查看更多>>摘要：Since 1975, the fuel economy of passenger cars and light trucks has been regulated by the corporate average fuel economy (CAFE) standards, established during the energy crises of the 1970s. Calls to increase fuel economy are usually met by a fierce debate on the effectiveness of the CAFE standards and their impact on highway safety. A seminal study of the link between CAFE and traffic fatalities was published by R. W. Crandall and J. D. Graham in 1989. They linked higher fuel economy levels to decreases in vehicle weight and correlated the decline in new car weight with about a 20% increase in occupant fatalities. The time series available to them, 1947-1981, includes only the first 4 years of fuel economy regulation, but any statistical relationship estimated over such a short period is questionable. This paper reexamines the relationship between U.S. light-duty vehicle fuel economy and highway fatalities from 1966 to 2002. Cointegration analysis reveals that the stationary linear relationships between the average fuel economy of passenger cars and light trucks and highway fatalities are negative: higher miles per gallon is significantly correlated with fewer fatalities. Log-log models are not stable and tend to produce statistically insignificant (negative) relationships between fuel economy and traffic fatalities. These results do not definitively establish a negative relationship between light-duty vehicle fuel economy and highway fatalities; instead they demonstrate that national aggregate statistics cannot support the assertion that increased fuel economy has led to increased traffic fatalities.
查看更多>>摘要：In the past 20 years, the acceleration performance of light-duty vehicles in the United States has improved substantially while vehicles have gotten larger and heavier. Over the same period, fuel economy, measured as miles per gallon, has not improved. These data suggest that technological innovation in vehicles is not lagging but is not being used to improve vehicle fuel economy. This paper quantifies vehicle efficiency improvements in U.S. light-duty vehicles since 1975 as they relate to fuel consumption. Energy efficiency improvements have been strongly positive and relatively constant since 1975. The rapid rise in fuel economy in the late 1970s was due to a mix of efficiency improvements and downgrading of utility in the form of reduced size, power, and elimination of accessories and amenities (such as air conditioning). In contrast, since the mid-1980s, fuel economy has remained constant while the benefits of technological innovation were used to satisfy private desires (more power, size, and amenities), instead of the public interest (reduced greenhouse gas emissions and oil imports). An important policy question is how and to what extent future efficiency innovations might be directed to the public interest.
查看更多>>摘要：The positions of the diesel and hybrid light-duty passenger vehicles in the technology adoption life cycle are examined with a mid-2004 stated preference study of 1,036 households. Implications of the technology life cycle for historical consumer preference estimates obtained for use in prior models of market share are briefly discussed. The hypothetical life-cycle segments addressed in this paper are early adopters, early buyers, and majority buyers. Survey respondents are segmented into subgroups, or markets, in light of hypothesized attributes of consumers within the product life cycle. Emphasis is placed on delineating the preferences of new instead of used vehicle buyer segments. These categories are compared with the five categories in the high-tech technology adoption life-cycle paradigm of G. Moore. One purpose of the analysis is to use the survey as a test of the reasonableness of the three categories used here. The implications of the survey for use of the rational buyer model of consumer trade-offs of incremental new vehicle capital cost (of a diesel or hybrid) against reduced fuel cost are addressed. Competition of desires for fuel efficiency, acceleration, and towing is also addressed, as are the effects of gender, income, education, and age.
Seungju YoonHainan LiJungwook JunJennifer H. Ogle...
