Research on Energy Consumption of Multi-Trains Tracking Traffic Flow Dynamics Model Under Moving Block

Many cellular automaton models (CA models) have been applied to analyze traffic flow. When analyzing multilane traffic flow, it is important how we define lane-changing rules. However, conventional models have used simple lane-changing rules that are dependent only on the distance from neighboring vehicles. We propose a new lane-changing rule considering velocity differences with neighboring vehicles; in addition, we embed the rules into a variant of the Nagel–Schreckenberg (NaSch) model, called the S-NFS model, by considering an open boundary condition. Using numerical simulations, we clarify the basic characteristics resulting from different assumptions with respect to lane changing.

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Enhancing Freeway Safety through Intervening in Traffic Flow Dynamics Based on Variable Speed Limit Control

Journal of Advanced Transportation ◽

10.1155/2018/3610541 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Jinming You ◽

Shouen Fang ◽

Lanfang Zhang ◽

John Taplin ◽

Jingqiu Guo

Keyword(s):

Real Time ◽

Traffic Flow ◽

New Technologies ◽

Flow Dynamics ◽

Crash Risk ◽

Speed Limit ◽

Variable Speed ◽

Variable Speed Limit ◽

Traffic Conditions ◽

Safety Research

New technologies and traffic data sources provide great potential to extend advanced strategies in freeway safety research. The High Definition Monitoring System (HDMS) data contribute comprehensive and precise individual vehicle information. This paper proposes an innovative Variable Speed Limit (VSL) based approach to manage crash risks by intervening in traffic flow dynamics on freeways using HDMS data. We first conducted an empirical analysis on real-time crash risk estimation using a binary logistic regression model. Then, intensive microscopic simulations based on AIMSUN were carried out to explore the effects of various intervention strategies with respect to a 3-lane freeway stretch in China. Different speed limits with distinct compliance rates under specified traffic conditions have been simulated. By taking into account the trade-off between safety benefits and delay in travel time, the speed limit strategies were optimized under various traffic conditions and the model with gradient feedback produces more satisfactory performance in controlling real-time crash risks. Last, the results were integrated into lane management strategies. This research can provide new ideas and methods to reveal the freeway crash risk evolution and active traffic management.

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

Modern Physics Letters B ◽

10.1142/s0217984917503249 ◽

2017 ◽

Vol 31 (34) ◽

pp. 1750324 ◽

Cited By ~ 2

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.

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Analysis of energy consumption and traffic flow by means of track occupation data

IET Conference on Railway Traction Systems (RTS 2010) ◽

10.1049/ic.2010.0022 ◽

2010 ◽

Cited By ~ 1

Author(s):

T. Albrecht ◽

C. Gassel ◽

J. Knijff ◽

J. van Luipen

Keyword(s):

Energy Consumption ◽

Traffic Flow

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The Influence of the Characteristics of the Traffic Flow and the Structure of Vehicles on the Energy Consumption and Ecological Safety of Passenger Transportation : case of Vologda, Russia

10.1109/tirved53476.2021.9639202 ◽

2021 ◽

Author(s):

M. Yu. Karelina ◽

P. I. Smirnov ◽

B. S. Subbotin

Keyword(s):

Energy Consumption ◽

Traffic Flow ◽

Ecological Safety ◽

Passenger Transportation

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A Crash Surrogate Metric considering Traffic Flow Dynamics in a Motorway Corridor

Journal of Advanced Transportation ◽

10.1155/2018/9349418 ◽

2018 ◽

Vol 2018 ◽

pp. 1-7

Author(s):

Xu Wang ◽

Kai Liu

Keyword(s):

Traffic Flow ◽

Risk Index ◽

Simple Calculation ◽

Flow Dynamics ◽

Crash Data ◽

Time To Collision ◽

Crash Rates ◽

Crash Surrogate ◽

Surrogate Measures ◽

Levels Of Service

We proposed a new crash surrogate metric, i.e., the maximum disturbance that a car following scenario can accommodate, to represent potential crash risks with a simple closed form. The metric is developed in consideration of traffic flow dynamics. Then, we compared its performance in predicting the rear-end crash risks for motorway on-ramps with other two surrogate measures (time to collision and aggregated crash index). To this end, a one-lane on-ramp of Pacific Motorway, Australia, was selected for this case study. Due to the lack of crash data on the study site, historical crash counts were merged according to levels of service (LOS) and then converted into crash rates. In this study, we used the societal risk index to represent the crash surrogate indicators and built relationships with crash rates. The final results show that (1) the proposed metric and aggregated crash index are superior to the time to collision in predicting the rear-end crash risks for on-ramps; (2) they have a relatively similar performance, but due to the simple calculation, the proposed metric is more applicable to some real-world cases compared with the aggregated crash index.

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Learning Traffic Flow Dynamics Using Random Fields

IEEE Access ◽

10.1109/access.2019.2941088 ◽

2019 ◽

Vol 7 ◽

pp. 130566-130577 ◽

Cited By ~ 5

Author(s):

Saif Eddin G. Jabari ◽

Deepthi Mary Dilip ◽

Dianchao Lin ◽

Bilal Thonnam Thodi

Keyword(s):

Traffic Flow ◽

Random Fields ◽

Flow Dynamics

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Analysis and Prediction of the Tertiary Industry in Beijing of China Based on System Dynamics Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.522-524.117 ◽

2014 ◽

Vol 522-524 ◽

pp. 117-121

Author(s):

Li Yun Yang ◽

Ying He

Keyword(s):

Energy Consumption ◽

System Dynamics ◽

Energy Saving ◽

Rapid Development ◽

System Dynamics Model ◽

Dynamics Model ◽

Total Consumption ◽

Tertiary Industry

The tertiary industry in Beijing has won rapid development. In 2010, GDP proportion of the tertiary industry has reached 75%, while the energy consumption of the tertiary industry accounted for 55.4% of the total consumption in Beijing. With the economy development of Beijing, the GDP proportion of the tertiary industry will increase further, thus, the energy saving of the tertiary industry is rather imperative. Based on the corresponding data of economy and energy consumption of Beijing from 2005 to 2010, in this study the system dynamics model was proposed to analyze and predict the energy consumption of the tertiary industry of Beijing in 2015.

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