Motor Vehicle Emission Modeling and Software Simulation Computing for Roundabout in Urban City

In urban road traffic systems, roundabout is considered as one of the core traffic bottlenecks, which are also a core impact of vehicle emission and city environment. In this paper, we proposed a transport control and management method for solving traffic jam and reducing emission in roundabout. The platform of motor vehicle testing system and VSP-based emission model was established firstly. By using the topology chart of the roundabout and microsimulation software, we calculated the instantaneous emission rates of different vehicle and total vehicle emissions. We argued that Integration-Model, combing traffic simulation and vehicle emission, can be performed to calculate the instantaneous emission rates of different vehicle and total vehicle emissions at the roundabout. By contrasting the exhaust emissions result between no signal control and signal control in this area at the rush hour, it draws a conclusion that setting the optimizing signal control can effectively reduce the regional vehicle emission. The proposed approach has been submitted to a simulation and experiment that involved an environmental assessment in Satellite Square, a roundabout in medium city located in China. It has been verified that setting signal control with knowledge engineering and Integration-Model is a practical way for solving the traffic jams and environmental pollution.

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A Model Tree-Based Vehicle Emission Model at Freeway Toll Plazas

Sustainability ◽

10.3390/su12218959 ◽

2020 ◽

Vol 12 (21) ◽

pp. 8959

Author(s):

Yueru Xu ◽

Chao Wang ◽

Yuan Zheng ◽

Zhuoqun Sun ◽

Zhirui Ye

Keyword(s):

Vehicle Emissions ◽

Polynomial Regression ◽

Mean Squared Error ◽

Percentage Error ◽

Vehicle Emission ◽

Emission Model ◽

Toll Plazas ◽

Model Tree ◽

Proposed Model ◽

Toll Collection

With the increased concern over sustainable development, many efforts have been made to alleviate air quality deterioration. Freeway toll plazas can cause serious pollution, due to the increased emissions caused by stop-and-go operations. Different toll collections and different fuel types obviously influence the vehicle emissions at freeway toll plazas. Therefore, this paper proposes a model tree-based vehicle emission model by considering these factors. On-road emissions data and vehicle operation data were obtained from two different freeway toll plazas. The statistical analysis indicates that different methods of toll collection and fuel types have significant impacts on vehicle emissions at freeway toll plazas. The performance of the proposed model was compared with a polynomial regression method. Based on the results, the mean absolute percentage error (MAPE), root mean squared error (RMSE), and mean absolute error (MAE) of the proposed model were all smaller, while the R-squared value increased from 0.714 to 0.833. Finally, the variations of vehicle emissions at different locations of freeway toll plazas were calculated and shown in heat maps. The results of this study can help better estimate the vehicle emissions and give advice to the development of electronic toll collection (ETC) lanes and relevant policies at freeway toll plazas.

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Minimizing Cost of Highway Maintenance Considering the Impact of Vehicle Emissions using an Artificial Bee Colony Approach

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120917667 ◽

2020 ◽

Vol 2674 (6) ◽

pp. 60-72

Author(s):

Celina Semaan ◽

Steven Chien ◽

Ching-Jung Ting

Keyword(s):

Vehicle Emissions ◽

Artificial Bee Colony ◽

Motor Vehicle ◽

Well Being ◽

Work Zone ◽

Emission Rates ◽

Traffic Demand ◽

Abc Algorithm ◽

Bee Colony ◽

The Impact

The increasing traffic demand has reduced the efficiency of road networks and intensified the maintenance need for mobility and safety, increasing vehicle emissions, reducing air quality, and affecting climate change. To mitigate the negative impacts of work zone activities, a reliable method that can optimize spatio-temporal work zone activities is desirable. Previous studies have aimed to minimize the total cost, including maintenance, user delay, and accident costs, yet the associated environmental impact has been neglected. This study aims to optimize work zone activities using the artificial bee colony (ABC) algorithm, considering the cost of vehicle emissions in addition to the aforementioned costs for an environmentally sustainable optimization. MOtor Vehicle Emission Simulator (MOVES) is applied to calculate emission rates. The results show that the ABC algorithm is very efficient to search for the optimal solution that yields the minimum cost taking into account the well-being of the environment.

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Impact of California Reformulated Gasoline on Motor Vehicle Emissions. 1. Mass Emission Rates

Environmental Science & Technology ◽

10.1021/es9803714 ◽

1999 ◽

Vol 33 (2) ◽

pp. 318-328 ◽

Cited By ~ 61

Author(s):

Thomas W. Kirchstetter ◽

Brett C. Singer ◽

Robert A. Harley ◽

Gary R. Kendall ◽

Michael Traverse

Keyword(s):

Vehicle Emissions ◽

Motor Vehicle ◽

Emission Rates ◽

Motor Vehicle Emissions ◽

Reformulated Gasoline

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Fusion of Vehicle Weight and Activity Data for Improved Vehicle Emission Modeling

