2014
DOI: 10.1155/2014/867236
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Dynamic Analyses of Urban Expressway Network with Mesoscopic Traffic Flow Model Integrated Variable Speed Limits

Abstract: Urban congestion is a major and costly problem in many cities both in China and other countries. The purpose of building urban expressway is to alleviate the growing traffic pressure. In this paper, the mesoscopic traffic flow models are improved by variable speed limits strategy for the dynamic of vehicles on urban expressway network. The models include static queuing model, the velocity model, and the movement model of the vehicle. Moreover the method of the simulation is also proposed. So that we can get th… Show more

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Cited by 9 publications
(5 citation statements)
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“…This section evaluates the proposed ACD approach and compares it with some important related works: Intelligent Driver Model (IDM) [35] and Human driving (HUMAN) [36]. In IDM [35], the vehicle dynamically drives according to the relative velocity and distance of the precedent vehicle under an average traffic loading. That is, the 1.5 s of time headway is considered.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…This section evaluates the proposed ACD approach and compares it with some important related works: Intelligent Driver Model (IDM) [35] and Human driving (HUMAN) [36]. In IDM [35], the vehicle dynamically drives according to the relative velocity and distance of the precedent vehicle under an average traffic loading. That is, the 1.5 s of time headway is considered.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…In today's rapidly expanding cities, urbanization and transportation development have become intertwined [1]. As a response to the growing volume of vehicles, urban expressways have been constructed, efficiently connecting different parts of the city [2][3][4]. While these developments improve transportation, they have also resulted in the construction of residential buildings and communities close to these expressways.…”
Section: Introduction 1backgroundmentioning
confidence: 99%
“…The effect of congestion was treated differently in most models. For example, some have used traffic properties like volume and speed from simulation results [3], while others have clustered their data into different time periods [4]. Historical data based models are used in geographical areas with less traffic congestion, because the models assumed cyclical traffic patterns.…”
mentioning
confidence: 99%