Correlation between carbon emissions,fuel consumption of vehicles and speed limit on expressway

This paper aimed to investigate the correlation between carbon emissions,fuel consumption,and speed limit.A theoretical model was derived based on the energy conservation law,which expresses the relationship between vehicle's fuel consumption and speed.Subsequently,a total of 40 sets of fuel consumption data were collected through field tests to verify the accuracy of the theoretical model at different speeds and different road longitudinal slope combinations.The fuel consumption was then converted to carbon emissions according to the carbon emission factors specified by Intergovernmental Panel on Climate Change(IPCC).In the field experiment,two types of cars and trucks,which are most common on the expressways in China,were selected.Finally,the travel speed under different posted speed limits was obtained through the previously established model,and the carbon emission changes of different vehicle types at different limited speeds are calculated.The results show that the speed limit has a significant impact on fuel consumption and carbon emissions.When the speed limit increased from 80 to 120 km/h,average vehicle speeds increased about 21%-27%,and fuel consumption and carbon emissions increased from approximately 33%-38%.Another interesting result was that the vehicle's fuel consumption and carbon emissions are only affected by speed.The results of the study explore the effect of speed limits on carbon emissions and provide evidence for road managers to set reasonable speed limits.

Predicting vehicle fuel consumption patterns using floating vehicle data

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used.The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers＇ information and vehicles＇ parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively.The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model.

Distributed receding horizon control for fuel-efficient and safe vehicle platooning

This paper investigates the problem of fuel-efficient and safe control of autonomous vehicle platoons. We present a two-part hierarchical control method that can guarantee platoon stability with minimal fuel consumption. The first part vehicle controller is derived in the context of receding horizon optimal control by constructing and solving an optimization problem of overall fuel consumption. The Second part platoon controller is a complementation of the first part, which is given on the basis of platoon stability analysis. The effectiveness of the presented platoon control method is demonstrated by both numerical simulations and experiments with laboratory-scale Arduino cars.

Predicting effects of tunnel throttling of annular freeway vehicular flow by a continuum model

Fluid flow throttling is common in industrial and building services engineering.Similar tunnel throttling of vehicular flow is caused by the abrupt number reduction of roadway lane,as the tunnel has a lower lane number than in the roadway normal segment.To predict the effects of tunnel throttling of annular freeway vehicular flow,a three-lane continuum model is developed.LaneⅢof the tunnel is completely blocked due to the need of tunnel rehabilitation,etc.There exists mandatory net lane-changing rate from laneⅢto laneⅡjust upstream of the tunnel entrance,which is described by a model of random number generated through a golden section analysis.The net-changing rate between adjacent lanes is modeled using a lane-changing time expressed explicitly in algebraic form.This paper assumes that the annular freeway has a total length of 100 km,a two-lane tunnel of length 2 km with a speed limit of 80 km/h.The free flow speeds on lanesⅠ,ⅡandⅢare assumed to be 110,100 and 90 km/h respectively.Based on the three-lane continuum model,numerical simulations of vehicular flows on the annular freeway with such a tunnel are conducted with a reliable numerical method of 3rd-order accuracy.Numerical results reveal that the vehicular flow has a smaller threshold of traffic jam formation in comparison with the case without tunnel throttling.Vehicle fuel consumption can be estimated by interpolation with time averaged grid traffic speed and an assumed curve of vehicle performance.The vehicle fuel consumption is lane number dependent,distributes with initial density concavely,ranging from 5.56 to 8.00 L.Tunnel throttling leads to an earlier traffic jam formation in comparison with the case without tunnel throttling.