p.26-33页
查看更多>>摘要：An emissions model for transit bus based on road load estimates emissions as a function of transit bus power demand for given transit bus activities and environmental conditions. Transit bus speed and acceleration rates are key activity parameters and are the most important parameters in the estimation of transit bus power demand, also known as engine load. Once the transit bus engine load is calculated for a given speed and acceleration, emissions in grams per vehicle hour can be calculated with grams per brake-horsepower hour emission rates. However, collecting speed and acceleration data on various road types and times of day requires extensive efforts for use in load-based mobile source emissions models. To quantify Atlanta regional transit bus speed and acceleration rates, the Georgia Institute of Technology research team installed trip data in a transit bus operated by the Metropolitan Atlanta Rapid Transit Authority. The team collected second-by-second speed and location data for 3 weeks on a variety of routes and created speed-acceleration matrices by roadway facility type and time of day. This paper focuses on developing a methodology to create transit bus speed-acceleration matrices for use in load-based modal emissions models for the Atlanta metropolitan area. Once a bus service route is specified by roadway facility type and time of day, engine power demand for each speed-acceleration matrix bin can be calculated, weighted by activity frequency on each corresponding matrix bin, and then multiplied by baseline emissions rates that can be obtained from engine dynamometer or chassis dynamometer test results.
查看更多>>摘要：Long-haul truck drivers idle their vehicles to operate heating systems and air conditioners, generate electricity, charge the vehicles' batteries, and warm up the engines. This type of idling, which often occurs over extended periods and could be a significant source of emissions, is expected to increase because of the U.S. Department of Transportation's latest rule mandating that truck drivers rest 10 h for every 14 h of driving. The emissions associated with this type of discretionary idling occurring at the beginning and end of trips are not included in emissions inventories and can be an important contributor to the overall mobile source emissions. There is, therefore, a need to develop a procedure that would yield accurate estimates of extended truck idling emissions. This study developed such a methodology by using a nonattainment area in Texas as a pilot study. On the basis of interviews and observations made at generators such as truck stops, public rest areas, industries, ports, and intermodal facilities, a model was developed to perform the emissions estimates. The procedure was applied to the remaining metropolitan areas in Texas. It was found that extended truck idling emissions were a major source of mobile source emissions, resulting in emissions of more than 30 tons per day of oxides of nitrogen and more than 0.8 ton per day of particulate matter in Texas metropolitan areas. Although these emissions represent less than 4% of the overall on-road mobile source emissions, they are important in assisting nonattainment areas to reach conformity.
Eric JacksonLisa Aultman-HallBritt A. HolmenJianhe Du...
p.43-50页
查看更多>>摘要：This paper evaluates the ability of Global Positioning System (GPS) receivers to determine accurately the second-by-second operating mode of a vehicle in the real-world transportation network. GPS offers the ability to obtain second-by-second velocity directly and to obtain acceleration data indirectly from a vehicle traveling in the real-world traffic network. Although GPS has been used successfully in travel behavior and route choice surveys, the uncertainty in accuracy of velocity and acceleration data obtained from the GPS warrants further investigation to gain a better understanding of the range and spatial distribution of vehicle emissions. In this study, data from two GPS receivers and a Scan-Tool were collected over five repetitions of a 65-mi route. The results indicate that GPS receivers perform as well as the ScanTool when measuring velocity. Furthermore, the GPS receivers determined the 1-s operating mode of the vehicle successfully when measured against the ScanTool. These results will aid in the future development of vehicle emissions models and allow for an analysis of real-world emissions based on real-world operating mode data.
查看更多>>摘要：Mobile source emission models for years have depended on laboratory-based dynamometer data. Recently, however, portable emission measurement systems (PEMS) have become commercially available and in widespread use, and make on-road real-world measurements possible. As a result, the newest mobile source emission models (e.g., U.S. Environmental Protection Agency's mobile vehicle emission simulator) are becoming increasingly dependent on PEMS data. Although on-road measurements are made under more realistic conditions than laboratory-based dynamometer test cycles, they introduce influencing variables that must be carefully measured for properly developed emission models. Further, test programs that simply measure in-use driving patterns of randomly selected vehicles will result in models that can effectively predict current-year emission inventories for typical driving conditions. However, when predicting more aggressive transportation operations than current typical operations (e.g., higher speeds, accelerations), the model predictions will be less certain. In this paper, various issues associated with on-road emission measurements and modeling are presented. Further, an example on-road emission data set and the reduction in estimation error through the addition of a short aggressive driving test to the in-use data are examined. On the basis of these results, recommendations are made on how to improve the on-road test programs for developing more robust emission models.
