Evaluating Impacts of Overloaded Heavy Vehicles on Freeway Traffic Condition by a Novel Multi-Class Traffic Flow Model

Xiang Wang, Po Zhao and Yanyun Tao
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Xiang Wang: School of Rail Transportation, Soochow University, No.8 Jixue Road, Suzhou 215000, China
Po Zhao: School of Rail Transportation, Soochow University, No.8 Jixue Road, Suzhou 215000, China
Yanyun Tao: School of Rail Transportation, Soochow University, No.8 Jixue Road, Suzhou 215000, China

Sustainability, 2018, vol. 10, issue 12, 1-22

Abstract: Overloaded heavy vehicles (HVs) have significant negative impacts on traffic conditions due to their inferior driving performance. Highway authorities need to understand the impact of overloaded HVs to assess traffic conditions and set management strategies. We propose a multi-class traffic flow model based on Smulders fundamental diagram to analyze the influence of overloaded HVs on traffic conditions. The relationship between the overloading ratio and maximum speed is established by freeway toll collection data for different types of HVs. Dynamic passenger car equivalent factors are introduced to represent the various impacts of overloaded HVs in different traffic flow patterns. The model is solved analytically and discussed in detail in the appendices. The model validation results show that the proposed model can represent traffic conditions more accurately with consideration for overloaded HVs. The scenario tests indicate that the increase of overloaded HVs leads to both a higher congestion level and longer duration.

Keywords: freeway traffic operation and management; multi-class traffic flow model; analytical method; overloaded HVs (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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