Phd Dissertation

Real time mass transport vehicle routing problem: Hierarchical global optimization for large networks

Abstract

This dissertation defines and studies a class of dynamic problems called the “Mass Transport Vehicle Routing Problem” (MTVRP) which is to efficiently route n vehicles in real time in a fast varying environment to pickup and deliver m passengers, where both n and m are large. The problem is very relevant to future transportation options involving large scale real-time routing of shared-ride fleet transit vehicles. Traditionally, dynamic routing solutions were found using static approximations for smaller-scale problems or using local heuristics for the larger-scale ones. Generally heuristics used for these types of problems do not consider global optimality. The main contribution of this research is the development of a hierarchical methodology to solve MTVRP in three stages which seeks global optimality. The first stage simplifies the network through an aggregated representation, which retains the main characteristics of the actual network and represents the transportation network realistically. The second stage solves a simplified static problem, called “Mass Transport Network Design Problem” (MTNDP). The output of stage 2 is a set of frequencies and paths used as an initial solution to the last stage of the process, called Local Mass Transport Vehicle Routing Problem (LMTVRP), where a local routing is performed. The thesis presents the proposed methodology, gives insights on each of the proposed stages, develops a general framework to use the proposed methodology to solve any VRP and presents an application through microsimulation for the city of Barcelona in Spain.

Suggested Citation
Laia Pages (2006) Real time mass transport vehicle routing problem: Hierarchical global optimization for large networks. Ph.D.. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/1gpb62p/alma991035093205004701 (Accessed: October 14, 2023).

published journal article

Ambient Air Pollution and Chronic Obstructive Pulmonary Disease: The Multiethnic Cohort Study

Annals of the American Thoracic Society

Publication Date

May 1, 2025

Author(s)

Seri Park, Daphne Lichtensztajn, Johnny Yang, Jun Wu, Salma Shariff-Marco, Daniel O. Stram, Pushkar Inamdar, Scott Fruin, Timothy Larson, Chiuchen Tseng, Veronica W. Setiawan, Scarlett Lin Gomez, Jonathan Samet, Loïc Le Marchand, Lynne R. Wilkens, Beate Ritz, Anna H. Wu, Iona Cheng

Abstract

Rationale: Globally, chronic obstructive pulmonary disease (COPD) was the third leading cause of death in 2019. Although tobacco smoking is the predominant risk factor, the role of long-term air pollution exposure in increasing the risk of COPD remains unclear. Moreover, few studies that account for smoking history and other known risk factors have been conducted in racially and ethnically minoritized and socioeconomically diverse populations. Objectives: We sought to evaluate the association of ambient air pollution with COPD in a multiethnic population in California. Methods: In the Multiethnic Cohort Study of 38,654 African-American, Japanese-American, Latino, and White California participants who were enrolled in the fee-for-service component of Medicare, we used Cox proportional hazards regression to estimate the association of time-varying ambient air pollutants—particulate matter with an aerodynamic diameter ⩽2.5 μm or ⩽10 μm, nitrogen dioxide, carbon monoxide, ozone, benzene, and ultrafine particles (UFPs)—with COPD risk (n = 10,915 cases; 8.8 yr of follow up). Subgroup analyses were conducted by race and ethnicity, sex, smoking status as recorded on the Multiethnic Cohort Study baseline questionnaire, and neighborhood socioeconomic status. Results: We observed a positive association of nitrogen oxide (per 50 ppb) with risk of COPD (hazard ratio = 1.45; 95% confidence interval = 1.35–1.55). The associations of nitrogen dioxide (per 20 ppb), particulate matter with an aerodynamic diameter ⩽2.5 μm (10 μg/m3) or ⩽10 μm (10 μg/m3), carbon monoxide (1,000 ppb), and UFPs (interquartile range = 5,241.7 particles/cm3) with risk of COPD were in similar directions, as these air pollutants are highly correlated with nitrogen oxide. These associations were found in African-American, Latino, and Japanese-American participants, but not in Whites (P heterogeneity across race and ethnicity 65 yr) population.

