Abstract

The macroscopic traffic flow model is the cornerstone of traffic flow theory and can be applied to investigate manytraffic planning and management issues. However, the macroscopic model of the heterogeneous traffic flow has not been profoundly studied. This paper developed a novel macroscopic model of the heterogeneous traffic flow under a partly connected and automated environment based on the safety potential field (SPF) theory. The SPF model was applied to describe the microscopic driving behaviour of traditional human-driven vehicles (HVs) and connected and automated vehicles (CAVs). A fundamental diagram (FD) model was derived according to the correlation with the microscopic car-following model under a steady-state condition. To verify the correlation between the FD and the microscopic simulation results, a Monte-Carlo-simulation was also performed. Finally, the macroscopic model of the heterogeneous traffic flow was validated through a simulation on a road section with a bottleneck under different CAVs market penetration rates ranging from 0.0 to 1.0. The results indicate that introducing the CAVs into the pure traffic flow of HVs may slightly have a negligible impact on road capacity when the CAVs penetration rate at a lower level, but the impact increases significantly as the CAVs penetration rate increased.

Highlights

  • The Connected and Automated Vehicles (CAVs) technology has offered unprecedented opportunities for people to open the door of the Intelligent Traffic System (ITS)

  • This paper develops the traffic flow model for pure CAVs or human-driven vehicles (HVs) traffic, mixed CAVs and HVs traffic, including the microscopic behavior analysis model and the macroscopic fundamental diagram (FD) model

  • From the perspective of the types of information that can be accepted by CAVs and HVs, the Traffic flow driving di rect ion

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Summary

Introduction

The Connected and Automated Vehicles (CAVs) technology has offered unprecedented opportunities for people to open the door of the Intelligent Traffic System (ITS). The vehicles can provide feedback on the required motion behavior in combination with the actual traffic environment and driving requirements[1,2]. Benefit from those characteristics described above, CAVs have the potential for the improvement of traffic flow performance in many aspects (e.g.,traffic safety, traffic efficiency, stability performance, and energy-saving) [3]–[8]. Before the arrival of a pure CAVs environment (All vehicles reach the highest automation level), the traffic flow on the road is bound to show a kind of heterogeneity. Investigating the characteristics of such kind of mixed traffic flow is a novel

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