Estimation of Emissions at Signalized Intersections Using an Improved MOVES Model with GPS Data

Lin, Ciyun; Zhou, Xiangyu; Wu, Dayong; Gong, Bowen

doi:10.3390/ijerph16193647

Cited by 17 publications

(9 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The number in bracket stands for the difference in average vehicle delays between different schemes. The arrow indicates an increment or decrement when compared with the current scheme 2. Similar to the former note, the value represents the difference in average capita delay.…”

mentioning

confidence: 88%

“…The units of speed v and acceleration a of the vehicle are defined as km/h and m/s 2 , respectively. 2 The abbreviation for driving conditions of electric and gasoline vehicles stands for acceleration, deceleration, uniformity and idling respectively.…”

Section: Energy Consumption Measurementmentioning

confidence: 99%

“…With the rapid development of the motorization process, environmental problems in the traffic field have become increasingly serious in the past decades, which has brought negative impacts on society and public health [1]. Many study results show that traffic emissions have become an important constituent of pollution emissions [2], which have also become significant factors hindering the sustainable development of cities. Scholars have conducted a lot of research on air and noise pollution prevention and management from a vehicle engineering perspective [3][4][5][6], while less attention has been paid to traffic control and other transport operational aspects when making traffic policy.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluating the Environmental Impact of Bus Signal Priority at Intersections under Hybrid Energy Consumption Conditions

Huan

Yao

Fan³

et al. 2019

Energies

View full text Add to dashboard Cite

The acceleration of the motorization process creates severe environmental problems by affecting the energy consumption of urban traffic. As a major source of traffic pollution, vehicle exhaust deserves more attention when making traffic policy. Actually, the acceleration, deceleration, and idling conditions of vehicles cause more pollution than usual, which mainly happens at intersections of the road network. Besides, in the context of giving priority on public transport development, bus signal priority (BSP) at intersections becomes a quite prevalent measure to reduce average capita delay for travelers, while long-term practice also indicates that the unreasonable setting of bus lane further worsens the running conditions for other vehicles by occupying excessive traffic capacity, which highlights the indirect environmental effects of BSP. This paper provides a simulation-based method for evaluating the adaptability of BSP to find an optimum balance between efficient and environmental care. Specifically, the traffic volume, bus mixed rate of the intersection and energy types of vehicles consist of hybrid energy consumption conditions collectively. A VSP (vehicle specific power)-based exhaust emission models for both buses and other vehicles are employed to estimate the environmental cost of the entire intersection. Moreover, the overall efficiency of gasoline and electric vehicles is further evaluated to offer more implications for traffic control practice.

show abstract

mentioning

confidence: 88%

Section: Energy Consumption Measurementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating the Environmental Impact of Bus Signal Priority at Intersections under Hybrid Energy Consumption Conditions

Huan

Yao

Fan³

et al. 2019

Energies

View full text Add to dashboard Cite

show abstract

“…These data help us to understand human travel behavior better by zooming into individuals' behaviors more closely than ever. Ciyun Lin et al improved the traditional Motor Vehicle Emission Simulator model by adding real-time GPS datasets, and the results showed that the model could effectively improve the estimation accuracy of traffic emissions and provide a strong scientific basis for environmental decision-making, planning, and management [24]. Consequently, various data mining techniques have been proposed to gain insight into travel behavior from trajectory data.…”

Section: The Study Of Travel Behaviormentioning

confidence: 99%

Detecting Pattern Changes in Individual Travel Behavior from Vehicle GPS/GNSS Data

Lou

Cheng

2020

Sensors

View full text Add to dashboard Cite

Although stable in the short term, individual travel behavior generally tends to change over the long term. The ability to detect such changes is important for product and service providers in continuously changing environments. The aim of this paper is to develop a methodology that detects changes in the patterns of individual travel behavior from vehicle global positioning system (GPS)/global navigation satellite system (GNSS) data. For this purpose, we first define individual travel behavior patterns in two dimensions: a spatial pattern and a frequency pattern. Then, we develop a method that can detect such patterns from GPS/GNSS data using a clustering algorithm. Finally, we define three basic pattern-change scenarios for individual travel behavior and introduce a pattern-matching metric for detecting these changes. The proposed methodology is tested using GPS datasets from three randomly selected anonymous users, collected by a Chinese automotive manufacturer. The results show that our methodology can successfully identify significant changes in individual travel behavior patterns.

show abstract

“…Klein [17] devised a pollution calculation approach for vehicle emission in the Netherlands factoring in the number of cargo vehicles active using simulation programs wherein different temperatures are accounted for, and factoring in additional effects by HDVs. Lin [18] study estimation of emissions at signalized intersections using an improved Motor Vehicle Emission Simulator (MOVES) Model with GPS Data is one to begin incorporating GPS data, which helped in producing a more accurate emission estimation than methods that only factor in numbers of vehicles which can better serve as a foundation for further environmental management planning.…”

Section: Carbon Dioxide Emission (Co 2 ) and Road Slope Conditionmentioning

confidence: 99%

The Development of a CO2 Emission Coefficient for Medium- and Heavy-Duty Vehicles with Different Road Slope Conditions Using Multiple Linear Regression, and Considering the Health Effects

2020

View full text Add to dashboard Cite

The current studies on carbon dioxide (CO2) emissions and the impacts on public health focus mainly on evaluating CO2 emissions from two types of emission sources. The first is a fixed source type from industrial plants, which can be controlled or easily evaluated. The second is a mobile source type from the transport sector, especially from medium- and heavy-duty vehicles (MHDVs), which produce high emissions. However, the common methods of evaluation of the average value of CO2 emissions per kilometer of a vehicle use a general Intergovernmental Panel on Climate Change (IPCC) model that does not consider the topography or road conditions. This affects the accuracy of CO2 emission assessments and, in turn, affects the accuracy of any analysis needed to establish health policies and the management of public health within the affected area. In this paper, therefore, we present the development of emission coefficient calculations with varying topography conditions for MHDVs with consideration of the health effects on the populace. The study area was the Asian highway network in Thailand that passes through all regions and is geographically diverse. Data were collected from the Department of Highway’s records, global positioning system (GPS) and electronic control unit (ECU) with data consisting of road data, slope, distance, traffic level and vehicle weight, as well as fuel consumption along the transportation route. To analyze and map out the correlation of the CO2 emission coefficients for each road slope, we determined the coefficient of the CO2 emissions using multiple linear regression analysis and validated this using Huber–White robust standard errors for heteroscedasticity. This method was more cost-efficient and time-efficient compared to the conventional approaches. We also created CO2 emission maps with risk points for health effects, and we propose policy designs and plans to manage the traffic level in each of these areas prone to higher levels of such emissions.

show abstract

Estimation of Emissions at Signalized Intersections Using an Improved MOVES Model with GPS Data

Cited by 17 publications

References 28 publications

Evaluating the Environmental Impact of Bus Signal Priority at Intersections under Hybrid Energy Consumption Conditions

Evaluating the Environmental Impact of Bus Signal Priority at Intersections under Hybrid Energy Consumption Conditions

Detecting Pattern Changes in Individual Travel Behavior from Vehicle GPS/GNSS Data

The Development of a CO2 Emission Coefficient for Medium- and Heavy-Duty Vehicles with Different Road Slope Conditions Using Multiple Linear Regression, and Considering the Health Effects

Contact Info

Product

Resources

About