scholarly journals Implications of sustainability for the United States light-duty transportation sector

2016 ◽  
Vol 3 ◽  
Author(s):  
Chris Gearhart
Keyword(s):  
United States ◽  
The United States ◽  
Light Duty ◽  
Transportation Sector ◽  
Image Position

ABSTRACT

scholarly journals By the Numbers: Will Trucking Go Electric?

2018 ◽  
Vol 140 (01) ◽  
pp. 28-29 ◽  
Author(s):  
Jeffrey Winters
Keyword(s):  
United States ◽  
Business Models ◽  
The United States ◽  
Future Trends ◽  
Single Charge ◽  
Light Duty ◽  
Diesel Trucks ◽  
Electric Powertrains ◽  
Fuel Costs

This article presents details of a report on new and future trends in trucking. According to the report, fleet owners may quickly adopt electronic vehicles (EV) for medium-haul routes. In November 2017, Tesla CEO Elon Musk unveiled the design for a battery-powered semi that could travel 500 miles on a single charge. According to Musk, the company would begin producing the trucks in 2019. The report highlighted the regional light-duty delivery market in Europe, where fuel costs are higher than in the United States. Designing vehicles and business models around the capabilities of electric powertrains—capabilities that differ from those of diesel trucks—are expected to enable battery-electric trucks to penetrate the market more quickly.

Minimizing the Cost of Automotive Accidents by Optimizing the Design of Advanced Driver Assist Systems: An Empirical Study Based on a Full-Size Light-Duty Pickup Truck

2021 ◽  
Author(s):  
Francis Fish ◽  
Bert Bras
Keyword(s):  
United States ◽  
The United States ◽  
Vehicle Body ◽  
Driver Assistance Systems ◽  
Full Size ◽  
Purchasing Cost ◽  
Pickup Truck ◽  
Light Duty ◽  
Gross Vehicle Weight ◽  
The Cost

Abstract Advanced Driver Assistance Systems (ADAS) have become increasingly common in vehicles in the last decade. The majority of studies has focused on smaller vehicles with gross vehicle weight rating (GVWR) under 5,000lbs, predominantly sedans, for their ADAS evaluations. While it is sensible to use this style of vehicle because it is ubiquitous worldwide for a typical vehicle body style, these studies neglect full-size light-duty pickup trucks (FSLDPTs), GVWR 5,000 – 10,000lbs, which are abundant on the roads in the United States, 18% of vehicles. The increase in mass, higher center of gravity, and utilitarianism of the vehicles allows for unique conditions for studying the effects of ADAS. This work determines the best and worst location to be hit in a full-size light-duty pickup truck based on data for the industry sales leader in this class of vehicles. The objective is to use these results for future designs of ADAS technologies and their placement on the FSLDPT. While these methods could be applied to any vehicle, the FSLDPT sales leader will be investigated as it represents about 9% of registered vehicles in the United States. The results will be optimized with respect to cost in terms of initial up-front purchasing cost and post-accident vehicle repair cost.

Plant Biomass as a Substitute for Oil in Transportation

2016 ◽  
Author(s):  
Michael B. McElroy
Keyword(s):  
United States ◽  
Co2 Emissions ◽  
Plant Biomass ◽  
Combustion Engine ◽  
Motor Fuel ◽  
Energy System ◽  
The United States ◽  
Corporate Average Fuel Economy ◽  
Transportation Sector ◽  
Henry Ford

As discussed in Chapter 3, the transportation sector accounts for approximately a third of total emissions of CO2 in the United States, with a smaller fraction but a rapidly growing total in China. Combustion of oil, either as gasoline or diesel, is primarily responsible for the transportation- related emissions of both countries. Strategies to curtail overall emissions of CO2 must include plans for a major reduction in the use of oil in the transportation sector. This could be accomplished (1) by reducing demand for trans¬portation services; (2) by increasing the energy efficiency of the sector; or (3) by transitioning to an energy system less reliant on carbon- emitting sources of energy. Assuming continuing growth in the economies of both countries, option 1 is unlikely, certainly for China. Significant success has been achieved already in the United States under option 2, prompted by the application of increasingly more stringent corporate average fuel economy (CAFE) standards. And the technological advances achieved under this program are likely to find application in China and elsewhere, given the global nature of the automobile/ truck industry. The topic for discussion in this chapter is whether switching from oil to a plant- or animal- based fuel could contribute to a significant reduction in CO2 emissions from the transportation sector of either or both countries, indeed from the globe as a whole. The question is whether plant- based ethanol can substitute for gasoline and whether additional plant- and animal- derived products can cut back on demand for diesel. The related issue is whether this substitution can contribute at acceptable social and economic cost to a net reduction in overall CO2 emissions when account is taken of the entire lifecycle for production of the nonfossil alternatives. There is an extensive history to the use of ethanol as a motor fuel. Nicolas Otto, cred¬ited with the development of the internal combustion engine, used ethanol as the energy source for one of his early vehicle inventions in 1860. Henry Ford designed his first auto¬mobile, the quadricycle, to run on pure ethanol in 1896.