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2503-17 ◽

2015 ◽

Vol 2503 (1) ◽

pp. 153-162 ◽

Cited By ~ 1

Author(s):

Kanok Boriboonsomsin ◽

Guoyuan Wu ◽

Peng Hao ◽

Matthew Barth

Keyword(s):

Los Angeles ◽

Vehicle Emissions ◽

Motor Vehicle ◽

Operating Mode ◽

Vehicle Emission ◽

Average Weight ◽

Activity Data ◽

Vehicle Weight ◽

Weight Data

Vehicle weight is one of several factors that affect vehicle emissions. Vehicle weight is especially important when modeling emissions from heavy-duty trucks (HDTs). The motor vehicle emission simulator (MOVES) model provides a way to account for vehicle weight during the construction of vehicle emissions inventories. To date, vehicle weight has not received much attention, although reliable vehicle weight data have become increasingly available in the past several years with the deployment of weigh-in-motion (WIM) technology. This study developed a method for fusing vehicle weight data from WIM stations and traffic data from vehicle detector stations (VDS) to obtain HDT activity data for input in MOVES as vehicle operating mode distributions. The study identified trucks recorded by a WIM station that were likely to travel over a VDS during a specified time period. The measured weight data of the trucks were fused with the second-by-second speed and acceleration values in truck trajectories that were created based on the knowledge of truck traffic speed at the VDS. The study used freeways in Los Angeles County, California, as a case study. The case study showed that the distributions of vehicle operating mode were quite different between the proposed method and the existing method, which assumed an average weight value for all HDTs in the same class. In the example case illustrated in this paper, the proposed method resulted in 78% higher nitrogen oxide emissions and 30% higher particulate matter emissions than the existing method.

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Development of Local Emissions Rate Model for Light-Duty Gasoline Vehicles: Beijing Field Data and Patterns of Emissions Rates in EPA Simulator

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2627-08 ◽

2017 ◽

Vol 2627 (1) ◽

pp. 67-76 ◽

Cited By ~ 10

Author(s):

Chenxu Li ◽

Lei Yu ◽

Weinan He ◽

Ying Cheng ◽

Guohua Song

Keyword(s):

Field Data ◽

Motor Vehicle ◽

Vehicle Emission ◽

Emission Model ◽

Regular Pattern ◽

Activity Data ◽

Light Duty ◽

Gasoline Vehicles ◽

Er Model ◽

Local Emissions

A local emissions rate (ER) model is an important tool that is often combined with vehicle activity data in assessing the effect of traffic control strategies on emissions. Such a model is especially critical in developing countries where local emissions data are either unavailable or limited. This study sought to develop a local ER model for light-duty gasoline vehicles (LDGVs) based on limited emissions testing data from Beijing, emissions factors in the China vehicle emission model, and the regular patterns of ERs in the Motor Vehicle Emission Simulator (MOVES) program. To this end, the research team first analyzed the characteristics of vehicle emissions on the basis of field data collected in Beijing. Then the authors summarized the regular pattern of ERs for LDGVs embedded in the MOVES model and examined consistency of normalized ERs derived from Beijing and the MOVES program. The normalized mean square error was used to evaluate the level of consistency. When consistency was sufficiently high, the regular pattern of ERs in the MOVES program was used to fill the missing field emissions data. Development of the model involved four essential elements: ( a) data-driven ERs, ( b) a supplement for high-power operating modes, ( c) modeling ERs of zero-mile-level emissions, and ( d) development of a deterioration model of ERs. On the basis of the proposed model, a local database of ERs for LDGVs was established and applied to assess the emissions benefit of electronic toll collection lanes.

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Estimasi Beban Pencemar Dari Emisi Kendaraan Bermotor di Ruas Jalan Kota Pekanbaru

Dinamika Lingkungan Indonesia ◽

10.31258/dli.1.2.p.71-79 ◽

2014 ◽

Vol 1 (2) ◽

pp. 71

Author(s):

Nurhadi Hodijah ◽

Bintal Amin ◽

Mubarak Mubarak

Keyword(s):

