Study on Vehicle Cumulative Energy Consumption of Signalized Intersections

Huang, Wenjuan; Rong-guo, MA; Ding, Heng; Bai, Huiyu

doi:10.1061/9780784413623.283

Cited by 6 publications

(4 citation statements)

References 1 publication

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“…and Xiang et al . discussed the factors affecting vehicle fuel consumption, analyzed the vehicle running characteristics and proposed fuel consumption models at pre-time signalized intersections [ 18 , 19 ]. Feng et al .…”

Section: Introductionmentioning

confidence: 99%

The Influence of Intersections on Fuel Consumption in Urban Arterial Road Traffic: A Single Vehicle Test in Harbin, China

Chu

et al. 2015

PLoS ONE

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The calculating method for fuel consumption (FC) was put forward and calibrated and the characteristics of the fuel consumption on intersections were analyzed based on 18 groups of vehicular operating data which were acquired from the test experiment of a single vehicle along the urban arterial roads in Harbin, China. The results obtained show that 50.36% of the fuel consumption for the test vehicle was used at the area of intersections compared with 28.9% of the influencing distance and 68.5% of the running time; and 78.4% of them was burnt at the stages of acceleration and idling. Meanwhile, the type (c) of the vehicular operating status was illustrated to be the worst way of reducing fuel consumption, the causes were analyzed and four improvement strategies were put forward.

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Section: Introductionmentioning

confidence: 99%

The Influence of Intersections on Fuel Consumption in Urban Arterial Road Traffic: A Single Vehicle Test in Harbin, China

Chu

et al. 2015

PLoS ONE

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“…They found that the traffic mobility was enhanced but improvement in traffic emissions was less evident. Huang et al [31] studied the relationship between fuel consumption, number of vehicles arriving, and signal control parameters at intersections. However, in this study, they used the following assumptions: fixed signal timings, vehicles had the same speed, and the vehicles' left rate was constant.…”

Section: Introductionmentioning

confidence: 99%

Cellular Automata Model for Analysis and Optimization of Traffic Emission at Signalized Intersection

et al. 2022

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Traffic emission is one of the most severe issues in our modern societies. A large part of emissions occurs in cities and especially at intersections due to the high interactions between vehicles. In this paper, we proposed a cellular automata model to investigate the different traffic emissions (CO2, PM, VOC, and NOx) and speeds at a two-lane signalized intersection. The model is designed to analyze the effects of signalization by isolating the parameters involved in vehicle-vehicle interactions (lane changing, speed, density, and traffic heterogeneity). It was found that the traffic emission increases (decreases) with the increasing of green lights duration (Tg) at low (high) values of vehicles injection rate (α). Moreover, by taking CO2 as the order parameter, the phase diagram shows that the system can be in four different phases (I, II, III, and IV) depending on α and Tg. The transition from phase II (I) to phase III (II) is second order, while the transition from phase II to phase IV is first order. To reduce the traffic emission and enhance the speed, two strategies were proposed. Simulation results show a maximum reduction of 13.6% in vehicles’ emissions and an increase of 9.5% in the mean speed when adopting self-organizing intersection (second strategy) at low and intermediate α. However, the first strategy enhances the mean speed up to 28.8% and reduces the traffic emissions by 3.6% at high α. Therefore, the combination of both strategies is recommended to promote the traffic efficiency in all traffic states. Finally, the model results illustrate that the system shows low traffic emission adopting symmetric lane-changing rules than asymmetric rules.

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“…To date, series of studies on vehicle energy consumption and emissions at signalized intersections have been performed by several research groups; authors such as Liao and Machemehl [1], Liao [2], Huang et al [3], Zhang et al [4] and Li et al [5] have put forward different mathematical estimation models. However, although these results have analyzed and estimated the CO 2 emissions of vehicles at signalized intersections, they were all obtained under specific assumptions, such as the acceleration and deceleration of vehicles in the processes of acceleration and deceleration at intersections remaining unchanged, respectively, or the fuel consumption and emissions characteristics of vehicles in the process of driving being characterized by equivalent fuel consumption and emission rates; these overideal assumptions limit the applicability.…”

Section: Introductionmentioning

confidence: 99%

“…Although these works combined VISSIM traffic simulation software with different fuel consumption and emissions models to study vehicle fuel consumption and emissions at signalized intersections, their research overcame the limitations in the hypotheses of the works of Liao and Machemehl [1], Liao [2], Huang et al [3], Zhang et al [4] and Li et al [5] that were too ideal. However, the combination of VISSIM simulation software and fuel consumption and emissions models is complex and requires a large amount of data processing, resulting in some limitations of research on the fuel consumption and emissions of traffic flow at signalized intersections based on the combination of VISS IM and vehicle fuel consumption and emission models.…”

Section: Introductionmentioning

confidence: 99%

Modeling of vehicle CO2 emissions and signal timing analysis at a signalized intersection considering fuel vehicles and electric vehicles

Zhao

Yin

2021

Eur. Transp. Res. Rev.

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Background An intersection is an area with more energy consumption and emissions by motor vehicles, and the energy consumption and emissionsof vehicles at intersections should be reduced in road planning and traffic control to improve the urban traffic environment. Objectives In order to analyze the influence of signal timing on CO2 emission of traffic flow under the mixed traffic environment of fuel vehicles and electric vehicles. Methods A set of CO2 incremental emission models is established to estimate the CO2 emissions of fuel vehicles and electric vehicles at signalized intersections. Then, a signal timing model with minimum CO2 emissions is established, and the influence of signal timing with minimum CO2 emissions on vehicle control delay and stop rates under different traffic conditions is analyzed. Conclusions The case study shows that optimizing of the timing parameters of intersections from the perspective of vehicle CO2 emissions is different from the perspective of control delay or stop rate; the model’s timing optimization will effectively balance the CO2 emissions generated by vehicles during the acceleration, deceleration and idling stages, essentially achieving a comprehensive consideration of vehicle control delay and stop rates. When the road section speed and the mixed proportion of electric vehicles are low, the timing results tend to reduce the vehicle delay at intersections, but when the road section speed and the mixed proportion of electric vehicles are high, the timing results tend to reduce the vehicle stop rate.

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Study on Vehicle Cumulative Energy Consumption of Signalized Intersections

Cited by 6 publications

References 1 publication

The Influence of Intersections on Fuel Consumption in Urban Arterial Road Traffic: A Single Vehicle Test in Harbin, China

The Influence of Intersections on Fuel Consumption in Urban Arterial Road Traffic: A Single Vehicle Test in Harbin, China

Cellular Automata Model for Analysis and Optimization of Traffic Emission at Signalized Intersection

Modeling of vehicle CO2 emissions and signal timing analysis at a signalized intersection considering fuel vehicles and electric vehicles

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