scholarly journals Mobility chains analysis of technologies for passenger cars and light duty vehicles fueled with biofuels : application of the Greet model to project the role of biomass in America's energy future (RBAEF) project.

2008 ◽  
Author(s):  
M. Wu ◽  
Y. Wu ◽  
M Wang
Keyword(s):  
Passenger Cars ◽  
Light Duty ◽  
Light Duty Vehicles

Recent evidence concerning higher NOx emissions from passenger cars and light duty vehicles

2011 ◽  
Vol 45 (39) ◽  
pp. 7053-7063 ◽  
Author(s):  
David C. Carslaw ◽  
Sean D. Beevers ◽  
James E. Tate ◽  
Emily J. Westmoreland ◽  
Martin L. Williams
Keyword(s):  
Nox Emissions ◽  
Passenger Cars ◽  
Light Duty ◽  
Light Duty Vehicles

Delafossite based catalysts for diesel soot removal for passenger cars and light duty vehicles

2007 ◽  
Author(s):  
A. Renzullo ◽  
A. Tarabocchia ◽  
G. Villata ◽  
A. Raimondi ◽  
D. Mescia ◽  
...  
Keyword(s):  
Diesel Soot ◽  
Passenger Cars ◽  
Light Duty ◽  
Light Duty Vehicles

Configuration Analysis of Two-Vehicle Rear-End Crashes

2003 ◽  
Vol 1840 (1) ◽  
pp. 140-147 ◽  
Author(s):  
Mohamed A. Abdel-Aty ◽  
Hassan T. Abdelwahab
Keyword(s):  
Statistical Models ◽  
Extreme Value ◽  
Passenger Cars ◽  
Passenger Car ◽  
Traffic Crash ◽  
Crash Data ◽  
Light Duty ◽  
Sight Distance ◽  
Multiple Categories

Light truck vehicles (LTVs), including light-duty trucks, vans, minivans, and sport-utility vehicles, are generally larger than common passenger cars and are able to take on additional tasks. LTVs usually ride higher than other common passenger cars, which likely affects the visibility of passenger car drivers. The role of LTVs in rear-end crashes was investigated. The use of statistical models of unordered multiple categories was attempted, including multinomial logit (MNL), heteroscedastic extreme value (HEV), and bivariate probit (BVP) models. Four different rear-end crash configurations (lead and following vehicles) were defined on the basis of the type of the two vehicles involved (LTV or regular passenger car). General Estimates System (GES 2000) traffic crash data were used to calibrate the three suggested models (the MNL, HEV, and BVP models). Modeling results showed that there are sight distance and discomfort problems when a driver in a regular passenger car is driving behind an LTV. The probability of a rear-end crash involving a regular passenger car striking an LTV increases when the driver of the following vehicle is distracted. The analysis also illustrates that the probability of a regular car striking an LTV increases when the driver of the following vehicle has an obscured view.

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