Spatiotemporal Patterns in Heterogeneous Traffic Flow

2004 ◽  
pp. 509-543
Author(s):  
Boris S. Kerner
Keyword(s):  
Traffic Flow ◽  
Spatiotemporal Patterns ◽  
Heterogeneous Traffic

Dynamic Models of Heterogeneous Traffic Flow on Highways

2020 ◽  
Vol 81 (8) ◽  
pp. 1486-1498
Author(s):  
M.A. Fedotkin ◽  
A.M. Fedotkin ◽  
E.V. Kudryavtsev
Keyword(s):  
Traffic Flow ◽  
Dynamic Models ◽  
Heterogeneous Traffic

Network-Level Heterogeneous Traffic Flow Modelling in VISSIM

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Ranju Mohan ◽  
Susan Eldhose ◽  
Gautham Manoharan
Keyword(s):  
Traffic Flow ◽  
Heterogeneous Traffic ◽  
Flow Modelling ◽  
Traffic Flow Modelling

Microscopic modelling of area-based heterogeneous traffic flow: Area selection and vehicle movement

2020 ◽  
Vol 111 ◽  
pp. 373-396
Author(s):  
Nikhil Chandra Sarkar ◽  
Ashish Bhaskar ◽  
Zuduo Zheng ◽  
Marc P Miska
Keyword(s):  
Traffic Flow ◽  
Heterogeneous Traffic ◽  
Flow Area ◽  
Area Selection ◽  
Microscopic Modelling ◽  
Vehicle Movement

Model and Stability of the Traffic Flow Consisting of Heterogeneous Drivers

2015 ◽  
Vol 10 (3) ◽  
Author(s):  
Da Yang ◽  
Liling Zhu ◽  
Yun Pu
Keyword(s):  
Traffic Flow ◽  
Heterogeneous Traffic ◽  
Model Parameters ◽  
Optimal Velocity ◽  
Stability Functions ◽  
Car Following Model ◽  
Traffic Wave ◽  
The Stability ◽  
Different Characteristics ◽  
Stationary Velocity

Although traffic flow has attracted a great amount of attention in past decades, few of the studies focused on heterogeneous traffic flow consisting of different types of drivers or vehicles. This paper attempts to investigate the model and stability analysis of the heterogeneous traffic flow, including drivers with different characteristics. The two critical characteristics of drivers, sensitivity and cautiousness, are taken into account, which produce four types of drivers: the sensitive and cautious driver (S-C), the sensitive and incautious driver (S-IC), the insensitive and cautious driver (IS-C), and the insensitive and incautious driver (IS-IC). The homogeneous optimal velocity car-following model is developed into a heterogeneous form to describe the heterogeneous traffic flow, including the four types of drivers. The stability criterion of the heterogeneous traffic flow is derived, which shows that the proportions of the four types of drivers and their stability functions only relating to model parameters are two critical factors to affect the stability. Numerical simulations are also conducted to verify the derived stability condition and further explore the influences of the driver characteristics on the heterogeneous traffic flow. The simulations reveal that the IS-IC drivers are always the most unstable drivers, the S-C drivers are always the most stable drivers, and the stability effects of the IS-C and the S-IC drivers depend on the stationary velocity. The simulations also indicate that a wider extent of the driver heterogeneity can attenuate the traffic wave.

Study of the Response of PW Traffic Flow Model to a Bottleneck on a Circular Road and its Suitability for Heterogeneous Traffic Conditions

2021 ◽  
Vol 9 (4) ◽  
pp. 460-463
Keyword(s):  
Fluid Flow ◽  
Traffic Flow ◽  
Flow Model ◽  
Equation Model ◽  
Heterogeneous Traffic ◽  
Flow Conditions ◽  
Flow Models ◽  
Traffic Conditions ◽  
Model Response ◽  
Traffic Flow Models

The traffic flow conditions in developing countries are predominantly heterogeneous. The early developed traffic flow models have been derived from fluid flow to capture the behavior of the traffic. The very first two-equation model derived from fluid flow is known as the Payne-Whitham or PW Model. Along with the traffic flow, this model also captures the traffic acceleration. However, the PW model adopts a constant driver behavior which cannot be ignored, especially in the situation of heterogeneous traffic.This research focuses on testing the PW model and its suitability for heterogeneous traffic conditions by observing the model response to a bottleneck on a circular road. The PW model is mathematically approximated using the Roe Decomposition and then the performance of the model is observed using simulations.

Analysis of energy consumption and emission of the heterogeneous traffic flow consisting of traditional vehicles and electric vehicles

2017 ◽  
Vol 31 (34) ◽  
pp. 1750324 ◽  
Author(s):  
Hong Xiao ◽  
Hai-Jun Huang ◽  
Tie-Qiao Tang
Keyword(s):  
Energy Consumption ◽  
Fuel Consumption ◽  
Electric Vehicle ◽  
Traffic Flow ◽  
Small Perturbation ◽  
Electric Vehicles ◽  
Electricity Consumption ◽  
Heterogeneous Traffic ◽  
Rarefaction Waves ◽  
Fuel Consumption And Emissions

Electric vehicle (EV) has become a potential traffic tool, which has attracted researchers to explore various traffic phenomena caused by EV (e.g. congestion, electricity consumption, etc.). In this paper, we study the energy consumption (including the fuel consumption and the electricity consumption) and emissions of heterogeneous traffic flow (that consists of the traditional vehicle (TV) and EV) under three traffic situations (i.e. uniform flow, shock and rarefaction waves, and a small perturbation) from the perspective of macro traffic flow. The numerical results show that the proportion of electric vehicular flow has great effects on the TV’s fuel consumption and emissions and the EV’s electricity consumption, i.e. the fuel consumption and emissions decrease while the electricity consumption increases with the increase of the proportion of electric vehicular flow. The results can help us better understand the energy consumption and emissions of the heterogeneous traffic flow consisting of TV and EV.

Heterogeneous traffic flow model under connected vehicles environment considering cyberattacks

2021 ◽  
Author(s):  
Lizhen Lin ◽  
Hongxia Ge ◽  
Rongjun Cheng
Keyword(s):  
Traffic Flow ◽  
Road Traffic ◽  
Heterogeneous Traffic ◽  
Connected Vehicles ◽  
Vehicle To Vehicle ◽  
Car Following Model ◽  
Time Extension ◽  
Potential Impact ◽  
The Stability ◽  
Traffic Behavior

Under the Vehicle-to-Vehicle (V2V) environment, connected vehicles (CVs) can share the traveling information with each other to keep the traffic flow stable. However, the open network cooperation environment makes CVs vulnerable to cyberattacks, which leads to changes in driving behavior. The existing theories divide cyberattacks into three types: bogus information, replay/delay and collusion cyberattacks. In addition, the mixed flow consisting of truck and car is a common form of road traffic. In order to clarify the potential impact of cyberattacks on mixed traffic flow, this paper proposes an extended car-following model considering cyberattacks under CVs environment. Subsequently, the stability of the model is analyzed theoretically, and the stability condition of the model is obtained. The numerical simulation is carried out and the result shows that the cyberattacks lead to different degrees of traffic behavior hazards such as queue time extension, congestion and even rear end collision. Among them, cooperative attack is the most serious.

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