conference paper

Mass transport vehicle routing problem (MTVRP) and the associated network design problem (MTNDP)

International scientific annual conference on operational research, bremen, germany

Publication Date

January 1, 2005
Suggested Citation
L Pagès and R Jayakrishnan (2005) “Mass transport vehicle routing problem (MTVRP) and the associated network design problem (MTNDP)”, in International scientific annual conference on operational research, bremen, germany, pp. 9–13.

research report

Charge it: The promise of plug-in electric hybrids

Publication Date

January 1, 2010

Author(s)

Suggested Citation
WW Recker and JE Kang (2010) Charge it: The promise of plug-in electric hybrids. University of California Transportation Center.

published journal article

Tour-based truck demand modeling with entropy maximization using GPS data

Journal of Advanced Transportation

Publication Date

December 1, 2019
Suggested Citation
Soyoung Iris You and Stephen G. Ritchie (2019) “Tour-based truck demand modeling with entropy maximization using GPS data”, Journal of Advanced Transportation, 2019, pp. 1–11. Available at: 10.1155/2019/5021026.

conference paper

The importance of HEV fuel economy and two research gaps preventing real world implementation of optimal energy management

SAE technical paper series

Publication Date

January 10, 2017

Author(s)

Zachary D. Asher, Van Wifvat, Anthony Navarro, Scott Samuelsen, Thomas Bradley

Abstract

Optimal energy management of hybrid electric vehicles has previously been shown to increase fuel economy (FE) by approximately 20% thus reducing dependence on foreign oil, reducing greenhouse gas (GHG) emissions, and reducing Carbon Monoxide (CO) and Mono Nitrogen Oxide (NOx) emissions. This demonstrated FE increase is a critical technology to be implemented in the real world as Hybrid Electric Vehicles (HEVs) rise in production and consumer popularity. This review identifies two research gaps preventing optimal energy management of hybrid electric vehicles from being implemented in the real world: sensor and signal technology and prediction scope and error impacts. Sensor and signal technology is required for the vehicle to understand and respond to its environment; information such as chosen route, speed limit, stop light locations, traffic, and weather needs to be communicated to the vehicle. Since optimal control requires accurate prediction of the vehicle environment and drive cycle, prediction scope and error impact analysis is needed to understand the required accuracy of sensor and signal information received by the vehicle as well as the accuracy of the optimal control computed. This review presents the current state of research and solutions in development for each of these research gaps. Once these research gaps have been filled, HEVs may have the potential to substantially increase the FE standard and remove ICE vehicles as the leading consumer of petroleum and leading contributor of GHG, CO, and NOx emissions.

Suggested Citation
Zachary D. Asher, Van Wifvat, Anthony Navarro, G. Scott Samuelsen and Thomas Bradley (2017) “The importance of HEV fuel economy and two research gaps preventing real world implementation of optimal energy management”, in SAE technical paper series. SAE International. Available at: 10.4271/2017-26-0106.

Phd Dissertation

The Perception-Intention-Adaptation (PIA) Model: A theoretical framework for examining the effect of behavioral intention and neighborhood perception on travel behavior

Publication Date

January 1, 2013

Author(s)

