Area of Expertise: Travel Behavior, Land Use, & the Built Environment

Phd Dissertation

Exploring Delivery Service Substitution of Travel: Optimized Fleet Systems and Household Activity Patterns

Publication Date

January 1, 2024

Author(s)

Marjan Mosslemi

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment
View Phd Dissertation

Abstract

This dissertation delves into the intersection of two critical elements shaping the future of transportation: opportunities and the challenges presented by shopping delivery services, particularly same-day delivery (SDD), and the necessity to anticipate and explore the forthcoming transportation paradigm with the new possibilities offered by Autonomous Vehicles (AVs). This study investigates the transformative potential of SDD services facilitated by a fleet of shared autonomous vehicles (SAVs) to reshape daily shopping trips and activities.With a dual focus on both the network and household layers, the dissertation addresses the viability of SDD services, considering vehicle miles traveled (VMT) savings and operational strategies for efficient fleet management on one side, and the impacts on travel patterns on the other. Leveraging real-world data for the network of Irvine, CA, and employing optimization methodologies, this dissertation (i) investigates the potential VMT savings from SDD compared to the base scenario where households conduct their own shopping activities, (ii) analyzes the optimal fleet size needed to achieve significant VMT reductions, and (iii) evaluates operational strategies for cost-effective and efficient service delivery. In this dissertation, I analyze the optimal fleet size and system design settings needed to achieve significant VMT reductions without losing profitability and I evaluate operational strategies for cost-effective and time-sensitive service delivery. At the network layer, the system is modeled as a multi-Vehicle and Multi-Depot Pickup and Delivery Problem with Time Windows (m-MDPDPTW), which was implemented in Google OR-Tools. The depots are assumed to be at the warehouse locations from where shopping goods deliveries are made. An analysis is presented for a delivery service comprising an AV fleet serving households on their daily shopping trips for the case study of the City of Irvine, CA. The results indicate these services can significantly decrease the distance traveled and the time spent for shopping trips. The dissertation tests several scenarios to determine how varying possible service operation parameters as well as demand characteristics would affect the results. Scenarios involving varying percentage of the service demand, time window for deliveries, loading/unloading time, and warehouse distribution are considered. At the household layer, the dissertation examines how the SDD service influences household travel patterns and savings, using output from the California Statewide Travel Demand Model (CSTDM) for the City of Irvine. The time saved is used as an accessibility measure. Using the Household Activity Travel Pattern Problem (HAPP), formulated as a pickup and delivery problem with time windows for household daily activities, time saved is compared over four distinct scenarios: a base (existing) case with CSTDM patterns, the HAPP-optimized version of the base case, the base case excluding shopping trips, and its HAPP-optimized version. HAPP-based analysis sheds light on new opportunities in travel and activity planning enabled by AVs as well as insights into future activity patterns shaped by subscription services that may lead to more optimized travel patterns. High Performance Computing is used to tackle the NP-Hard computational problem involved in HAPP in the real world case study with a large set of households. This research is also intended to establish the viability of operationalizing a HAPP-methodology for analyzing realistic travel network contexts, for transportation policies that involve innovative vehicle usage and routing patterns. A HAPP solution is not a model for the actual household-level travel behavior, but rather a constraint-driven optimal version of it. Nonetheless, with the availability of rich individual level activity data now and in the future, HAPP can indeed become an optimizer for households, if computational problems can be surmounted. This dissertation establishes that computational problems are not insurmountable with current cloud and advanced computing options, even for 4-member households with activities substitutable across individuals, which past research had generally avoided. The research illustrated that, for a real-world network that has an individual and household-level activity-based planning model, or at least a synthesized model of that kind, policy analysis for future transportation options can be done using HAPP to find an optimized implementation of the policy when the behavioral response to such policy is not available in the existing activity models or data. The dissertation also points to future research possibilities involving faster optimizations that can be achieved if HAPP can be implemented with starting feasible solutions that may be developed from existing networks.

