Mark Bradley

Bio: Mark Bradley is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Travel behavior & Mode choice. The author has an hindex of 21, co-authored 53 publications receiving 2121 citations.

Urban Form, Travel Time, and Cost Relationships with Tour Complexity and Mode Choice

Abstract: The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the specific land use changes necessary to address different types of travel, and to develop a comparative framework by which the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel. Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice. Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns where respondents work predicted mode choice for mid day and journey to work travel.

Demand for clean-fuel vehicles in california: a discrete-choice stated preference pilot project

Abstract: A study was conducted to determine how demand for clean-fuel vehicles and their fuel is likely to vary as a function of attributes that distinguish these vehicles from conventional gasoline vehicles. For the purposes of the study, clean-fuel vehicles are defined to encompass both electric vehicles and unspecified (methanol, ethanol, compressed natural gas or propane) liquid and gaseous fuel vehicles, in both dedicated or multiple-fuel versions. The attributes include vehicle purchase price, fuel operating cost, vehicle range between refueling, availability of fuel, dedicated versus multiple-fuel capability and the level of reduction in emissions (compared to current vehicles). In a mail-back stated preference survey, approximately 700 respondents in the California South Coast Air Basin gave their choices among sets of hypothetical future vehicles, as well as their choices between alternative fuel versus gasoline for hypothetical multiple-fuel vehicles. Estimates of attribute importance and segment differences are made using discrete-choice nested multinomial logit models for vehicle choice and binomial logit models for fuel choice. These estimates can be used to modify present vehicle-type choice and utilization models to accomodate clean-fuel vehicles; they can also be used to evaluate scenarios for alternative clean-fuel vehicle and fuel supply configurations. Results indicate that range between refueling is an important attribute, particularly if range for an alternative fuel is substantially less than that for gasoline. For fuel choice, the most important attributes are range and fuel cost, but the predicted probability of choosing alternative fuel is also affected by emissions levels, which can compensate for differences in fuel prices.

SACSIM: An applied activity-based model system with fine-level spatial and temporal resolution

Abstract: This paper presents the regional travel forecasting model system (SACSIM) being used by the Sacramento (California) Area Council of Governments (SACOG). Within SACSIM an integrated activity-based disaggregate econometric model (DaySim) simulates each resident's full-day activity and travel schedule. Sensitivity to neighborhood scale is enhanced through disaggregation of the modeled outcomes in three key dimensions: purpose, time, and space. Each activity episode is associated with one of seven specific purposes, and with a particular parcel location at which it occurs. The beginning and ending times of all activity and travel episodes are identified within a specific 30-minute time period. Within SACSIM, DaySim equilibrates iteratively with traditional traffic assignment models. SACSIM was calibrated and tested for a base year of 2000 and for forecasts to the years 2005 and 2035, and was subjected to a formal peer-review. It was used to provide forecasts for the Regional Transportation Plan (RTP) and continues to be used for various policy analyses. The paper explains the model system structure and components, the integration with the traffic assignment model, calibration and validation, sensitivity tests, model application and Federal peer review results. We conclude that it is possible to create and apply a regional demand model system using parcel-level geography and half-hour time of day periods. Experiences thus far have pointed to major benefits of using detailed land use variables and urban design variables, but also to new challenges in providing parcel-level land use inputs for future years.

A model for joint choice of daily activity pattern types of household members

Abstract: Intra-household interactions constitute an important aspect in modeling activity and travel-related decisions. Recognition of this importance has recently produced a growing body of research on various aspects of modeling intra-household interactions and group decision-making mechanisms as well as first attempts to incorporate intra-household interactions in regional travel demand models. The previously published research works were mostly focused on time allocation aspect and less on generation of activity episodes, trips, and travel tours that are necessary units for compatibility with regional travel demand models. Also, most of the approaches were limited to household heads only and did not consider explicitly the other household members as acting agents in the intra-household decision making. A model is proposed for joint choice of daily activity pattern (DAP) types for all household members that explicitly takes into account added group-wise utilities of joint participation in the same activity. The model is based on the aggregate description of individual DAP types by three main categories – mandatory travel pattern, non-mandatory travel pattern, and at-home pattern. Important intra-household interactions can be captured already at this aggregate level. A choice structure considers all possible combinations of DAPs of all household members as alternatives. Utility function of each alternative includes components corresponding to each individual DAP type as well as group-wise interaction terms that correspond to joint choice of the same pattern by several household members. Statistical analysis of intra-household interactions and estimation results of the choice model are presented. The model estimation has confirmed a strong added utility of joint choice of the same pattern for such person types as non-worker or part time worker in combination with child, two retired persons, two children, and others. The proposed model represents a part of the advanced regional model system being developed for the Atlanta Regional Commission.

Activity-Based Travel Forecasting Models in the United States: Progress since 1995 and Prospects for the Future

Abstract: This paper focuses on the use of activity based models in practice for urban and regional planning in the United States (U.S.). In addition to projects that have been carried out, also recognized is work done in a variety of research settings, both inside and outside the U.S. that will assist in the choice of activity based models in the future. Regional planning in the U.S. is at a critical stage with the adoption of activity based models accelerating. The paper's goal is to provide an opportunity to review the types of modeling developments that have been successfully implemented. Also discussed are factors that remain as hindrances to the acceptance of activity based models for planning by U.S. government agencies.

Travel and the Built Environment

Abstract: Problem: Localities and states are turning to land planning and urban design for help in reducing automobile use and related social and environmental costs. The effects of such strategies on travel demand have not been generalized in recent years from the multitude of available studies. Purpose: We conducted a meta-analysis of the built environment-travel literature existing at the end of 2009 in order to draw generalizable conclusions for practice. We aimed to quantify effect sizes, update earlier work, include additional outcome measures, and address the methodological issue of self-selection. Methods: We computed elasticities for individual studies and pooled them to produce weighted averages. Results and conclusions: Travel variables are generally inelastic with respect to change in measures of the built environment. Of the environmental variables considered here, none has a weighted average travel elasticity of absolute magnitude greater than 0.39, and most are much less. Still, the combined effect o...

Structural equation modeling for travel behavior research

Abstract: Structural equation modeling (SEM) is an extremely flexible linear-in-parameters multivariate statistical modeling technique. It has been used in modeling travel behavior and values since about 1980, and its use is rapidly accelerating, partially due to the availability of improved software. The number of published studies, now known to be more than 50, has approximately doubled in the past three years. This review of SEM is intended to provide an introduction to the field for those who have not used the method, and a compendium of applications for those who wish to compare experiences and avoid the pitfall of reinventing previous research.