working paper

Why Do People Drive to Shop? Future Travel and Telecommunications Tradeoffs

Publication Date

December 31, 1997

Abstract

In this study we look at the relationship between shopping and travel trips, especially by car, and ask whether the travel trip has intrinsic value and/or costs for shoppers.

The plan of this paper is as follows: First we establish a baseline about shopping travel, based on recent travel statistics. We then seek, through the transportation and marketing literatures, different approaches to the question of why people travel to stores. This leads us to pose specific hypotheses about shopping-related trips which we then test using activity-based demand modeling. The final sections discuss our results and conclusions. They suggest that the behaviors associated with the adoption of electronic home shopping are complex, and that it is naive to view home shopping as just another channel. Home shopping will not evolve independently of other changes in work, daily routines, and leisure time use.

working paper

Simulating Travel Reliability

Abstract

We present a simulation model designed to determine the impact on congestion of policies for dealing with travel time uncertainty. The model combines a supply side model of congestion delay with a discrete choice econometric demand model that predicts scheduling choices for morning commute trips. The supply model describes congestion technology and exogenously specifies the probability, severity, and duration of non-recurrent events. From these, given traffic volumes, a distribution of travel times is generated, from which a mean, a standard deviation, and a probability of arriving late are calculated. The demand model uses these outputs from the supply model as independent variables and choices are forecast using sample enumeration and a synthetic sample of work start times and free flow travel times. The process is iterated until a stable congestion pattern is achieved. We report on the components of expected cost and the average travel delay for selected simulations.

working paper

Project Evaluation

Publication Date

July 31, 1997

Author(s)

Abstract

Transportation policy making frequently requires evaluating a proposed change, whether it be a physical investment or a new set of operating rules for allocating rights to an existing facility. Some, like the rail tunnel under the English channel, are one-time capital investments with enormous and complex effects on accessibility throughout a network. Others, like congestion pricing proposed for Hong Kong, may be technically reversible but require major behavioral and political groundwork. 

In such cases, the optimization framework that proves useful in so much transportation analysis is often inadequate. In an optimization model, important aspects of a problem are represented as a few variables which can be chosen to maximize some objective. For example, Robert Strotz shows how highway capacity can be chosen to minimize total travel costs in the presence of traffic congestion. But often the change is too sharp a break from existing practice, or the objectives too numerous, to represent the problem in a mathematical optimization framework. Perhaps a given highway improvement not only expands capacity to handle peak traffic flows but also speeds off-peak travel, reduces accidents, and imposes noise on residential neighborhoods. Perhaps the required capital expenditures occur in a complex time pattern, and the safety effects depend on future but uncertain demographic shifts. One would like a method for analyzing the merits of such a package of changes, and for comparing it to alternative packages. 

Such a method is called project evaluation. Performed skillfully, it can identify key consequences of a proposed project and provide quantitative information about them to guide policy makers. Much of this information may be non-commensurable: i.e., the consequences may not all be measured in the same units and hence the analyst may not be able to determine the precise extent to which these effects offset each other. For example, a tax-financed improvement in airway control equipment might improve safety but magnify existing income inequalities. 

Phd Dissertation

The Value of Access to Highways and Light Rail Transit: Evidence for Industrial and Office Firms

Abstract

This dissertation examines the relationship between transportation access and industrial and office property rents. The primary purpose of this research is to evaluate two sparsely studied topics in the transportation-land use literature: the impacts of light rail transit on property values, and the effect of transportation facilities on non-residential land uses.

Multivariate regression analysis is used on longitudinal data for approximately five hundred and twenty office properties and five hundred industrial properties collected from the San Diego metropolitan region over the period from 1986 to 1995. Asking rents ($/square foot/month) is the dependent variable. Straight-line distance of each property to the nearest freeway on/off ramp, the nearest light rail station, and to the San Diego central business district provide measures of access. Other independent variables include building and neighborhood characteristics.

The findings show that access to freeways is consistently significant in predicting office rents. This result indicates that freeways are important in shaping office property values, and by extension office land use patterns. Light rail transit did not have a significant effect on office rents. Access to the CBD was only significant for downtown office properties. The CBD variable in this case may be a proxy for the effect of localization economies. None of the measures of access was significant for industrial properties.

This research underscores the importance of refining measures of access in order to capture and better understand the transportation-land use relationship. In particular, if the distance of an industrial firm to freeways, light rail transit, and the CBD is not important, then what kinds of access do matter? This research also has important implications for planning light rail transit systems. There is strong evidence that light rail systems do not provide enough travel cost savings to increase non-residential property values. This finding should be taken seriously in planning alignments for future light rail systems. Light rail systems need to be aligned with existing activity centers, rather than expected to stimulate new development or the redevelopment of distressed urban areas.

working paper

A Simultaneous Model of Activity Participation and Trip Chain Generation by Households

Publication Date

June 30, 1997

Author(s)

Abstract

A trip generation model has been developed using a time-use perspective, in which trips are generated in conjunction with out-of-home activities, and time spent traveling is another component of overall time use. The model jointly forecasts three sets of endogenous variables – (1) activity participation and (2) travel time (together making up total out-of home time use), and (3) trip generation — as a function of household characteristics and accessibility indices. It is estimated with data from the Portland, Oregon 1994 Activity and Travel Survey. Results show that the basic model, which has ten endogenous time use and trip generation variables and thirteen exogenous variables, fits well, and all postulated relationships are upheld. Test show that the basic model, which divides activities into work and nonwork, can be extended to a three-way breakdown of subsistence, discretionary and obligatory activities. The model can also capture the effects of in-home work on trip chaining and activity participation. We use the model to explore the effects on time use and trip chaining of GIS-based and zone-based accessibility indices.