Suggested Citation
Marjan Mosslemi (2024) Exploring Delivery Service Substitution of Travel: Optimized Fleet Systems and Household Activity Patterns. Ph.D.. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_3087787095 (Accessed: October 23, 2024).

Phd Dissertation

Essays on Missing Data Models, BLP Contraction Mappings, and MCMC Estimation

Publication Date

January 1, 2012

Author(s)

Phillip Li

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment
View Phd Dissertation

Abstract

My dissertation is composed of four chapters that focus on missing data models, BLP contraction mappings, and Markov chain Monte Carlo estimation. The first chapter focuses on estimating sample selection models with two incidentally truncated outcomes and two corresponding selection mechanisms. The method of estimation is an extension of the Markov chain Monte Carlo (MCMC) sampling algorithm from Chib (2007) and Chib et al. (2009). Contrary to conventional data augmentation strategies for dealing with missing data, the proposed algorithm augments the posterior with only a small subset of the total missing data caused by sample selection. This results in improved convergence of the MCMC chain and decreased storage costs, while maintaining tractability in the sampling densities. The methods are applied to estimate the effects of residential density on vehicle miles traveled and vehicle holdings in California. The empirical results suggest that residential density has a small economic impact on vehicle usage and holdings. In addition, the results show that changes to vehicle holdings from increased residential density are more sensitive for less fuel-efficient vehicles than for fuel-efficient vehicles on average. The second chapter considers the estimation of a multivariate sample selection model with p pairs of selection and outcome variables. A unique feature of this model is that the variables can be discrete or continuous with any parametric distribution, allowing a large class of multivariate models to be accommodated. For example, the model may involve any combination of variables that are continuous, binary, ordered, or censored. Although the joint distribution can be difficult to specify, a multivariate Gaussian copula function is used to link the marginal distributions together and handle the multivariate dependence. The proposed estimation approach relies on the MCMC-based techniques from Lee (2010) and Pitt et al. (2006) and adapts the methods from the preceding authors to a missing data setting. An important aspect of the estimation algorithm, in the same spirit as the algorithm from the first chapter, is that it does not require simulation of the missing outcomes. This has been shown to improve the mixing of the Markov chain. The methods are applied to both simulated and real data. The third paper analyzes a discrete choice model where the observed outcome is not the exact alternative chosen by a decision maker but rather the broad group of alternatives in which the chosen alternative belongs to. This model is designed for situations where the choice behavior at a lower level is of interest but only higher level data are available (e.g. analyzing households’ choices for vehicles at the make-model-trim level but only choice data at the make-model level are observed). I show that the parameters in the proposed model are locally identified, but for certain configurations of the data, they are weakly identified. Methods to incorporate additional information into the problem are discussed, and both maximum likelihood and Bayesian estimation methods are explored. The last chapter proposes improvements to the contraction mappings used in the context of multinomial logit models. The contraction mapping algorithm proposed in Berry et al. (1995) is slow to converge and is a major burden to implement in applied work. While it is relatively quick to converge for a single run of the algorithm, it is computationally expensive when repeated evaluations are needed, particularly when the algorithm is embedded into maximum likelihood, generalized method of moments, or Bayesian Markov chain Monte Carlo estimation routines. To alleviate this problem, I explore four simple modifications of the contraction mapping to improve its rate of convergence. Importantly, the modifications can be incorporated into existing code with minimal effort. In a simulation study, I demonstrate that the new algorithms require significantly fewer iterations to converge to the unique vector of fixed points than the original specification. The best algorithm results in an 80-fold improvement.