Corrigendum to “Air quality impacts from the electrification of light-duty passenger vehicles in the United States” [Atmos. Environ. 208 (2019) 95–102]

2020 ◽  
Vol 229 ◽  
pp. 117487
Author(s):  
Jordan L. Schnell ◽  
Vaishali Naik ◽  
Larry W. Horowitz ◽  
Fabien Paulot ◽  
Paul Ginoux ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
The United States ◽  
Atmos Environ ◽  
Passenger Vehicles ◽  
Light Duty

Passenger Car Equivalents of Light Duty Trucks and the Costs of Mixed Vehicle Traffic: Evidence from Michigan

2011 ◽  
Author(s):  
Sarah B. Cosgrove
Keyword(s):  
United States ◽  
The United States ◽  
Transportation System ◽  
External Cost ◽  
Passenger Car ◽  
Vehicle Type ◽  
Light Duty ◽  
Different Types ◽  
Detroit Area ◽  
Instrumented Vehicles

This study uses naturalistic data from drivers operating instrumented vehicles to estimate the following distance by vehicle type and compute the passenger car equivalents of light duty trucks (LDTs). Unlike most previous studies, this study separates LDTs by vehicle type and produces evidence that cars follow different types of LDTs at different distances. While car drivers follow pickup trucks more closely, they follow SUVs and minivans at a greater distance. The external cost on the transportation system is estimated to be approximately $37 million annually in the Detroit area and $2.05 billion annually for the United States as a whole.

Transport Energy Demand Modeling of the United States Using Artificial Neural Networks and Multiple Linear Regressions

2014 ◽  
Author(s):  
Arash Kialashaki ◽  
John Reisel
Keyword(s):  
Neural Network ◽  
United States ◽  
Energy Demand ◽  
Regression Models ◽  
The United States ◽  
Transportation Energy ◽  
Independent Variables ◽  
Transportation Sector ◽  
The Future ◽  
Artificial Neural

In 2009, the transportation sector was the second largest consumer of primary energy in the United States, following the electric power sector and followed by the industrial, residential, and commercial sectors. The pattern of energy use varies by sector. For example, petroleum provides 96% of the energy used for transportation but its share is much less in other sectors. While the United States consumes vast quantities of energy, it has also pledged to cut its greenhouse gas emissions by 2050. In order to assist in planning for future energy needs, the purpose of this study is to develop a model for transport energy demand that incorporates past trends. This paper describes the development of two types of transportation energy models which are able to predict the United States’ future transportation energy-demand. One model uses an artificial neural network technique (a feed-forward multilayer perceptron neural network coupled with back-propagation technique), and the other model uses a multiple linear regression technique. Various independent variables (including GDP, population, oil price, and number of vehicles) are tested. The future transport energy demand can then be forecast based on the application of the growth rate of effective parameters on the models. The future trends of independent variables have been predicted based on the historical data from 1980 using a regression method. Using the forecast of independent variables, the energy demand has been forecasted for period of 2010 to 2030. In terms of the forecasts generated, the models show two different trends despite their performances being at the same level during the model-test period. Although, the results from the regression models show a uniform increase with different slopes corresponding to different models for energy demand in the near future, the results from ANN express no significant change in demand in same time frame. Increased sensitivity of the ANN models to the recent fluctuations caused by the economic recession may be the reason for the differences with the regression models which predict based on the total long-term trends. Although a small increase in the energy demand in the transportation sector of the United States has been predicted by the models, additional factors need to be considered regarding future energy policy. For example, the United States may choose to reduce energy consumption in order to reduce CO2 emissions and meet its national and international commitments, or large increases in fuel efficiency may reduce petroleum demand.

The Benefits and Costs of New Fuels and Engines for Light-Duty Vehicles in the United States

Risk Analysis ◽  
2008 ◽  
Vol 28 (5) ◽  
pp. 1141-1154 ◽  
Author(s):  
Ryan Keefe ◽  
James P. Griffin ◽  
John D. Graham
Keyword(s):  
United States ◽  
The United States ◽  
Light Duty ◽  
Light Duty Vehicles ◽  
Benefits And Costs
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