Car following model for urban signalised intersection to estimate speed based vehicle exhaust emissions

Urban Climate ◽  
2019 ◽  
Vol 29 ◽  
pp. 100480 ◽  
Author(s):  
Boski P. Chauhan ◽  
G.J. Joshi ◽  
Purnima Parida
Keyword(s):  
Exhaust Emissions ◽  
Vehicle Exhaust ◽  
Car Following ◽  
Car Following Model ◽  
Signalised Intersection

Influences of vehicles’ fuel consumption and exhaust emissions on the trip cost without late arrival under car-following model

2016 ◽  
Vol 27 (01) ◽  
pp. 1650011 ◽  
Author(s):  
Tie-Qiao Tang ◽  
Qiang Yu
Keyword(s):  
Fuel Consumption ◽  
Exhaust Emissions ◽  
Optimal Time ◽  
Fuel Cost ◽  
Total Cost ◽  
Car Following ◽  
Time Headway ◽  
Late Arrival ◽  
Car Following Model ◽  
Open Road

In this paper, we use car-following model to explore the influences of the vehicle’s fuel consumption and exhaust emissions on each commuter’s trip cost without late arrival on one open road. Our results illustrate that considering the vehicle’s fuel cost and emission cost only enhances each commuter’s trip cost and the system’s total cost, but has no prominent impacts on his optimal time headway at the origin of each open road under the minimum total cost.

Vehicle's exhaust emissions under car-following model

2014 ◽  
Vol 25 (06) ◽  
pp. 1450007 ◽  
Author(s):  
Tie-Qiao Tang ◽  
Jin-Gang Li ◽  
Dong Zhang ◽  
Yun-Peng Wang
Keyword(s):  
Exhaust Emissions ◽  
Numerical Results ◽  
Velocity Difference ◽  
Car Following ◽  
Car Following Model

In this paper, we explore each vehicle's exhaust emissions under the full velocity difference (FVD) model and the car-following model with consideration of the traffic interruption probability during three typical traffic situations. Numerical results show that the vehicle's exhaust emissions of the second model are less than those of the first model under the three typical traffic situations, which shows that the second model can reduce each vehicle's exhaust emissions.

Fuel consumptions and exhaust emissions induced by cooperative adaptive cruise control strategies

2015 ◽  
Vol 29 (14) ◽  
pp. 1550084 ◽  
Author(s):  
Shaowei Yu ◽  
Zhongke Shi
Keyword(s):  
Adaptive Cruise Control ◽  
Control Strategies ◽  
Exhaust Emissions ◽  
Cruise Control ◽  
Difference Model ◽  
Velocity Difference ◽  
Car Following ◽  
Road Traffic Safety ◽  
Cooperative Adaptive Cruise Control ◽  
Car Following Model

Many cooperative adaptive cruise control strategies have been presented to improve traffic efficiency as well as road traffic safety, but scholars have rarely explored the impacts of these strategies on cars' fuel consumptions and exhaust emissions. In this paper, we respectively select two-velocity difference model, multiple velocity difference model and the car-following model considering multiple preceding cars' accelerations to investigate each car's fuel consumptions, carbon monoxide (CO), hydrocarbons (HC) and nitrogen oxides ( NO X ) emissions and carry out comparative analysis. The comparisons of fuel consumptions and exhaust emissions in three different cruise control strategies show that cooperative cars simulated by the car-following model considering multiple preceding cars' accelerations can run with the minimal fuel consumptions, CO, HC and NO X emissions, thus, taking the car-following model considering multiple preceding cars' accelerations as the cooperative adaptive cruise control strategy can significantly improve cars' fuel efficiency and exhaust emissions.

scholarly journals Estimation and Analysis of Vehicle Exhaust Emissions at Signalized Intersections Using a Car-Following Model

2019 ◽  
Vol 11 (14) ◽  
pp. 3992 ◽  
Author(s):  
Hongxing Zhao ◽  
Ruichun He ◽  
Xiaoyan Jia
Keyword(s):  
Vehicle Emissions ◽  
Arrival Rate ◽  
Signalized Intersections ◽  
Specific Power ◽  
Nox Emissions ◽  
Emission Model ◽  
Vehicle Exhaust ◽  
Car Following ◽  
Road Section ◽  
Car Following Model

A signalized intersection is a high fuel consumption and high emission node of a traffic network. It is necessary to study the emission characteristics of vehicles at signalized intersections in order to reduce vehicle emissions. In this study, the combination of a car-following model and the vehicle specific power emission model was used to estimate the vehicle emissions, including the CO2, CO, HC, and nitric oxide (NOX) emissions, at unsaturated signalized intersections. The results of simulations show that, under the influence of the signal light, the substantial changes in a vehicle’s trajectory increase the CO2, CO, HC, and NOX emissions. The CO2, CO, HC, and NOX emissions from vehicles at signalized intersections were further analyzed in terms of signal timing, vehicle arrival rate, traffic interference, and road section speed. The results show that an increase in the signal cycle, the vehicle arrival rate, and the traffic interference amplitude result in increases in the CO2, CO, HC, and NOX emissions per vehicle at the intersection inbound approach, and an increase in the green signal ratio and the vehicle road section speed within a specified range has a positive significance for reducing the CO2, CO, HC, and NOX emissions of vehicles in the study range. The proposed method can be flexibly applied to the analysis of vehicle emissions at unsaturated signalized intersections. The obtained results provide a reference for the control and management of signalized intersections.

