Guohua Song

Assessing Effect of Traffic Signal Control Strategies on Vehicle Emissions

Abstract In response to the increased traffic congestion and worsened air pollution, using the portable emission measurement system (PEMS), this paper collects and compares the real world emissions under signal coordination and non-coordination in Beijing, and analyzes the emission levels and distribution characteristics under these two control strategies. Furthermore, by integrating the microscopic traffic simulation model of VISSIM and the VSP-based approach of emission modeling, the paper develops an integrated microscopic simulation platform of traffic emissions, which is finally used to evaluate the impact of two traffic control strategies, alternative signal timing and traffic flow on emissions.

Distribution Characteristics of Vehicle-Specific Power on Urban Restricted-Access Roadways

The development of new fuel consumption and emission models creates the need to characterize traffic conditions by using vehicle-specific power (VSP) distribution. However, in existing transportation engineering, there has been a lack of knowledge of relationships between the VSP distribution and commonly used traffic parameters and a lack of models to develop the VSP distribution from traffic parameters. To examine how traffic conditions affect VSP distributions, this study uses large samples of floating car data collected from expressways in Beijing to associate VSP distributions with various average travel speeds. After a comprehensive analysis, regular patterns are found between the VSP distribution and the average travel speed. Specifically, when the average travel speed is more than 20  km/h, the VSP distribution comes close to a normal distribution. The mean of the VSP distribution is the VSP value when cruising at the average travel speed, and the standard deviation could be expressed as a power f...

Estimation of Fuel Efficiency of Road Traffic by Characterization of Vehicle-Specific Power and Speed Based on Floating Car Data

To evaluate the fuel efficiency of road traffic, an approach that captures the characteristics of road traffic on the basis of floating car data (FCD) is proposed. In existing studies of fuel consumption, parameters such as speed, acceleration, and power demand have been adopted to represent the characteristics of traffic flows and vehicle activities. However, they are not suitable for use in the evaluation of fuel efficiency in a dynamic traffic network with various advanced traffic management alternatives. On the basis of a comprehensive analysis of the data collected by portable emission measurement systems and FCD collected in Beijing, it was found that the time distribution in vehicle-specific power (VSP) bins, that is, the VSP bin distribution, can well represent fuel consumption per unit of time. Furthermore, the combination of the VSP bin distribution and the average travel speed in a network can represent fuel consumption per unit of distance. According to these findings, the paper develops a method for evaluating the fuel efficiency for road traffic on the basis of defined indicators of fuel consumption and fuel consumption at the most efficient speed. A comparison of the estimated indicators and the real values indicates that the proposed approach performs well in evaluating the fuel efficiency of road traffic. This approach was applied to develop the temporal distribution of fuel efficiency for the West 2nd Ring Road in Beijing. Finally, the paper provides recommendations for expansion of this study by including more vehicle types and different rates of penetration of FCD.

Applicability of Traffic Microsimulation Models in Vehicle Emissions Estimates: Case Study of VISSIM

Efforts in estimating emissions by an integration of traffic simulation models and emissions models have become a fast-evolving research area. However, because of the lack of effective methods and indicators to characterize traffic behaviors, the accuracy of emissions by such an approach has not been effectively verified or evaluated. The current study is intended to examine the applicability of traffic microsimulation models in vehicle emissions estimates on the basis of the explanatory parameter of vehicle emissions—the vehicle-specific power (VSP) distribution. Analyzing massive real-world and simulated vehicle activity data showed that the results from traffic simulation could not represent real-world driving behaviors for emissions estimates. The simulated vehicle- specific power distribution led to errors that were as high as 82.8%, 53.6%, and 29.6% for nitrogen oxides, hydrocarbons, and carbon monoxide emissions, respectively. Then a sensitivity analysis of 16 adjustments on eight parameters of simulation models was conducted to determine their effects on simulated VSP distributions: systematic errors existed in the use of traffic simulation models to represent second-by-second driving behaviors. The errors could not be reduced by parameter calibration on the simulation model. This study concluded that the traditional approach of integrating traffic simulation models with emissions models was not applicable for vehicle emissions estimates. The primary reasons for the errors need to be investigated further from the internal mechanism of submodels of microsimulation. On the basis of these findings, several recommendations are proposed for future studies.