Suggested Citation
Sungshim Lani Park, Daphne Lichtensztajn, Juan Yang, Jun Wu, Salma Shariff-Marco, Daniel O. Stram, Pushkar Inamdar, Scott Fruin, Timothy Larson, Chiuchen Tseng, Veronica W. Setiawan, Scarlett Lin Gomez, Jonathan Samet, Loïc Le Marchand, Lynne R. Wilkens, Beate Ritz, Anna H. Wu and Iona Cheng (2025) “Ambient Air Pollution and Chronic Obstructive Pulmonary Disease: The Multiethnic Cohort Study”, Annals of the American Thoracic Society, 22(5), pp. 698–706. Available at: 10.1513/AnnalsATS.202404-387OC.

published journal article

Refining time-activity classification of human subjects using the global positioning system

PLoS One

Publication Date

February 1, 2016

Author(s)

Maogui Hu, Wei Li, Lianfa Li, Doug Houston, Jun Wu

Abstract

Background Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Methods Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Results Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. Conclusions The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well with just GPS, road and tax parcel data. However, caution is warranted when generalizing the model developed from a small number of subjects to other populations.

Suggested Citation
Maogui Hu, Wei Li, Lianfa Li, Douglas Houston and Jun Wu (2016) “Refining time-activity classification of human subjects using the global positioning system”, PLoS One, 11(2), p. e0148875. Available at: 10.1371/journal.pone.0148875.

published journal article

A model of complex travel behavior: Part II—An operational model

Transportation Research Part A: General

Publication Date

July 1, 1986

Abstract

Based on the theoretical model of complex travel behavior developed in a companion paper (Recker et al., 1986), an operational system of models, STARCHILD (Simulation of Travel/Activity Responses to Complex Household Interactive Logistic Decisions), has been developed to examine the formation of household travel/activity patterns. The system employs a simulation approach in combination with techniques of pattern recognition, multiobjective optimization and disaggregate choice models. Initial empirical verification of the system of models is presented based on results obtained from a sample data set.

Suggested Citation
W. W. Recker, M. G. McNally and G. S. Root (1986) “A model of complex travel behavior: Part II—An operational model”, Transportation Research Part A: General, 20(4), pp. 319–330. Available at: 10.1016/0191-2607(86)90090-7.

published journal article

Estimating Post‐Fire Flood Infrastructure Clogging and Overtopping Hazards

Water Resources Research

Publication Date

August 1, 2024

Author(s)

Ariane Jong‐Levinger, Doug Houston, Brett F. Sanders

Abstract

Abstract Cycles of wildfire and rainfall produce sediment‐laden floods that pose a hazard to development and may clog or overtop protective infrastructure, including debris basins and flood channels. The compound, post‐fire flood hazards associated with infrastructure overtopping and clogging are challenging to estimate due to the need to account for interactions between sequences of wildfire and storm events and their impact on flood control infrastructure over time. Here we present data sources and calibration methods to estimate infrastructure clogging and channel overtopping hazards on a catchment‐by‐catchment basis using the Post‐Fire Flood Hazard Model (PF2HazMo), a stochastic modeling approach that utilizes continuous simulation to resolve the effects of antecedent conditions and system memory. Publicly available data sources provide parameter ranges needed for stochastic modeling, and several performance measures are considered for model calibration. With application to three catchments in southern California, we show that PF2HazMo predicts the median of the simulated distribution of peak bulked flows within the 95% confidence interval of observed flows, with an order of magnitude range in bulked flow estimates depending on the performance measure used for calibration. Using infrastructure overtopping data from a post‐fire wet season, we show that PF2HazMo accurately predicts the number of flood channel exceedances. Model applications to individual watersheds reveal where infrastructure is undersized to contain present‐day and future overtopping hazards based on current design standards. Model limitations and sources of uncertainty are also discussed. , Plain Language Summary Communities at the foot of the mountains face an especially dangerous type of flooding called “sediment‐laden floods.” Many such communities in the southwestern U.S. are protected from water floods by flood infrastructure designed to trap sediment at the mouth of mountain canyons and convey only water flows safely past developed areas to a downstream water body. Sediment‐laden floods, which are more forceful and typically larger than water floods, are more likely to happen during storms over burned mountain canyons soon after a wildfire occurs. However, estimating the likelihood that sediment‐laden floods fill and overtop flood infrastructure is challenging since existing sediment‐laden flood models do not explicitly consider the role of flood infrastructure. Here we present the Post‐Fire Flood Hazard Model (PF2HazMo), a model that can estimate the likelihood of post‐fire floods on a canyon‐by‐canyon basis accounting for flood infrastructure. Environmental data collected following a major wildfire is used to apply PF2HazMo to three mountain canyons in southern California, and we find that it predicts the number of floods accurately relative to observed post‐fire flood channel overtopping events. Further, the model is used to predict the frequency of floods due to infrastructure overtopping under both present‐day and future wildfire scenarios. , Key Points Flood risks are heightened by clogging of infrastructure with sediment, which can occur from sequences of storms especially after wildfires A framework for calibration and validation of a post‐fire infrastructure clogging and flood hazard model is presented Model applications reveal whether infrastructure is adequately sized to meet design levels of protection