Phd Dissertation

A network traffic control algorithm with analytically embedded traffic flow models

Abstract

This dissertation documents the development of optimization models in a mixed integer-linear form for the control of network traffic signalized intersections. The existing network traffic signal optimization formulations usually do not include traffic flow models, except for control schemes such as SCOOT that use simulation for heuristic optimization. Other conventional models normally use isolated intersection optimization with traffic arrival prediction using detector information, or optimization schemes based on green bandwidth. In this dissertation a complete formulation of the problem that includes explicit constraints to model the movement of traffic along the streets between the intersections in a time-expanded network is presented, as well as constraints to capture the permitted movements from modern signal controllers. The platoon dispersion model used is the well-known Robertson’s model, which forms linear constraints. Thus it is a rare example of a traffic simulation being analytically embedded in an optimization formulation. The formulation is an integer-linear program, and does not assume fixed cycle lengths or phase sequences. It assumes full information on external inputs, but can be incorporated in a sensor-based environment. The integer-linear program formulation may not be efficiently solved with standard simplex and branch and bound techniques. We discuss network programming formulations to handle the linear platoon dispersion equations and the integer constraints at the intersections. A special purpose network simplex algorithm for fast solution is addressed in the proposed solution approach. The optimization model takes the form of mixed integer linear programming. The control strategies generated by these optimization models were compared with those derived from conventional signal timing models, using the TRAF-NETSIM microscopic simulation model. It was found that the optimization models successfully produced optimal signal timing plans for the various signalized intersections including simulated and real-world networks. The proposed optimization models consistently outperformed the conventional signal control methods with respect to system delay objective. This conclusion was drawn from the TRAF-NETSIM simulation.

Phd Dissertation

Network surveillance supported object-based and task-based time-bounded fault tolerance schemes and their incorporation into a timeliness-guaranteed kernel

Abstract

Real-time fault tolerance (RTFT) is a core technology for increasing the reliability of computer-based safety-critical applications such as space applications, factory automation systems, etc. In recent years, the real-time computing market has started showing explosive growth. In order to realize highly robust real-time fault tolerant computing stations, several component techniques are necessary. Among the most significant include (a) a scaleable RTFT scheme, (b) a network surveillance (NS) scheme, (c) a timeliness-guaranteed kernel that supports both the RTFT and the NS schemes. This dissertation attempts to make a significant step forward towards the goal of realizing ultra-reliable computer-based safety-critical systems. As a first step in this direction, the following new technologies have been devised: (i) the primary-shadow time-triggered message-triggered object (TMO) replication (PSTR) scheme which provides time-bounded recovery from faults in TMO structured systems, (ii) the supervisor-based network surveillance (SNS) scheme which is effective in a variety of point-to-point networks and is amenable to fault detection latency bound analysis. Second, it was observed that even though a few promising component technologies that addressed certain specific requirements of real-time fault tolerant computing stations have been established, little efforts were made to integrate these technologies. Only such integrated technologies can meet the diverse demands that are imposed by safety-critical applications. This dissertation attempts to establish guidelines for such integration. The following integrated schemes have been devised: (i) the PSTR scheme and the SNS scheme, (ii) the distributed recovery block (DRB) scheme established earlier and the SNS scheme, (iii) the adaptable DRB scheme established earlier and the SNS scheme. Third, convincing demonstrations of the validity and potential utility of the devised schemes would facilitate their use in real-world applications. A timeliness-guaranteed kernel developed earlier was extended to support all the devised schemes. A TMO-structured defense application supported by the newly extended kernel was also made fault-tolerant. Finally, the performance analyses of the RTFT and NS schemes, even though of great importance, have been scarcely practiced. We have analyzed the performance of the devised schemes and obtained some tight time bounds. The modeling and analysis techniques presented would serve as useful guides to system engineers.

Preprint Journal Article

A Choice Experiment Survey of Drayage Fleet Operator Preferences for Zero-Emission Trucks

Abstract

Many U.S. states are supporting the transition of the heavy-duty vehicle (HDV) sector to zero-emission vehicles (ZEVs), with California leading the way through its policy and regulatory initiatives. Within various HDV fleet segments, California’s drayage fleets face stringent targets, requiring all vehicles newly registered in the Truck Regulation Upload, Compliance, and Reporting System to be ZEVs starting January 2024, and all drayage trucks in operation to be zero-emission by 2035. Understanding fleet operator behavior and perspectives is crucial for achieving these goals; however, it remains a critical knowledge gap. This study investigates the preferences and influencing factors for ZEVs among drayage fleet operators in California. A stated preference choice experiment survey was conducted, developed based on previous qualitative studies and literature reviews. With participation from 71 fleets of various sizes and alternative fuel adoption status, there were 648 choice observations in a dual response design collected, consisting of a forced choice between ZEVs and a free choice between ZEVs and status quo alternatives. Multinomial logit model analyses revealed driving range and purchase costs as significant factors for ZEV adoption, with charging facility construction costs also critical in hypothetical choices between ZEVs and status quo alternatives. Fleet or organization size also influenced ZEV choices, with large fleets more sensitive to operating costs and small organizations more sensitive to off-site stations. These findings enhance understanding in this area and provide valuable insights for policymakers dedicated to facilitating the transition of the HDV sector to zero-emission.