Aggregate Fuel Consumption Model of Light-Duty Vehicles for Evaluating Effectiveness of Traffic Management Strategies on Fuels

The primary objective of this research is to develop a practical model for evaluating the effects of traffic management on fuel efficiency. The relationships between the real-world driving activities, the vehicle specific power, and the corresponding fuel consumptions are analyzed based on the data of 26 gasoline and liquefied petroleum gas-fueled light-duty vehicles (LDVs). Then, an indicator for evaluating the level of fuel consumption is designed by dividing the normalized fuel consumption by the fuel use in the most economic scenario. An aggregate model is developed following the design of the indicator that features minimal input requirement and meaningful output for LDVs. In the case studies, the proposed model is applied to estimating and comparing the fuel efficiency of several driving cycles, evaluating the fuel efficiency improvement resulting from the electronic toll collection system, and developing temporal variations of fuel efficiency for a road in Beijing by using floating car data. Finally, the merits of the proposed model are discussed, and the limitations and recommendations are provided for further model improvement.

Development of City-Specific Driving Cycles for Transit Buses Based on VSP Distributions: Case of Beijing

With the rapid increase of automobile ownership, the city of Beijing, China, faces challenging issues with regard to traffic congestion and vehicle emissions. In seeking solutions to these issues, developing and improving public transportation systems is considered one of the most feasible and promising strategies because these systems have high passenger-carrying capacity and low pollution on a per passenger basis. Driving cycles reflect traffic conditions, and thus vehicle emissions, and form a scientific base to further improve bus operations. This paper is intended to develop city-specific driving cycles for transit buses for Beijing. The operational data of 126 buses were collected by using a portable global positioning system (GPS) for three types of bus routes: the bus rapid transit (BRT) line, express line, and regular line. Through analysis of the operating characteristics, a methodology for developing driving cycles is proposed based on the parameter of vehicle-specific power (VSP) distribution. Then, by applying this methodology, driving cycles for BRT, express, and regular lines are developed accordingly. Finally, the developed driving cycles are evaluated. Based on the analysis, the proposed driving cycles are able to reflect the real-world operating characteristics of transit buses better than other driving cycles. Furthermore, the emission factors generated based on the developed driving cycles are lower on average than those predicted by using the default driving cycles in the motor vehicle emission simulator (MOVES).

Comparative Analysis of Car-Following Models for Emissions Estimation

Recent studies have indicated that the accuracy of the emissions estimation in a traffic simulation model can be little improved by using the traditional model calibration approaches. Instead, the models internal mechanism in depicting the second-by-second vehicle activities needs to be investigated. Since the car-following model is the core component of a traffic simulation model, this paper attempts to conduct a comparative study of car-following models concerning their effects on the explanatory parameter of vehicle emissions, namely, the vehicle specific power (VSP) distribution. The car-following models selected for the analysis are the optimal velocity model (OVM), generalized force model (GFM), full velocity difference model (FVDM), Wiedemann model, and the Fritzsche model. Massive field car-following trajectories are collected, and a numerical simulation method is designed for each car-following model to generate its vehicle trajectories and the speed-specific VSP distributions. By a comparison of VSP distributions collected from the field and generated by car-following models, it was found that OVMs and GFMs generate unrealistic VSP distributions, which will lead to significant emissions estimation errors. By adding the variable of positive velocity difference, the FVDM can effectively improve the accuracy of the VSP distribution and emissions estimation. The VSP distribution of the Wiedemann model differs largely from the field data, which overestimate the peak VSP fraction and the fractions in aggressive driving modes. The Fritzsche model produces VSP distributions consistent with the field distributions. It is also found that the speed-specific VSP distribution is highly correlated with the acceleration distribution. Therefore, improving the accuracy of the speed-specific acceleration distribution is an effective measure to improve the accuracy of the VSP distribution and thus the emissions estimation of the car-following models.