Suggested Citation
Phillip Li (2012) Essays on Missing Data Models, BLP Contraction Mappings, and MCMC Estimation. Ph.D.. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991013957179704701 (Accessed: October 13, 2023).

working paper

Strategic Hydrogen Refueling Station Locations Analysis with Scheduling and Routing Considerations of Individual Vehicles

Publication Date

September 5, 2012

Author(s)

Jee Eun (Jamie) Kang, Will Recker

Working Paper

UCI-ITS-WP-12-2

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment Zero-Emission Vehicles & Low-Carbon Fuels
View working paper

Abstract

Set Covering problems find the optimal provision of service locations while guaranteeing an acceptable level of accessibility for every demand points in a given area. Other than reliance on static,exogenously-imposed accessibility measures, these problems either exclude substantive infrastructure-vehicle interactions or only include fragmented infrastructure-vehicle interactions related to the routing considerations of households seeking refueling service as a requirement of performing routine, daily activities. Here, we address this problem by coupling a Location-Routing Problem (LRP) that uses the set covering model as a location strategy to the Household Activity Pattern Problem (HAPP) as the mixed integer scheduling and routing model that optimizes households’ participation in out-of-home activities. The problem addressed includes multiple decision makers: the public/private sector as the service provider, and the collection of individual households that make their own routing decisions to perform a given set of “out-of-home activities” together with a visit to one of the service locations. A solution method that does not necessarily require the full information of the coverage matrix is developed to reduce the number of HAPPs that needs to be solved. The performance of the algorithm, as well as comparison of the results to the set covering model, is presented. Although the application is focused on identifying the optimal locations of Hydrogen Fuel Cell Vehicle (HFCV) refueling stations, this proposed formulation can be used as a facility location strategy for any service activity that is generally toured with other activities.

Suggested Citation
Jee Eun Kang and Will W. Recker (2012) Strategic Hydrogen Refueling Station Locations Analysis with Scheduling and Routing Considerations of Individual Vehicles. Working Paper UCI-ITS-WP-12-2. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/9bf4j0xn.

working paper

Specification Issues in Choice Modeling

Publication Date

December 1, 1978

Author(s)

Timothy Tardiff

Working Paper

UCI-ITS-WP-78-12

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment
View working paper

Abstract

This paper examines problems involved in the specification of the correct set of independent variables in choice models. The analytical approach is similar to Theil’s use of auxiliary regressions in the case of standard linear models. The key conclusions are that the inclusion of superfluous independent variables does not affect the consistency of the correct coefficients, but exclusion of independent variables can lead to inconsistent estimates. The sources of bias are the possible correlations between included and excluded independent variables and the change in the structure of the random error terms in the utility functions. Because of the flexibility of its error structure, particular attention is given to the multinomial probit model. When independent variables are excluded, asymptotic differences among are alternative estimators arise because of different implicit error structures. The differences among the alternative estimators and the general effects of under specification are examined empirically with simulated data.

Suggested Citation
Timothy J. Tardiff (1978) Specification Issues in Choice Modeling. Working Paper UCI-ITS-WP-78-12. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/2sw3332t.

working paper

Simultaneous Equation Systems Involving Binary Choice Variables

Publication Date

May 1, 1990

Associated Project

Author(s)

