Transportation and Activity Systems

Activity-Based Forecasting Model for Planning Applications

Investigator: Will Recker

Support: U.S. Department of Transportation and California Department of Transportation/University of California Transportation Center

The work proposed here will be based on previous activity-based research conducted by the principal investigator and his colleagues and will be directed toward developing a practical planning application of a mathematical programming activity-based model as an effective travel demand forecasting tool.

In this proposed research, we seek to complete the modeling framework that has evolved over past research efforts by extending it to a "traditional" planning framework. Specifically, we will couch the activity-based approach in terms that are amenable to its development as a planning tool for travel demand forecasting that not only provides output consistent with accepted trip-based static planning methodologies, but further provides full estimates of the associated dynamics of trip generation, distribution and route selection; all from a theoretically consistent paradigm based on the need/desire of households to interact with their environment. By showing that the particular mathematical programming paradigm can be used to describe the demand modeling processes both for conventional trip-based travel demand and for activity- based approaches it is hoped not only to facilitate the practicality of activity-based modeling approaches, but also to tap into the wealth of research that has guided mainstream travel demand analysis.

If successful, the research will produce the first known activity-based model framework that can be applied to empirical demand forecasting -an application that has long eluded activity-based modeling proponents.


Assessing the Influence of Residential Location Changes on Travel Behavior

Investigator: Michael G. McNally

Support: U.S. Department of Transportation and California Department of Transportation/University of California Transportation Center

There are certain fundamental transportation problems that have remained problems, in part, due to an inability to effectively collect the data necessary to address the problem. One such problem involves the "learning" process by which a household re-locating into a new neighborhood evolves new household activity patterns. More specifically, when a household relocates, what are the immediate and longer term impacts on travel behavior of the local activity and transportation systems? How do household travel patterns evolve? While simple logic suggests that new alternatives will be available for travel and activity decision-making, what are these choices and how does knowledge of these choices evolve.

This project proposes to use technologies developed in prior UCTC, PATH, and Testbed research projects to facilitate the observation of a small number of households re-locating from other areas in Orange County, CA to selected new home developments in Irvine. We will install in-vehicle GPS/Wireless Communication units in all household vehicles to measure specific vehicle use for a multi-day period prior to moving, upon re-locating, and a few months after relocating to Irvine. We will also have the sampled households use iCHASE, an computer-based survey research software developed in prior UCTC research, to record their household activities during this same period. We will utilize GIS-based data sets depicting both the local activity-systems and transport networks. Together, this data will enable us to address the immediate changes in travel behavior upon relocation, and to assess the evolution of stability in this behavior over time.


A Household Survey via an Internet GIS for Models of Activity Scheduling

Investigator: Ming-Sheng Lee

Support: U.S. Department of Transportation and California Department of Transportation/ University of California Transportation Center

This project uses data from a geographic information system (GIS)-based household survey on the Internet to build a production system model of household activity scheduling. The model is a rule-based system that shows how activities are initially scheduled and dynamically changed during execution. Transactional opportunistic problem solving are being used to simulate dynamic scheduling behavior. The model is being verified by comparing model outputs to activity patterns recorded in the existing activity/travel diaries.

 

Considering Risk-Taking Behavior in Travel Time Reliability

Investigator: Will Recker

Support: California Department of Transportation, Partners for Advanced Transit and Highways (PATH)

Despite the importance of assessing the reliability of road networks, there exist only a few suitable techniques. The approaches used in water supply systems, communication systems, and power transmission systems are not directly applicable for transportation systems. The reason is that these approaches ignore route choice behavior when evaluating the performance reliability of a network. This research proposes to incorporate a risk-taking, route choice behavior when estimating travel time reliability of a road network. The proposed research approach will allow the evaluation of network performance under uncertainty. It is particularly useful for the traffic information systems in which travel time information (not only the mean travel time but also the variance of travel time) is provided to the network users for decision-making. It is anticipated that the proposed research can also be used to evaluate the performance of the Advanced Traveler Information Systems (ATIS) and to improve the level-of-service of a road network.

A significant part of this project focuses on developing realistic route choice models by incorporating both the traveler's imperfect knowledge of network travel times as well as the variability of these travel times. Since the route choice problem and the origin-destination (OD) estimation problem are inter-dependent (i.e., the input of one problem is the output of the other problem), this project is also expected to contribute to improving the accuracy and reliability of the OD estimation problem. Though the OD estimation problem is not explicitly addressed in this proposal, the development of realistic route choice models is a key factor in the investigation of origin-destination demand procedures. In addition, it is possible to assess the quality of the estimated OD demand using the variance-covariance matrices of the link choice proportions resulted from the proposed route choice models since uncertainties associated with supply and demand variations are explicitly captured in the models.