Characteristics of Low-Speed Vehicle-Specific Power Distributions on Urban Restricted-Access Roadways in Beijing

The emission modeling approach has evolved from using the average speed associated with the driving cycle to using the parameter vehicle-specific power (VSP). With this evolution, a new research need focuses on developing ways to characterize traffic conditions by using the VSP distribution. For urban restricted-access roadways, an applicable mathematical model has been developed in existing studies to describe the VSP distributions based on the average travel speed for traffic with a speed higher than 20 km/h. For the average travel speed lower than 20 km/h, the characteristics of VSP distribution are still unclear. For this reason, this study uses large samples of second-by-second floating car data, collected from the expressways in Beijing, to associate the VSP distributions with the average travel speed from 0 to 20 km/h. After VSP distributions of 1,195 pieces of 60-s speed segments are examined, regular patterns are found between the VSP distribution and the average travel speed. Specifically, the highest fraction always appears in the VSP bin of 0, which decreases monotonically with the increase of the average travel speed. A mathematical model of VSP distribution is proposed on the basis of the separate analysis of VSP fractions in negative, zero, and positive VSP bins. A comparative analysis between the estimated and actual fuel consumption demonstrates that the proposed VSP distribution model is reliable and accurate for the estimation of fuel consumption. The findings of this study may help in monitoring the dynamic traffic fuel consumption or emissions when the real-time speed data are available.

Delay correction model for estimating bus emissions at signalized intersections based on vehicle specific power distributions.

The intersection is one of the biggest emission points for buses and also the high exposure site for people. Several traffic performance indexes have been developed and widely used for intersection evaluations. However, few studies have focused on the relationship between these indexes and emissions at intersections. This paper intends to propose a model that relates emissions to the two commonly used measures of effectiveness (i.e. delay time and number of stops) by using bus activity data and emission data at intersections. First, with a large number of field instantaneous emission data and corresponding activity data collected by the Portable Emission Measurement System (PEMS), emission rates are derived for different vehicle specific power (VSP) bins. Then, 2002 sets of trajectory data, an equivalent of about 140,000 sets of second-by-second activity data, are obtained from Global Position Systems (GPSs)-equipped diesel buses in Beijing. The delay and the emission factors of each trajectory are estimated. Then, by using baseline emission factors for two types of intersections, e.g. the Arterial @ Arterial Intersection and the Arterial @ Collector, delay correction factors are calculated for the two types of intersections at different congestion levels. Finally, delay correction models are established for adjusting emission factors for each type of intersections and different numbers of stops. A comparative analysis between estimated and field emission factors demonstrates that the delay correction model is reliable.

Improved Vehicle-Specific Power Bins for Light-Duty Vehicles in Estimation of Carbon Dioxide Emissions in Beijing

With increasingly wide recognition and acceptance of vehicle-specific power (VSP) as a viable variable in modeling vehicle emissions, the method for defining VSP bins is becoming critical. The primary objective of this study is to develop emission-specific VSP bins for estimating carbon dioxide (CO2) emissions for light-duty vehicles by using the real-world data collected in Beijing. The proposed method is developed by considering both emission characteristics and emission contributions of each bin. In this method, speed is chosen as the secondary parameter in defining bins because it has a higher impact on the CO2 emission rate than the engine stress for each VSP bin. With the proposed method, 24 VSP bins are eventually defined on the basis of the emission data collected in Beijing. In the proposed VSP bins, the data under VSP < 0 are grouped into one single bin because of their similar CO2 emission rates and comparable total emission contributions to other bins. Data at VSP = 0 are defined as an independent bin for characteristics that this single VSP point carries, such as its high VSP frequency, high total CO2 emission contributions, and significant lower emission rate than that of adjacent bins. On the basis of the validation of the proposed method, it is found that the use of an independent bin for VSP = 0 improves the accuracy of CO2 emission estimates and that the use of a single bin for VSP < 0, which simplifies the computational procedure, will not increase the error in the estimation of CO2 emissions.