Leo J. G. van Wissen, Thomas Golob

Working Paper

Reprint No. 20

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment
View working paper

Abstract

In this paper a simultaneous modeling system for dichotomous endogenous variables is developed and applied empirically to longitudinal travel demand data of modal choice. The reported research is motivated by three factors. First, the analysis of discrete data has become standard practice among geographers, sociologists, and economists. In the seventies a number of new tools were developed to handle multivariate discrete data (Bishop, et al., 1975; Fienberg, 1980; Goodman, 1972). However, while these methods are invaluable in studying empirical relationships among sets of discrete variables, they have a limited ability to reveal the underlying causal structure that generated the data.Second, in travel demand analysis and housing market modeling, attention has been focused largely on single-equation models. It can be argued that this scope is too limited. Human decisions are usually not taken in isolation but in conjunction with other decisions and events. There may be complex feedback relations, recursive, sequential, and simultaneous decision structures that cannot be adequately described in a single equation. This has been a major motivation in the seventies in sociology for the development of a new modeling approach: linear structural equations with latent variables. Such models combine the classical simultaneous equation system model with a linear measurement model. Original developments, particularly the LISREL model (Joreskog, 1973, 1977), did not allow for discrete dependent variables. More recently, Muthen (1983, 1984, 1987) and others (e.g., Bentler, 1983, 1985) developed models that incorporate various types of non-normal endogenous variables, including censored/truncated polytomous and dummy variables. This paper explores the possibilities of this method for simultaneous equation models in dynamic analysis of mobility.A third motivation for the present research is the rapid growth of longitudinal data sets. In recent years many longitudinal surveys have become available for geographical, economic, and transportation analyses. In labor and housing market analysis the Panel Study of Income Dynamics (PSID, 1984) has played an important role (Heckman and Singer, 1985; Davies and Crouchley, 1984, 1985). In consumer behavior, the Cardiff Consumer Panel has been a major motivation for the development and testing of dynamic discrete choice models (Wrigley, et al., 1985; Wrigley and Dunn, 1984a, 1984b, 1984c, 1985; Dunn and Wrigley, 1985; Uncles, 1987). In the Netherlands a large general mobility panel has been conducted annually since 1984 (J. Golob, et al., 1985; van Wissen and Meurs, 1989). Here analyses have focused on discrete data on modal choice (T. Golob, et al., 1986), as well as on dynamic structural modeling (Golob and Meurs, 1987, 1988; Kitamura, 1987; Golob and van Wissen, 1988; Golob, 1988). The present paper is an extension of this line of research to incorporate dynamic structural models of modal choice, using data from the Dutch Mobility Panel.This paper is organized as follows: In Section 2 the basic methodology is developed. In Section 3 the simultaneous equation system of dummy variables is compared with the conditional logistic model, which is derived from, and equivalent to, the familiar log-linear model. In the fourth section, both models are applied to a dynamic data set of train and bus usage. Some major conclusions regarding the above are drawn in the final section.

Suggested Citation
Leo J. van Wissen and Thomas F. Golob (1990) Simultaneous Equation Systems Involving Binary Choice Variables. Working Paper Reprint No. 20. Institute of Transportation Studies, UC Irvine: University of California Transportation Center. Available at: https://escholarship.org/uc/item/5t28k04n.

Related Publications

working paper | Jun 1991

Federal Subsidies and the Ruinous Decline in Transit Productivity: It Wasn't Supposed to Turn out Like This

working paper | Dec 1988

Structural Equation Modeling of Travel Choice Dynamics

working paper | Nov 1988

Simultaneous Equation Systems Involving Binary Choice Variables

working paper | Jun 1991

Home Environment Consequences of Commute Travel Impedance

working paper | Jun 1989

Aggression on Roadways

working paper

Simultaneous Equation Systems Involving Binary Choice Variables

Publication Date

November 1, 1988

Associated Project

Author(s)