Air Quality ◽

Vehicle Emissions ◽

Motor Vehicle ◽

Ambient Air ◽

Motor Vehicles ◽

Vehicle Emission ◽

Pollutant Load ◽

Diesel Vehicles ◽

Motor Vehicle Emissions ◽

Pm 10

Increasing population and economy in Pekanbaru City was clearly followed by anincrease in the number of motor vehicles has the potential to cause air pollution andendanger human health. This research was aimed to analyze the pollutant load gases of CO,HC, NO 2 , SO 2 and PM 10 emissions from motor vehicles at at Pekanbaru City. Survey on thevolume of motor vehicles, roadside air quality and vehicle emission test was conducted onthree different road in Pekanbaru city. The volume of motor vehicles and pollutants loadsfrom motor vehicle emissions was highest at Sudirman road and the lowest at Diponegororoad. There are very significant differences between Sudirman road with Diponegoro roadand Tuanku Tambusai road with Diponegoro road. Higher pollutant load was found for gasCO (76,4 %), than gas HC (19,4 %), gas NO 2 (3,6 %), gas SO 2 (0,1 % ) and PM 10 ( 0,7 % ).The largest contribution of pollutant load gas CO, HC and PM 10 comes from motorcycles, gasNO 2 from the city cars and gas SO 2 coming from the truck. The quality of roadside air in thethird road to the gases CO, NO 2 , SO 2 and PM 10 are still below the ambient air qualitystandards, whilest gas HC had passed the ambient air quality standard. A positive correlationbetween concentrations of roadside air pollutants with a load of motor vehicle emissions wasfound. The percentage of motor vehicle emission test results explain that the rates of vehiclesfueled with gasoline were higher than diesel vehicles and that do not pass of the emission testwere generally produced before 2007, while for diesel vehicles that do not pass the emissionstest opacity value that were produced in the 2010 onward.

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Dynamic noise mapping of road traffic in an urban city

Arabian Journal of Geosciences ◽

10.1007/s12517-020-06373-9 ◽

2021 ◽

Vol 14 (2) ◽

Author(s):

Rajeev Kumar Mishra ◽

Kartik Nair ◽

Kranti Kumar ◽

Ankita Shukla

Keyword(s):

Road Traffic ◽

Noise Mapping ◽

Dynamic Noise ◽

Urban City

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COVID Lockdowns, Social Distancing, and Fatal Car Crashes: More Deaths on Hobbesian Highways?

Cambridge Journal of Evidence-Based Policing ◽

10.1007/s41887-020-00059-8 ◽

2020 ◽

Vol 4 (3-4) ◽

pp. 238-259 ◽

Cited By ~ 2

Author(s):

Marshall W. Meyer

Keyword(s):

World War Ii ◽

Traffic Safety ◽

Motor Vehicle ◽

Road Traffic ◽

Research Question ◽

Traffic Volume ◽

Similar Data ◽

World War ◽

Social Distancing ◽

The Usa

Abstract Research Question What happened to US traffic safety during the first US COVID-19 lockdown, and why was the pattern the opposite of that observed in previous sudden declines of traffic volume? Data National and local statistics on US traffic volume, traffic fatalities, injury accidents, speeding violations, running of stop signs, and other indicators of vehicular driving behavior, both in 2020 and in previous US economic recessions affecting the volume of road traffic. Methods Comparative analysis of the similarities and differences between the data for the COVID-19 lockdown in parts of the USA in March 2020 and similar data for the 2008–2009 global economic crisis, as well as other US cases of major reductions in traffic volume. Findings The volume of traffic contracted sharply once a COVID-19 national emergency was declared and most states issued stay-at-home orders, but motor vehicle fatality rates, injury accidents, and speeding violations went up, and remained elevated even as traffic began returning toward normal. This pattern does not fit post-World War II recessions where fatality rates declined with the volume of traffic nor does the 2020 pattern match the pattern during World War II when traffic dropped substantially with little change in motor vehicle fatality rates. Conclusions The findings are consistent with a theory of social distancing on highways undermining compliance with social norms, a social cost of COVID which, if not corrected, poses potential long-term increases in non-compliance and dangerous driving.

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Quantifying Air Pollutant Variations during COVID-19 Lockdown in a Capital City in Northwest China

Atmosphere ◽

10.3390/atmos12060788 ◽

2021 ◽

Vol 12 (6) ◽

pp. 788

Author(s):

Rong Feng ◽

Hongmei Xu ◽

Zexuan Wang ◽

Yunxuan Gu ◽

Zhe Liu ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Rural Areas ◽

Vehicle Emissions ◽

Motor Vehicle ◽

Northwest China ◽

Air Pollutant ◽

Capital City ◽

Air Pollution Control ◽

Motor Vehicle Emissions

In the context of the outbreak of coronavirus disease 2019 (COVID-19), strict lockdown policies were implemented to control nonessential human activities in Xi’an, northwest China, which greatly limited the spread of the pandemic and affected air quality. Compared with pre-lockdown, the air quality index and concentrations of PM2.5, PM10, SO2, and CO during the lockdown reduced, but the reductions were not very significant. NO2 levels exhibited the largest decrease (52%) during lockdown, owing to the remarkable decreased motor vehicle emissions. The highest K+ and lowest Ca2+ concentrations in PM2.5 samples could be attributed to the increase in household biomass fuel consumption in suburbs and rural areas around Xi’an and the decrease in human physical activities in Xi’an (e.g., human travel, vehicle emissions, construction activities), respectively, during the lockdown period. Secondary chemical reactions in the atmosphere increased in the lockdown period, as evidenced by the increased O3 level (increased by 160%) and OC/EC ratios in PM2.5 (increased by 26%), compared with pre-lockdown levels. The results, based on a natural experiment in this study, can be used as a reference for studying the formation and source of air pollution in Xi’an and provide evidence for establishing future long-term air pollution control policies.

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