Abstract

Recent research has indicated convincing evidence of a link between characteristics of the built environment and travel behavior. However, few land use—travel behavior studies include cognitive factors (such as attitudes, perceptions, and environmental norms) that have been found to affect travel mode choice in the social psychology literature. This dissertation develops and empirically tests a theoretical framework called the Perception-Intention-Adaptation (PIA) model that brings land use and attitude-behavior theory together in order to address gaps in the travel behavior literature. Following a detailed description of the PIA model, the dissertation is comprised of three empirical essays. The analyses in these essays are based on cross-sectional and panel data collected during the Expo Line Study, the first experimental-control, before-and-after evaluation of a rail transit investment in California. The first essay evaluates the predictive power of the core socio-psychological constructs of the PIA (attitudes, norms, and control beliefs) in combination with a comprehensive set of built environment and socio-economic measures. Regression models of transit use are used to analyze cross-sectional data obtained before the opening of the Exposition light rail line in Los Angeles. The analysis indicates that two PIA constructs, attitudes toward public transportation and concerns about personal safety, significantly improve the model fit and were robust predictors of transit use, independent of built environment factors. The second essay uses panel data collected before and after the opening of the Exposition light rail line to examine changes in travel behavior. A quasi-experimental approach with experimental (within ½ mile of an Expo station) and control (beyond ½ mile) households is used to evaluate the travel effects of the opening of the Expo line at the household level. The results show a statistically significant reduction in vehicle miles traveled (VMT) in the experimental group, though overall transit ridership and travel-related physical activity did not change significantly. The final essay uses the before and after opening panel data to examine socio-psychological aspects of travel behavior change in response to the Expo Line opening. Random effects models of transit use, car driver trips, and active travel trips all show that the socio-psychological constructs hypothesized in the PIA model do have a significant impact on travel behavior. In addition, cross-lagged models designed to examine the attitude-behavior relationship show an apparent causal pathway from attitudes to behavior for all three travel outcomes.

Suggested Citation
Steven Paul Spears (2013) The Perception-Intention-Adaptation (PIA) Model: A theoretical framework for examining the effect of behavioral intention and neighborhood perception on travel behavior. Ph.D.. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/1gpb62p/alma991034268399704701 (Accessed: October 13, 2023).

published journal article

Outdoor ambient air pollution and breast cancer survival among California participants of the Multiethnic Cohort Study

Environment International

Publication Date

March 1, 2022

Author(s)

Iona Cheng, Johnny Yang, Chiuchen Tseng, Jun Wu, Shannon M. Conroy, Salma Shariff-Marco, Scarlett Lin Gomez, Alice S. Whittemore, Daniel O. Stram, Loïc Le Marchand, Lynne R. Wilkens, Beate Ritz, Anna H. Wu

Abstract

Background Within the Multiethnic Cohort (MEC), we examined the association between air pollution and mortality among African American, European American, Japanese American, and Latina American women diagnosed with breast cancer. Methods We used a land use regression (LUR) model and kriging interpolation to estimate nitrogen oxides (NOx , NO2) and particulate matter (PM2.5, PM10) exposures for 3,089 breast cancer cases in the MEC, who were diagnosed from 1993 through 2013 and resided largely in Los Angeles County, California. Cox proportional hazards models were used to examine the association of time-varying air pollutants with all-cause, breast cancer, cardiovascular disease (CVD), and non-breast cancer/non-CVD mortality, accounting for key covariates. Results We identified 1,125 deaths from all causes (474 breast cancer, 272 CVD, 379 non-breast cancer/non-CVD deaths) among the 3,089 breast cancer cases with 8.1 years of average follow-up. LUR and kriged NOX (per 50 ppb) and NO2 (per 20 ppb), PM2.5 (per 10 µg/m3), and PM10 (per 10 µg/m3) were positively associated with risks of all-cause (Hazard Ratio (HR) range = 1.13–1.25), breast cancer (HR range = 1.19–1.45), and CVD mortality (HR range = 1.37–1.60). Associations were statistically significant for LUR NOX and CVD mortality (HR = 1.60; 95% CI: 1.08–2.37) and kriged NO2 and breast cancer mortality (HR = 1.45; 95% CI 1.02–2.07). Gaseous and PM pollutants were positively associated with breast cancer mortality across racial/ethnic group. Conclusion In this study, air pollutants have a harmful impact on breast cancer survival. Additional studies should evaluate potential confounding by socioeconomic factors. These data support maintaining clean air laws to improve survival for women with breast cancer.