查看更多>>摘要：The newly developed on-road emission measurement device OEM-2100 was used to collect emissions in the Houston, Texas, area. The device can measure second-by-second fuel consumption and emissions of nitrogen oxides, hydrocarbons, carbon monoxide, carbon dioxide, and particu-late matter. A total of 459.0 mi of on-road tests and 813.9 min of idling tests were conducted on three passenger cars and two trucks under 170 different test conditions (170 bags placed). Global Positioning System data were recorded simultaneously in line with the emission data. Data were analyzed by a six-step data processing procedure. The bag-based analysis indicated that vehicle emissions varied strongly, not only with vehicle activity data but also with roadway facility types and vehicle specifications. Spatial distributions of tested emissions illustrated how the emissions altered along the driving routes. The tested vehicle emissions were compared with the MOBILE6.2 estimates, and significant differences were found for all vehicles and for most testing conditions. Among the roadway facility types, the largest difference was on arterial roads, where the tested on-road emissions were higher than MOBILE6.2 estimates. As for idling conditions, the tested emissions were much higher than MOBILE6.2 estimates and indicates a need for further investigation of idling emissions. The large amount of emission and vehicle activity data collected initiated a useful database in Houston with promising potential uses. More on-road vehicle emission tests are necessary to obtain more accurate and reliable local vehicle emission individuality and to establish a richer on-road emission database.
John S. MillerG. Michael FitchLance E. DougaldScott R. Kreissler...
p.72-80页
查看更多>>摘要：The air quality conformity process requires travel speed estimation for a horizon year, where often few roadway characteristics are precisely known. This paper presents the results of a study to validate three relatively common speed estimation techniques comparing predicted speeds with speeds measured on specific roadway links and illustrates how disparity in speed predictions affect nitrogen oxide (NOx) and volatile organic compound (VOC) estimates in the MOBILE6 emissions model. The results are intriguing. On average, the mean absolute errors for the three techniques were similar, ranging between 8 and 12 mph. This large error resulted because free-flow speed and capacity from the long-range model were not always representative of the links being studied. Further, the study suggests that the error associated with any of the techniques could be reduced to 4 mph through judicious altering of the default capacity or default free-flow speed for a given class of links, a feasible approach even for large networks. Finally, MOBILE6 testing with Virginia metropolitan data suggests that the differences in speed predictions yield a 2.5% difference in estimated VOC emissions, with one technique overestimating VOC emissions by 1.75% and two underestimating VOC emissions by 0.71%. All three techniques underestimated metropolitan area NOx emissions by less than 2%. Because link-based speed validation efforts are relatively rare within the conformity analysis process, the methodology discussed here should be of interest to smaller metropolitan planning organizations seeking to verify that accurate speeds are used in conformity determination.
查看更多>>摘要：This paper examines the impact of a regional simulation model on estimating vehicle emissions. The TRANSIMS software was used to simulate traffic for the Portland, Oregon, metropolitan area. Network and trip table data from the Portland METRO regional model were converted to TRANSIMS and calibrated against traffic counts. The TRANSIMS microsimulator was then used to generate detailed speed and volume information for 30-m link segments at 15-min intervals throughout the day. Second-by-second vehicle speeds were summarized with six speed bins (0, 16.8, 33.5, 503, 67.1, and 83.8 mph). The detailed simulation results were aggregated in various ways to produce the input data required by the MOBILE6 emission inventory software. MOBILE6 was also applied with specific parameters to test the impacts of various assumptions with regard to analysis year, seasons, vehicle types, facility types, and inspection and maintenance programs. The total emissions from each aggregation method were compared with the emissions estimated with the use of MOBILE6 with METRO's EMME/2 volumes and speeds. The analysis indicates that the emission estimates generated with simulation data are significantly different from the emission estimates produced by traditional modeling techniques. If simulation data are aggregated to levels that are more consistent with traditional regional outputs, the magnitude of the difference is minimized. In general, using the more detailed information produced by TRANSIMS or other simulation models will result in higher emissions than are currently estimated by using aggregate methods.
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