Suggested Citation
Ariane Jong‐Levinger, Douglas Houston and Brett F. Sanders (2024) “Estimating Post‐Fire Flood Infrastructure Clogging and Overtopping Hazards”, Water Resources Research, 60(8), pp. e2023WR036522. Available at: 10.1029/2023WR036522.

published journal article

Inverse optimization with endogenous arrival time constraints to calibrate the household activity pattern problem

Transportation Research Part B: Methodological

Publication Date

March 1, 2012
Suggested Citation
Joseph Y.J. Chow and Will W. Recker (2012) “Inverse optimization with endogenous arrival time constraints to calibrate the household activity pattern problem”, Transportation Research Part B: Methodological, 46(3), pp. 463–479. Available at: 10.1016/j.trb.2011.11.005.

conference paper

Estimating commute time and distance for human subjects in air pollution epidemiological studies

Proceedings of the conference of the international society of exposure assessment, seoul, korea

Publication Date

August 1, 2010
Suggested Citation
J. Wu and D. Houston (2010) “Estimating commute time and distance for human subjects in air pollution epidemiological studies”, in Proceedings of the conference of the international society of exposure assessment, seoul, korea.

working paper

Estimating the Full Economic Costs of Truck Incidents on Urban Freeways

Publication Date

November 1, 1988

Author(s)

Working Paper

UCI-ITS-WP-88-11

Areas of Expertise

Abstract

This study uses Los Angeles County as the setting for examining the full economic costs of truck-related freeway incidents. Los Angeles County was selected as a setting due to its size–over 7.5 million population in an area of 4,080 square miles, the highly developed nature of its freeway system (504 miles of freeway), the heavy truck traffic on that system (over 12 million truck miles of travel per day), and the availability of data to facilitate analysis of this problem. Another reason for using Los Angeles as the site for this study is that truck-related incidents are a significant and growing problem on the Los Angeles freeway system, one which the California Department of Transportation is also examining. The majority of major incidents on the Los Angeles freeway system involve one or more trucks. During 1983, 1984, and 1985, 424 major incidents–defined as an incident which closes at least two lanes and is predicted to last at least two hours–involving trucks occurred on the freeway system. In other words, a major truck-related incident occurred nearly three out of every five working days of the week. Moreover, data collected for this study indicates that 6,700 to 8,000 total truck incidents occur annually on the Los Angeles County freeway system, or approximately 20 to 25 truck incidents per weekday. The scope of the problem in Los Angeles makes it an excellent setting for analyzing the costs of truck-related freeway incidents. 

Suggested Citation
Roger F. Teal (1988) Estimating the Full Economic Costs of Truck Incidents on Urban Freeways. Working Paper UCI-ITS-WP-88-11. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/8vt3q1m7.

book/book chapter

Interjurisdictional competition and land development: A micro-level analysis

Publication Date

September 1, 2012

Author(s)

Jae Hong Kim, Geoffrey J.D. Hewings
Suggested Citation
Jae Hong Kim and Geoffrey J.D. Hewings (2012) “Interjurisdictional competition and land development: A micro-level analysis”, in Employment location in cities and regions. Springer Berlin Heidelberg, pp. 181–199. Available at: https://doi.org/10.1007/978-3-642-31779-8_9.