Suggested Citation
Iona Cheng, Juan Yang, Chiuchen Tseng, Jun Wu, Shannon M. Conroy, Salma Shariff-Marco, Scarlett Lin Gomez, Alice S. Whittemore, Daniel O. Stram, Loïc Le Marchand, Lynne R. Wilkens, Beate Ritz and Anna H. Wu (2022) “Outdoor ambient air pollution and breast cancer survival among California participants of the Multiethnic Cohort Study”, Environment International, 161, p. 107088. Available at: 10.1016/j.envint.2022.107088.

conference paper

What is the Optimal Fleet Size for Online Food Delivery Companies?– An Application to San Francisco

Transportation Research Board 100th Annual Meeting

Publication Date

January 1, 2021
Suggested Citation
Bumsub Park and Jean-Daniel M. Saphores (2021) “What is the Optimal Fleet Size for Online Food Delivery Companies?– An Application to San Francisco”. Transportation Research Board 100th Annual Meeting. Available at: https://trid.trb.org/view/1759433 (Accessed: October 11, 2023).

published journal article

Multiclass, multicriteria dynamic traffic assignment with path-dependent link cost and entropy-based risk preference

Transportation Research Record

Publication Date

January 1, 2017
Suggested Citation
Jiangbo Gabriel Yu and R. Jayakrishnan (2017) “Multiclass, multicriteria dynamic traffic assignment with path-dependent link cost and entropy-based risk preference”, Transportation Research Record, 2667(1), pp. 108–118. Available at: 10.3141/2667-11.

published journal article

Air Pollution and Breast Cancer Incidence in the Multiethnic Cohort Study

Journal of Clinical Oncology

Publication Date

January 20, 2025

Author(s)

Anna H. Wu, Jun Wu, Chiuchen Tseng, Daniel O. Stram, Salma Shariff-Marco, Timothy Larson, Deborah Goldberg, Scott Fruin, Anqi Jiao, Pushkar P. Inamdar, Ugonna Ihenacho, Loïc Le Marchand, Lynne Wilkens, Christopher Haiman, Beate Ritz, Iona Cheng

Abstract

PurposeRecent studies suggested fine particulate matter (PM2.5) exposure increases the risk of breast cancer, but evidence among racially and ethnically diverse populations remains sparse.Materials and MethodsAmong 58,358 California female participants of the Multiethnic Cohort (MEC) Study followed for an average of 19.3 years (1993-2018), we used Cox proportional hazards regression to examine associations of time-varying PM with invasive breast cancer risk (n = 3,524 cases; 70% African American and Latino females), adjusting for sociodemographics and lifestyle factors. Subgroup analyses were conducted for race and ethnicity, hormone receptor status, and breast cancer risk factors.ResultsSatellite-based PM2.5 was associated with a statistically significant increased incidence of breast cancer (hazard ratio [HR] per 10 μg/m3, 1.28 [95% CI, 1.08 to 1.51]). We found no evidence of heterogeneity in associations by race and ethnicity and hormone receptor status. Family history of breast cancer showed evidence of heterogeneity in PM2.5-associations (Pheterogeneity = .046). In a meta-analysis of the MEC and 10 other prospective cohorts, breast cancer incidence increased in association with exposure to PM2.5 (HR per 10 μg/m3 increase, 1.05 [95% CI, 1.00 to 1.10]; P = .064).ConclusionFindings from this large multiethnic cohort with long-term air pollutant exposure and published prospective cohort studies support PM2.5 as a risk factor for breast cancer. As about half of breast cancer cannot be explained by established breast cancer risk factors and incidence is continuing to increase, particularly in low- and middle-income countries, our results highlight that breast cancer prevention should include not only individual-level behavior-centered approaches but also population-wide policies and regulations to curb PM2.5 exposure.

Suggested Citation
Anna H. Wu, Jun Wu, Chiuchen Tseng, Daniel O. Stram, Salma Shariff-Marco, Timothy Larson, Deborah Goldberg, Scott Fruin, Anqi Jiao, Pushkar P. Inamdar, Ugonna Ihenacho, Loïc Le Marchand, Lynne Wilkens, Christopher Haiman, Beate Ritz and Iona Cheng (2025) “Air Pollution and Breast Cancer Incidence in the Multiethnic Cohort Study”, Journal of Clinical Oncology, 43(3), pp. 273–284. Available at: 10.1200/JCO.24.00418.