scholarly journals An Asymmetric-Anticipation Car-following Model in the Era of Autonomous-Connected and Human-Driving Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Ammar Jafaripournimchahi ◽  
Wusheng Hu ◽  
Lu Sun
Keyword(s):  
Energy Consumption ◽  
Traffic Flow ◽  
Exhaust Emissions ◽  
Driving Behavior ◽  
Arrival Process ◽  
Motion Information ◽  
Mixed Traffic ◽  
Car Following ◽  
Mixed Traffic Flow ◽  
Car Following Model

Herein, we explored the impact of anticipation and asymmetric driving behavior on vehicle’s position, velocity, acceleration, energy consumption, and exhaust emissions of CO, HC, and NOx in mixed traffic flow. We present an asymmetric-anticipation car-following model (AAFVD) considering the motion information from two direct preceding vehicles (i.e., human-driving (HD) and autonomous and connected (AC) vehicles platoon) via wireless data transmission. The linear stability approach was used to evaluate the properties of the AAFVD model. Our simulations revealed that the drivers’ anticipation factor using the motion information from two direct preceding vehicles in connected vehicles environment can effectively improve traffic flow stability. The vehicle’s departure and arrival process while passing through a signal lane with a traffic light considering the anticipation and asymmetric driving behavior, and the motion information from two direct preceding vehicles was explored. Our numerical results demonstrated that the AAFVD model can decrease the velocity fluctuations, energy consumption, and exhaust emissions of vehicles in mixed traffic flow system.

scholarly journals Spatiotemporal distribution of light-absorbing carbon and its relationship to other atmospheric pollutants in Stockholm

2011 ◽  
Vol 11 (22) ◽  
pp. 11553-11567 ◽  
Author(s):  
P. Krecl ◽  
A. C. Targino ◽  
C. Johansson
Keyword(s):  
Exhaust Emissions ◽  
Atmospheric Pollutants ◽  
Spatiotemporal Variability ◽  
Rural Site ◽  
Strong Increase ◽  
Population Exposure ◽  
Emission Sources ◽  
Vehicle Exhaust ◽  
Urban Background ◽  
Urban Sites

Abstract. Carbon-containing particles have deleterious effects on both Earth's climate and human health. In Europe, the main sources of light-absorbing carbon (LAC) emissions are the transport (67%) and residential (25%) sectors. Information on the spatiotemporal variability of LAC particles in urban areas is relevant for air quality management and to better diagnose the population exposure to these particles. This study reports on results of an intensive field campaign conducted at four sites (two kerbside stations, one urban background site and a rural station) in Stockholm, Sweden, during the spring 2006. Light-absorbing carbon mass (MLAC) concentrations were measured with custom-built Particle Soot Absorption Photometers (PSAP). The spatiotemporal variability of MLAC concentrations was explored by examining correlation coefficients (R), coefficients of divergence (COD), and diurnal patterns at all sites. Simultaneous measurements of NOx, PM10, PM2.5, and meteorological variables were also carried out at the same locations to help characterize the LAC emission sources. Hourly mean (± standard deviation) MLAC concentrations ranged from 0.36±0.50 at the rural site to 5.39±3.60 μg m−3 at the street canyon site. Concentrations of LAC between urban sites were poorly correlated even for daily averages (R<0.70), combined with highly heterogeneously distributed concentrations (COD>0.30) even at spatial scales of few kilometers. This high variability is connected to the distribution of emission sources and processes contributing to the LAC fraction at these sites. At urban sites, MLAC tracked NOx levels and traffic density well and mean MLAC/PM2.5 ratios were larger (26–38%) than at the background sites (4–10%). The results suggest that vehicle exhaust emissions are the main responsible for the high MLAC concentrations found at the urban locations whereas long-range transport (LRT) episodes of combustion-derived particles can generate a strong increase of levels at background sites. To decrease pollution levels at kerbside and urban background locations in Stockholm, we recommend abatement strategies that target reductions of vehicle exhaust emissions, which are the main contributors to MLAC and NOx concentrations.

scholarly journals String Stability and Platoon Safety Analysis of a New Car-following Model Considering a Stabilization Strategy

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Mingfei Mu ◽  
Junjie Zhang ◽  
Changmiao Wang ◽  
Jun Zhang ◽  
Can Yang
Keyword(s):  
Safety Analysis ◽  
String Stability ◽  
Car Following ◽  
Car Following Model
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