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.

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.

An improved car-following model considering the impact of safety messages

2018 ◽  
Vol 32 (32) ◽  
pp. 1850398 ◽  
Author(s):  
Tenglong Li ◽  
Fei Hui ◽  
Xiangmo Zhao
Keyword(s):  
Traffic Congestion ◽  
Dominant Factor ◽  
Velocity Difference ◽  
Car Following ◽  
Safety Message ◽  
Warning Messages ◽  
Gray Correlation ◽  
Car Following Model ◽  
The Stability ◽  
The Impact

The existing car-following models of connected vehicles commonly lack experimental data as evidence. In this paper, a Gray correlation analysis is conducted to explore the change in driving behavior with safety messages. The data mining analysis shows that the dominant factor of car-following behavior is headway with no safety message, whereas the velocity difference between the leading and following vehicle becomes the dominant factor when warning messages are received. According to this result, an extended car-following model considering the impact of safety messages (IOSM) is proposed based on the full velocity difference (FVD) model. The stability criterion of this new model is then obtained through a linear stability analysis. Finally, numerical simulations are performed to verify the theoretical analysis results. Both analytical and simulation results show that traffic congestion can be suppressed by safety messages. However, the IOSM model is slightly less stable than the FVD model if the average headway in traffic flow is approximately 14–20 m.

Non-lane-based full velocity difference car following model

2010 ◽  
Vol 389 (21) ◽  
pp. 4654-4662 ◽  
Author(s):  
Sheng Jin ◽  
Dianhai Wang ◽  
Pengfei Tao ◽  
Pingfan Li
Keyword(s):  
Velocity Difference ◽  
Car Following ◽  
Car Following Model ◽  
Lane Based

scholarly journals A Modified Car-following Model Considering Traffic Density and Acceleration of Leading Vehicle

2020 ◽  
Vol 10 (4) ◽  
pp. 1268
Author(s):  
Xudong Cao ◽  
Jianjun Wang ◽  
Chenchen Chen
Keyword(s):  
Traffic Flow ◽  
Linear Stability Theory ◽  
Traffic Density ◽  
Neutral Stability ◽  
Difference Model ◽  
Velocity Difference ◽  
Car Following ◽  
Car Following Model ◽  
The Difference ◽  
Improved Model

Although the difference between the velocity of two successive vehicles is considered in the full velocity difference model (FVDM), more status information from preceding vehicles affecting the behavior of car-following has not been effectively utilized. For improving the performance of the FVDM, an extended modified car-following model taking into account traffic density and the acceleration of a leading vehicle (DAVD, density and acceleration velocity difference model) is presented under the condition of vehicle-to-vehicle (V2V) communications. Stability in the developed model is derived through applying linear stability theory. The curves of neutral stability for the improved model indicate that when the driver pays more attention to the traffic status in front, the traffic flow stability region is larger. Numerical simulation illustrates that traffic flow disturbance could be suppressed by gaining more information on preceding vehicles.

scholarly journals An Extended Car-Following Model at Signalised Intersections

2018 ◽  
Vol 2018 ◽  
pp. 1-26 ◽  
Author(s):  
Hongxing Zhao ◽  
Ruichun He ◽  
Changxi Ma
Keyword(s):  
Velocity Model ◽  
Measured Data ◽  
Velocity Difference ◽  
Optimal Velocity ◽  
Car Following ◽  
Optimal Velocity Model ◽  
Trajectory Simulation ◽  
Car Following Model ◽  
Point Data ◽  
Isolated Point

An extended car-following model is proposed on the basis of experimental analysis to improve the performance of the traditional car-following model and simulate a microscopic car-following behaviour at signalised intersections. The new car-following model considers vehicle gather and dissipation. Firstly, the parameters of optimal velocity, generalised force and full velocity difference models are calibrated by measured data, and the problems and causes of the three models are analysed with a realistic trajectory simulation as an evaluation criterion. Secondly, an extended car-following model based on the full optimal velocity model is proposed by considering the vehicle gather and dissipation. The parameters of the new car-following model are calibrated by the measured data, and the model is compared with comparative models on the basis of isolated point data and the entire car-following process. Simulation results show that the optimal velocity, generalised force, and full velocity difference models cannot effectively simulate a microscopic car-following behaviour at signalised intersections, whereas the new car-following model can avoid a collision and has a high fit degree for simulating the measured data of the car-following behaviour at signalised intersections.

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