 

Micro-Simulation Traffic Model Implementation

Investigator: Michael G. McNally

Support: Orange County Transportation Authority

The OCTA RFP summarizes the state-of-the-practice for macro-simulation modeling in Orange County. The Orange County Transportation Authority (Authority) is responsible for transportation modeling in Orange County. The current Orange County Transportation Analysis model (OCTAM) has been recently updated to OCTAM 3.0 for Base Year 1998 and further improvements are on-going. OCTAM 3.0 incorporates state-of-the-practice modeling components that are consistent with the new Southern California Regional Transportation Model recently released by the Southern California Association of Governments (SCAG). The OCTAM 3.0 model provides a regional travel forecasting base for transportation planning work in Orange County. The OCTAM model is regional in nature and suited for macro-level analysis.

This proposal offers professional services, which are required to assist the regional modeling section in evaluating and integrating a traffic micro-simulation model. The purpose of integrating a micro-simulation with the macro-simulation OCT AM model is to allow a more detailed evaluation of projects through the analysis of various measures of effectiveness. OCTA has identified candidate projects for the application of the micro- simulation model, including network infrastructure improvements such as gap closures, arterial widening, and the addition of HOV or general purpose lanes, as well as operational enhancements such as grade separation of rail, freeway auxiliary lane addition, ramp metering, one-way couplets, reversible lanes, reconfiguration of interchanges, smart streets, and the identification of specific locations to target for improvements such as arterial or freeway bottlenecks.

 

Putting Behavior in Household Travel Behavior Data: An Interactive GIS-based Survey via the Internet [Year 2]

Investigator: Michael G. McNally

Support: U.S. Department of Transportation and California Department of Transportation/ University of California Transportation Center

This project is the second phase of a planned two-year research effort.  The primary goal of the research is a fundamental examination of the behavioral process that results in revealed travel behavior.  To reveal this process, a computer-based household activity survey program, CHASE, is being re-programmed, enhanced, and extended for Internet application (iCHASE), integrated with a GIS, and utilized in a pilot study to collect data for a study of the determinants of travel and activity behavior in households.  These data are inherently dynamic, since CHASE respondents record planned activity agendas and then update and schedule these agenda, on a daily basis, fully defined in time and space (with CHASE recording the process of adding, modifying, and deleting components of a weekly travel pattern).  The resultant data will facilitate the identification of fundamental inter-relationships among a comprehensive range of revealed travel and activity participation variables, leading toward the identification of what are the critical variables, relationships, and rules that govern that behavior.  It is believed that an internet-based travel survey, particularly one as rich in resultant content as ICHASE, will significant reduce data collection costs, improve data quality and quantity, and allow for continuous data collection.

 

Recent Patterns in California Residential Vehicle Fuel Usage

Investigator: Thomas F. Golob

Support: University of California Energy Institute

Understanding total residential transportation energy usage is vital for the planning of conservation measures and the evaluation of incentives and mandates aimed at vehicle fuel efficiency. The annual fuel consumption of households is the outcome of complex decisions that involve the number of vehicles the household owns, leases or has other access to (including company cars), the makes, models and vintages of these vehicles, allocation of vehicles among drivers, allocation of activities to drivers and non-drivers, and choices of mode and activity site. Lifestyle plays a major role. So do demographic and socioeconomic factors, including age, race, ethnicity, education, and income. Spatial location of residence and workplace determines trip lengths, travel opportunities, and the availability of public transportation and non-motorized modes. The proposed research uses the 2001 National Household Transportation Survey that has just become available (in January 2003) to model fuel consumption by California households as a function of the types of vehicles in the household fleet, demographic and socioeconomic characteristics, and residential location. Vehicle types can be defined by any combination of vehicle, make, model and vintage, but it is expected that it will be instructive to use both a consumer-based typology (e.g., subcompact cars, compact cars, compact pickups, full-sized trucks, minivans, compact SUVs, fullsize SUVs) and a fuel-efficiency breakdown for classification purposes. Conclusions will be drawn regarding potential changes in fuel consumption resulting from planned residential developments in California, as well as expected effects of changes in new vehicle fleet fuel-efficiency. Forecasts will be made of the fuel savings that are likely to result from different levels of penetration, by market segment, of new fuel-efficient and alternative-fuel vehicles, including hybrid fuel-cell vehicles.