Indian Vehicle Ownership: Insights from Literature Review, Expert Interviews, and State-Level Model

This study reviews existing vehicle ownership models for India and describes the results of nine experts’ interviews to gather insights about Indians’ travel patterns and vehicle choices. According to the experts, vehicle price, fuel economy, and brand (in declining importance) are the most decisive factors in Indians’ car purchase choices. This study also estimated household vehicle ownership levels across India’s 35 states using Census 2011 data. The results suggest that states with a higher proportion of computer-owning households and higher share of households living in rural areas with larger household size, ceteris paribus, are likely to have higher car ownership

Local Sensitivity Analysis of Forecast Uncertainty in a Random-Utility-Based Multiregional Input-Output Model

Transportation systems are critical to regional economies and quality of life. The Random-Utility-Based Multiregional Input-Output Model (RUBMRIO) for trade and travel choices is used here to appreciate the distributed nature of commodity flow patterns across the United States’ 3,109 contiguous counties and 12 industry sectors, for rail and truck operations. This paper demonstrates the model’s sensitivity to various inputs using the method of local sensitivity analysis with interactions (LSAI). This work simulates both individual effects as well as interaction effects of model inputs on outputs by providing sensitivity indices of model outputs to variations of inputs under two scenarios. Model outputs include predictions of domestic and export trade flows, value of goods produced, labor expenditures, and household and industry consumption levels across the counties in the United States. The LSAI technique allows transportation system operators to appreciate the roles of any model input and the associated uncertainty of outputs

Welfare Measures to Reflect Home Location Options When Transportation Systems are Modified

Transportation system improvements do not provide simply travel time savings, for a fixed trip table; they affect trip destinations, modes, times of day, and, ultimately, home and business location choices. This paper examines the welfare (or willingness-to-pay) impacts of system changes by bringing residential location choice into a three-layer nested logit model to more holistically anticipate the regional welfare impacts of various system shifts using logsum differences (which quantify changes in consumer surplus). Here, home value is a function of home price, size, and accessibility; and accessibility is a function of travel times and costs, vis-à-vis all mode and destination options. The model is applied to a sample of 60 Austin, Texas, zones to estimate home buyers’ welfare impacts across various scenarios, with different transit fares, automobile operating costs, travel times, and home prices. Results suggest that new locators’ choice probabilities for rural and suburban zones are more sensitive to changing regional access, while urban and central business zone choice probabilities are more impacted by home price shifts. Automobile costs play a more important role in residential location choices in these simulations than those of transit, as expected in a typical U.S. setting (where automobile travel dominates). When generalized costs of automobile travel are simulated to rise 20%, 40%, and 60% (throughout the region), estimated welfare impacts (using normalized differences in logit logsum measures) for the typical new home buying household (with $70,000 in annual income and 2.4 household members) are estimated to be quite negative, at -$56,000, -$99,000, and -$132,000, respectively. In contrast, when auto’s generalized costs fall everywhere (by 20%, 40%, and then 60%), welfare impacts are very positive (+$74,000,$172,500, and $320,000, respectively). Such findings are meaningful for policymakers, planners, and others when anticipating the economic impacts of evolving transportation systems, in the face of new investments, rising travel demands, distance-based tolls, self-driving vehicles, and other changes

Occupant injury severity using a heteroscedastic ordered logit model: Distinguishing the effects of vehicle weight and type

This paper uses a heteroscedastic ordered logit model to study the effects of various vehicle, environmental, roadway and occupant characteristics on the severity of injuries sustained by vehicle occupants, conditional on the crash occurrence. As expected, the models find that heavier vehicles increase both a vehicle’s crashworthiness and its aggressiveness towards others. The models also find that if all passenger vehicles were to become 1000 lbs heavier, crash injury outcomes would not change dramatically. However, if all passenger cars were to become light duty trucks (i.e., minivans, pickups and sport utility vehicles) of the same weight, incapacitating injuries and the fatalities are predicted to rise by 26 and 64 percent, respectively. Beyond weight and vehicle type, many other factors were controlled for all well. For example, older occupants and female occupants are more likely to experience injury and death, particularly when navigating curved roadway sections with higher speed limits

Electrified Vehicle Technology Trends, Infrastructure Implications, and Cost Comparisons

Alternatives to petroleum-based fuels for transportation are sought to address concerns over climate change and energy security. Key semiconductor, software, and battery technologies have sufficiently progressed over the past few decades to enable a mass-market-viable plug-in electric vehicle (PEV) alternative. In this paper, the various PEV architectures are described, including market availability, technologies and trends, practical ranges, battery replacement and power costs, implications for grid operations, and other developments. Manufacturers’ recently announced prices and EPA standardized test data are used (where available) to increase the accuracy of cost comparisons for competing vehicles. Results indicate that in relatively low fuel-cost regions, like the U.S., PEVs enjoy a positive discounted net present value, thanks to tax credits and assuming that the original battery does not need replacement by the owner. Even without the tax credits, PEVs offer financial payback for those residing in higher fuel-cost regions, as long as their batteries last the vehicle’s lifetime or are replaced by manufacturers (under warranty)

Driver Attitudes and Choices: Speed Limits, Seat Belt Use, and Drinking-and-Driving

A better understanding of attitudes and behavioral principles underlying driving behavior and traffic safety issues can contribute to design and policy solutions, such as speed limits and seat belt legislation. This work examines the Motor Vehicle Occupant Safety Surveys (MVOSS) dataset to illuminate drivers' seatbelt use, driving speed choices, drinking-and-driving tendencies, along with their attitudes towards speed limits and seat belt laws. Ordered probit, negative binomial, and linear regression models were used for the data analysis, and several interesting results emerged. The number and variety of results feasible with this single dataset are instructive as well as intriguing