1997
DOI: 10.1016/s0360-8352(97)00266-0
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Modeling traffic operations at electronic toll collection and traffic management systems

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Cited by 34 publications
(9 citation statements)
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“…The results of the analysis showed that factors of vehicle category, payment form, tollbooth operator sex have the greatest influence on the service time. The vehicle category has the most impact, agreeing with previous studies (Zarrillo, 2000;Zarrillo et al, 1997;Woo & Hoel, 1991), that is, heavy vehicles have a lower acceleration rate and, due to the increased length of the vehicle, remain for a longer period of time in the tollbooth area.…”
Section: Discussionsupporting
confidence: 90%
“…The results of the analysis showed that factors of vehicle category, payment form, tollbooth operator sex have the greatest influence on the service time. The vehicle category has the most impact, agreeing with previous studies (Zarrillo, 2000;Zarrillo et al, 1997;Woo & Hoel, 1991), that is, heavy vehicles have a lower acceleration rate and, due to the increased length of the vehicle, remain for a longer period of time in the tollbooth area.…”
Section: Discussionsupporting
confidence: 90%
“…Diversos modelos analíticos foram desenvolvidos nos últimos anos visando analisar alguns dos parâmetros relativos à operação de praças de pedágio, entre os quais, os elaborados por Zarrillo et al (1997), Widmer et al (1999) e Oliveira et al (2003). O primeiro é um modelo matemático que reflete as condições de tráfego em um praça de pedágio com vários tipos de coleta de tarifa, incluindo a eletrônica.…”
Section: Pesquisas Desenvolvidas Sobre Praças De Pedágiounclassified
“…Arrival traffic and service time are often stochastic in nature. There is a body of research in developing empirical traffic delay functions (Lin, 2001;Fambro and Rouphail, 1997), stochastic queuing models (Newell, 1982), and microscopic traffic simulation models (Al-Deek et al, 2000;Saka et al, 2000;Robinson and Van Aerde, 1995;Zarrillo et al, 1997). While traffic simulation models can provide detailed traffic parameters including individual vehicle speeds and queue length they are often data demanding and require extensive model calibration.…”
Section: Overview Of Roadside Air Dispersion Modelingmentioning
confidence: 99%