesian statistics techniques that can address the difficult problem of censored data. Finally, a comparative analysis has been conducted between the estimations of deterministic and probabilistic models to come up with a conclusion regarding spatial and temporal characteristics of freeway capacity. The analysis results indicate that including stochasticity in the model estimation results in better representation of observed data and thus improve understanding of real-life situations.
AB - The random characteristics of the traffic flow make it essential to have a random component and therefore add a stochastic meaning to the deterministic parameters. This paper aims to improve the conventional deterministic approach to the freeway capacity by estimating parameters of the various probability distribution functions that are likely to represent the probabilistic nature of freeway traffic capacity. Firstly, Maximum Likelihood Estimation method is applied to estimate the capacity distribution function. Then, confidence intervals for the capacity distribution function are calculated using Bayesian statistics techniques that can address the difficult problem of censored data. Finally, a comparative analysis has been conducted between the estimations of deterministic and probabilistic models to come up with a conclusion regarding spatial and temporal characteristics of freeway capacity. The analysis results indicate that including stochasticity in the model estimation results in better representation of observed data and thus improve understanding of real-life situations.
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U2 - 10.1109/ITSC.2007.4357728
DO - 10.1109/ITSC.2007.4357728
M3 - Conference contribution
AN - SCOPUS:49249110792
SN - 1424413966
SN - 9781424413966
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 1034
EP - 1039
BT - 10th International IEEE Conference on Intelligent Transportation Systems, ITSC 2007
T2 - 10th International IEEE Conference on Intelligent Transportation Systems, ITSC 2007
Y2 - 30 September 2007 through 3 October 2007
ER -