Abstract

Knowing what people think about the usefulness, fairness, and success of new transport initiatives is vital information for planners and project evaluators. Methods for studying the complex relationships between attitudes and choice behaviour need to be included in evaluation processes. 

The attitudes of an individual faced with a new transport option will depend in part on whether the individual can take advantage of the new option, whether he or she actually chooses to take advantage, and the perceived benefits of the option, to the individual and to the community. Transport planners use choice models to understand factors affecting demand, but modelling of attitudes has not received similar attention. In this paper we demonstrate how a joint model of attitudes and behaviour can be used in comprehensive project evaluation. The approach involves analysing attitude survey data using a structural equations model designed for use with discrete choice and ordinal-scale variables. 

Our application involves the evaluation of responses to a project that allows solo drivers to pay a fee to use a carpool, or high-occupancy vehicle (HOV) lane facility on the Interstate 15 (1-15) Freeway in San Diego. The attitude survey is of subscribers to the program and a random sample of other freeway users. Four endogenous variables are explained as functions of each other and of exogenous variables such as income, household composition, age and gender. These endogenous variables are: (1) choice of subscription to the program, (2) mode choice of carpooling versus solo driving, (3) perception of the seriousness of the traffic congestion on the route, and (4) attitude towards allowing solo drivers to pay to save time by using the carpool lanes.

Abstract

This paper is a case study of carpooling behavior on the 91 Express Lanes. The 91 Express Lanes are the nation’s first implementation of High Occupancy/Toll (HOT) lanes where carpools with three or more passengers could use the lanes for free (at the time the data for this study was collected) and others pay a toll that varies by time of day to use the premium Express Lane. One concern over such a policy is that people won’t carpool if they can just pay for the travel time savings that they would normally obtain by carpooling and using a High Occupancy Vehicle (HOV) lane. Our survey data show that the rate of carpooling did not change much between the opening of the Express Lanes and now, there is a lot of changing between modes (increases and decreases in the number of passengers), there are a large number of people that carpool a few times a week, and that HOV-2s use both the regular lanes and the Express Lanes. We further investigate whether HOT lanes encourage carpooling by modeling carpool formation with discrete choice models. The results show that mode choice behavior in the corridor is similar to carpooling behavior in other locations and carpooling in the corridor is not discouraged.

Abstract

Auto insurance rates can vary dramatically, with much higher premiums in poor and minority areas than elsewhere, even after accounting for individual characteristics, driving history and coverage. This project used a unique data set to examine the relative influence of place-based socioeconomic characteristics (or redlining) and place-based risk factors on the place-based component of automobile insurance premiums. We used a novel approach of combining tract-level census data and car insurance rate quotes from multiple companies for sub-areas within the city of Los Angeles. The quotes are for a hypothetical individual with identical demographic and auto characteristics, driving records and insurance coverage. This method allowed the individual demographic and driving record to be fixed. Multivariate models are then used to estimate the independent contributions of these risk and redlining factors to the place-based component of the car insurance premium. We find that both risk and redlining factors are associated with variations in insurance costs in the place-based component, with black and poor neighborhoods being adversely affected, although risk factors are stronger predictors. However, even after risk factors are taken into account in the model specification, SES factors remain statistically significant. Moreover, simulations show that redlining factors explain more of the gap in auto insurance premiums between black (and Latino) and white neighborhoods and between poor and nonpoor neighborhoods. The findings do not appear sensitive to the individual characteristics of the hypothetical driver.

Abstract

We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. We do so, however, in an empirical setting where several key observations are missing. To overcome this, we apply Rubin’s Multiple Imputation Method to generate consistent estimates and valid statistical inferences. We also compare these estimates to those produced in a “single imputation” scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. Our results show the importance of properly accounting for errors in the imputation process, and they also show that value of time savings varies greatly according to motorist characteristics.

Abstract

We measure values of time and reliability from 1998 data on actual behavior of commuters on State Route 91 in Orange County, California, where they choose between a free and a variably tolled route. For each route at each time of day and for each day of the week, the distribution of travel times cross different weeks is measured using loop detector data. The best-fitting models represent travel-time by its median and unreliability by the difference between the 90th percentile and the median. We present models of route choice both alone and combined with other choices, namely time of day, car occupancy, and installation of an electronic transponder. In our best model, containing all these choices except time of day, value of time (VOT) is $22.87 per hour, while value of reliability is $15.12 per hour for men and $31.91 for women. These values are 72%,48%, and 101%, respectively, of the average wage rate in our sample.

Abstract

Although the neoclassical labor economics literature assumes that hours of work are determined solely on the supply side as a result of individual demand for leisure, an abundance of evidence points to the importance of employer demand factors in the market for hours of work. Despite the appeal of models allowing for simultaneity in the market for hours, the scarcity of appropriate data has made their estimation difficult. In this paper I attempt to incorporate labor demand into the problem of hours determination in an empirically tractable manner by exploiting the theoretically distinct roles played by commuting time at the individual and aggregate levels. Applying instrumental variables techniques to data from the 1990 U.S. Census yields larger cross-sectional wage elasticities of labor supply for both men and women than are generally found using conventional estimation methods.

Abstract

Transportation professionals have always been interested in how travelers respond to different transportation options. A new application of congestion pricing offers the opportunity to extend such research to situations where travelers face a priced alternative. Travelers along State Route 91 (SR 91) in Southern California can now pay a time-varying fee in order to travel on a set of essentially congestion-free “Express Lanes” located in the median of a very congested preexisting freeway. For this study, we conduct a mail survey of such travelers to learn how they decide to use the free lanes or the toll lanes. We use the data to estimate route choice models and models that incorporate various types of real-time information about accidents, traffic conditions, and price levels into the route choice decision. This study provides new information about the acceptance of congestion pricing, the use of real-time information in making dynamic travel decisions, and individual travelers’ interests in forming carpools.