Leo J. G. van Wissen, Thomas Golob

Working Paper

UCI-ITS-WP-88-15, UCI-ITS-AS-WP-88-3

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment
View working paper

Abstract

In this paper a simultaneous modeling system for dichotomous endogenous variables is developed and applied empirically to longitudinal travel demand data of modal choice. The reported research is motivated by three factors. First, the analysis of discrete data has become standard practice among geographers, sociologists, and economists. In the seventies a number of new tools were developed to handle multivariate discrete data (Bishop, et al., 1975; Fienberg, 1980; Goodman, 1972). However, while these methods are invaluable in studying empirical relationships among sets of discrete variables, they have a limited ability to reveal the underlying causal structure that generated the data. Second, in travel demand analysis and housing market modeling, attention has been focused largely on single-equation models. It can be argued that this scope is too limited. Human decisions are usually not taken in isolation but in conjunction with other decisions and events. There may be complex feedback relations, recursive, sequential, and simultaneous decision structures that cannot be adequately described in a single equation. This has been a major motivation in the seventies in sociology for the development of a new modeling approach: linear structural equations with latent variables. Such models combine the classical simultaneous equation system model with a linear measurement model. Original developments, particularly the LISREL model (Jtireskog, 1973, 1977), did not allow for discrete dependent variables. More recently, Muthen (1983, 1984, 1987) and others (e.g., Bentler, 1983, 1985) developed models that incorporate various types of non-normal endogenous variables, including censored/truncated polytomous and dummy variables. This paper explores the possibilities of this method for simultaneous equation models in dynamic analysis of mobility. A third motivation for the present research is the rapid growth of longitudinal data sets. In recent years many longitudinal surveys have become available for geographical, economic, and transportation analyses. In labor and housing market analysis the Panel Study of Income Dynamics (PSID, 1984) has played an important role (Heckman and Singer, 1985; Davies and Crouchley, 1984, 1985). In consumer behavior, the Cardiff Consumer Panel has been a major motivation for the development and testing of dynamic discrete choice models (Wrigley, et al., 1985; Wrigley and Dunn, 1984a, 1984b, 1984c, 1985; Dunn and Wrigley, 1985; Uncles, 1987). In the Netherlands a large general mobility panel has been conducted annually since 1984 (J. Golob, et al., 1985; van Wissen and Meurs, 1989). Here analyses have focused on discrete data on modal choice (T. Golob, et al., 1986), as well as on dynamic structural modeling (Golob and Meurs, 1987, 1988; Kitamura, 1987; Golob and van Wissen, 1988; Golob, 1988). The present paper is an extension of this line of research to incorporate dynamic structural models of modal choice, using data from the Dutch Mobility Panel.

Suggested Citation
Leo J. van Wissen and Thomas F. Golob (1988) Simultaneous Equation Systems Involving Binary Choice Variables. Working Paper UCI-ITS-WP-88-15, UCI-ITS-AS-WP-88-3. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/79d13259.

Related Publications

working paper | Jun 1991

Federal Subsidies and the Ruinous Decline in Transit Productivity: It Wasn't Supposed to Turn out Like This

working paper | Dec 1988

Structural Equation Modeling of Travel Choice Dynamics

working paper | May 1990

Simultaneous Equation Systems Involving Binary Choice Variables

working paper | Jun 1991

Home Environment Consequences of Commute Travel Impedance

working paper | Jun 1989

Aggression on Roadways

working paper

Population and Employment Densities: Structure and Change

Publication Date

September 5, 1994

Associated Project

Author(s)

Kenneth Small, Shunfeng Song

Working Paper

UCI-ITS-WP-93-5, UCTC 161

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment
View working paper

Abstract

We examine spatial patterns and their changes during the 1970s for the Los Angeles region, by estimating monocentric and polycentric density functions for employment and population. Downtown Los Angeles is clearly identified as the statistical monocentric center of the region, and it is the most consistently strong center in the polycentric patterns. Polycentric models fit statistically better than monocentric models, and there was some shift in employment distribution toward a more polycentric pattern. These findings verify the existence of polycentricity in Los Angeles and demonstrate for the first time that employment and especially population follow a polycentric pattern based on exogenously defined employment centers. The results confirm that both employment and population became more dispersed during the 1970s.

Suggested Citation
Kenneth A. Small and Shunfeng Song (1994) Population and Employment Densities: Structure and Change. Working Paper UCI-ITS-WP-93-5, UCTC 161. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/6nk5v6b4.

Related Publications

working paper | Aug 1992

A Comparative Assessment of Travel Characteristics for Neo-Traditional Developments

working paper | May 1993

Regional Impacts of Neotraditional Neighborhood Development

working paper | Jan 1999

The Determinants of Growth of Employment Subcenters

working paper | Sep 1998

A Utility-Theory-Consistent System-of-Demand-Equations Approach to Household Travel Choice

working paper | Nov 1997

Simulating Travel Reliability

working paper | Aug 1993

Clean or a Day: Troubles with California's Smog Check

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