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

2010 ◽  
Author(s):  
T. Albrecht ◽  
C. Gassel ◽  
J. Knijff ◽  
J. van Luipen
Keyword(s):  
Energy Consumption ◽  
Traffic Flow

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.

Effect of Multi-Slowdown Sections on Traffic Flow

2012 ◽  
Vol 253-255 ◽  
pp. 1619-1622
Author(s):  
Yan Hong Fan ◽  
Hua Kuang ◽  
Guo Xin Zhang ◽  
Ling Jiang Kong ◽  
Xing Li Li
Keyword(s):  
Energy Consumption ◽  
Traffic Flow ◽  
Maximum Flow ◽  
Underlying Mechanism ◽  
Speed Limit ◽  
Fundamental Diagram ◽  
Mean Velocity ◽  
Traffic System ◽  
Flow Phase ◽  
Multi Phase

Based on the NS model, an extended cellular automaton model is proposed to simulate complex characteristics and energy consumption of traffic flow with some slowdown sections on a highway by considering the number, speed limit and distribution of slowdown sections. The simulation results show that the present model can exhibit a multi-phase coexistence phenomenon, i.e., the freely moving phase, the maximum flow phase and the jamming phase coexist in traffic system. The fundamental diagram shows that the number of slowdown section has no influence on the mean velocity and flow. However, energy consumption increases with increase of the number of slowdown section at low density. In addition, it can be found that the speed limit and distribution of different slowdown sections have an important effect on traffic flow and energy consumption, and the underlying mechanism is also analyzed.

Dynamic simulation of energy consumption in mixed traffic flow considering highway toll station

2015 ◽  
Vol 29 (02) ◽  
pp. 1450264 ◽  
Author(s):  
Yong-Sheng Qian ◽  
Xiao-Long Zhang ◽  
Jun-Wei Zeng ◽  
Xiao-Ming Shao ◽  
Neng Wang
Keyword(s):  
Energy Consumption ◽  
Traffic Flow ◽  
Peak Velocity ◽  
Mixed Traffic ◽  
Total Energy Consumption ◽  
Mixed Traffic Flow ◽  
Toll Collection ◽  
Improved Model ◽  
Toll Station ◽  
Increasing Functions

An improved model of energy consumption including toll station is presented in this paper. Using the model, we study the influences of mixed ratio, the idling energy consumption of vehicle, vehicle peak velocity, dwell time and random deceleration probability on energy consumption of Electronic Toll Collection or Manual Toll Collection mixed traffic flow on single lane under periodic condition. Simulating results indicate that the above five parameters are all increasing functions of total energy consumption, in which the idling energy consumption represents the major amounts with the increase of mixed ratio and occupancy rate. Thus, the existence of toll station has significant effect on the energy consumption of mixed traffic flow.

Research on Energy Consumption of Two-Lane Traffic Based on Turn Signal Effect

2013 ◽  
Vol 827 ◽  
pp. 412-416
Author(s):  
Rui Kang ◽  
Kai Yang
Keyword(s):  
Energy Consumption ◽  
Numerical Simulations ◽  
Traffic Flow ◽  
Driver Behavior ◽  
Behavior Changes ◽  
Traditional Model ◽  
Lane Change ◽  
Right Of Way ◽  
Ca Model ◽  
The Right

Based on the STCA model, an improved two-lane traffic CA model considering turn signals is proposed. The model designs driver behavior changes because of the effect of turn light of front vehicle,and introduces rules of changing lanes, cutting lanes and yielding the right of way for the rear vehicle. Through computer numerical simulations, this study has presented curve diagrams of relationship between turning rate and energy consumption and also analyzed the effects of driver behavior of the rear vehicles on traffic flow. The results indicate that increased probability of lane change make more turning rate and energy consumption. When probability of lane change is from 0.5 to 1.0, turning rate increases 13.23% and energy consumption increases 22.15% . Compared with the traditional model, STCA model can depict more complex traffic situations and reproduce driver behaviors and more realistic process of traffic.

Nonlinear analysis of an improved continuum model considering headway change with memory

2018 ◽  
Vol 32 (03) ◽  
pp. 1850037 ◽  
Author(s):  
Rongjun Cheng ◽  
Jufeng Wang ◽  
Hongxia Ge ◽  
Zhipeng Li
Keyword(s):  
Energy Consumption ◽  
Nonlinear Analysis ◽  
Traffic Flow ◽  
Linear Stability ◽  
Continuum Model ◽  
Density Wave ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Neutral Stability ◽  
With Memory

Considering the effect of headway changes with memory, an improved continuum model of traffic flow is proposed in this paper. By means of linear stability theory, the new model’s linear stability with the effect of headway changes with memory is obtained. Through nonlinear analysis, the KdV–Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the improved traffic flow model, which explores how the headway changes with memory affected each car’s velocity, density and energy consumption. Numerical results show that when considering the effects of headway changes with memory, the traffic jams can be suppressed efficiently. Furthermore, research results demonstrate that the effect of headway changes with memory can avoid the disadvantage of historical information, which will improve the stability of traffic flow and minimize car energy consumption.

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