published journal article

A study of tour formation: pre-, during, and post-recession analysis

Transportation

Publication Date

October 1, 2021

Abstract

This study examines changes in activity-travel patterns of employed people during a recession by using a tour-based representation of the activity-based approach. The term tour is defined as a sequence of trips and activities that begins and ends at home and contains at least one non-home activity. Tours are classified based on the presence of work and/or non-work activities. We are interested in investigating how a recession can affect an individual’s tour choices. We developed a rigorous methodological framework by using multi-group structural equation modeling (SEM) to analyze changes in tour choice. In particular, we developed a causal structure conceptualsizing the interrelationships among socio-demographic and economic characteristics, activity-travel participation, and the choice of various work and non-work tours. Using data from the American Time Use Survey (ATUS), the study found that activity-travel relationships and their role in tour choice differed in the recession year (2009) compared to pre- and post-recession years (2009 and 2012, respectively). By analyzing temporal changes in causal structure, we identified four sub-trend groups defined by: (1) norms that did not change in pre-, during, and post-recession years, (2) norms that changed during the recession but returned to the old norm, (3) norms that changed during the recession and were maintained as new norm, and finally (4) 2006 norms that did not change during the 2009 recession but changed after the recession. Via analysis of multiple group SEM, we identified instances of each of these cases and provided potential rationales in the context of how a recession can influence norms and thus can affect activity-travel behavior.

Suggested Citation
Rezwana Rafiq and Michael G. McNally (2021) “A study of tour formation: pre-, during, and post-recession analysis”, Transportation, 48(5), pp. 2187–2233. Available at: 10.1007/s11116-020-10126-8.

conference paper

GAN-Sec: Generative adversarial network modeling for the security analysis of cyber-physical production systems

2019 design, automation & test in europe conference & exhibition (DATE)

Publication Date

March 1, 2019

Author(s)

Sujit Rokka Chhetri, Anthony Lopez, Jiang Wan, Mohammad Al Faruque
Suggested Citation
Sujit Rokka Chhetri, Anthony Bahadir Lopez, Jiang Wan and Mohammad Abdullah Al Faruque (2019) “GAN-Sec: Generative adversarial network modeling for the security analysis of cyber-physical production systems”, in 2019 design, automation & test in europe conference & exhibition (DATE). IEEE, pp. 770–775. Available at: 10.23919/date.2019.8715283.

conference paper

A lane changing cell transmission model for modeling capacity drop at lane drop bottlenecks

Proceedings of the 95th annual meeting of the transportation research board

Publication Date

January 1, 2016

Abstract

Over the years the capacity drop phenomenon at freeway bottlenecks has remained a topic of interest and intrigue. Capacity drop has an undeniable impact on freeway performances, directly affecting the throughput. Various studies have tried to measure, predict, and model capacity drop. In this paper, the authors integrate a simplistic lane changing model and an acceleration model together into the Cell Transmission Model framework. The capacity drop is modeled as a combined effect of a lane changing area upstream of the bottleneck location and an acceleration region downstream. Each lane changing vehicle is considered to contribute towards density on two lanes during the lane changing maneuver as it effects the following vehicles on both the original and target lanes. This effect is modeled through the introduction of a â??perceived densityâ?? variable. This perceived density is obtained by scaling the actual density up by the lane-changing intensity, and is used to determine the demand at the bottleneck. A demand function linearly decreasing in density under over-saturated conditions is used to model the acceleration process of vehicles as they discharge from the bottleneck. It is shown that the capacity drop can then be predicted from calibrated demand-supply functions and lane changing intensity.

Suggested Citation
Anupam Srivastava and Wenlong Jin (2016) “A lane changing cell transmission model for modeling capacity drop at lane drop bottlenecks”, in Proceedings of the 95th annual meeting of the transportation research board, p. 17p.

published journal article

System performance and user response under real-time information in a congested traffic corridor

Transportation Research Part A: General

Publication Date

September 1, 1991

Author(s)

Hani Mahmassani, R. (Jay) Jayakrishnan
Suggested Citation
Hani S. Mahmassani and R. Jayakrishnan (1991) “System performance and user response under real-time information in a congested traffic corridor”, Transportation Research Part A: General, 25(5), pp. 293–307. Available at: 10.1016/0191-2607(91)90145-G.

published journal article

Child serum metabolome and traffic-related air pollution exposure in pregnancy

Environmental Research

Publication Date

January 1, 2022

Author(s)

Beate Ritz, Qi Yan, Di He, Jun Wu, Douglas I. Walker, Karan Uppal, Dean P. Jones, Julia E. Heck

Abstract

Background Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates. Methods We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education. Results In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism. Conclusion The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.

Suggested Citation
Beate Ritz, Qi Yan, Di He, Jun Wu, Douglas I. Walker, Karan Uppal, Dean P. Jones and Julia E. Heck (2022) “Child serum metabolome and traffic-related air pollution exposure in pregnancy”, Environmental Research, 203, p. 111907. Available at: 10.1016/j.envres.2021.111907.

conference paper

US household preferences for alternative-fuel vehicles: Results from a national survey

Proceedings of the 91st annual meeting of the transportation research board

Publication Date

January 1, 2012

Abstract

This paper analyzes responses to a 2010 national survey of 835 US households to explore consumer preferences among five types of vehicles that differ in propulsion technology (gasoline, hybrid electric (HEV), compressed natural gas (CNG), hydrogen fuel cell (HFC), and electric (EV)), vehicle cost, fuel cost, fuel availability, vehicle range, and CO2 emissions during operation. Although gasoline-fueled vehicles are still preferred, there was strong interest in alternatives to gasoline vehicles, and especially in HEVs, while EVs are least popular. The authors estimated a panel rank-ordered mixed logit model to understand the impact of vehicle characteristics and of the socio-economic characteristics of respondents on their preferences for alternative fuel technologies. With the exception of CNG, respondents prefer alternative propulsion technology in cars as opposed to pick-up trucks, sport utility vehicles (SUV), or minivans. The region where people live is not statistically significant. Education matters only in the case of HEVs, but gender has no significant impact, and the influence of age is technology specific. It was found that environmental attitudes are strong predictors of AFV support, particularly for HFC vehicles and EVs. In addition, the authors elicited trade-offs people are willing to make between vehicle cost, fuel cost, vehicle range, and refueling time. In spite of consumer interest for alternative-fuel vehicles, environmental benefits still take second place to economic considerations.

Suggested Citation
Jean-Daniel Saphores and Hilary Nixon (2012) “US household preferences for alternative-fuel vehicles: Results from a national survey”, in Proceedings of the 91st annual meeting of the transportation research board, p. 18p.

published journal article

Bootstrapping improved estimators for linear regression models

Journal of Econometrics

Publication Date

April 1, 1990

Author(s)

Suggested Citation
David Brownstone (1990) “Bootstrapping improved estimators for linear regression models”, Journal of Econometrics, 44(1-2), pp. 171–187. Available at: 10.1016/0304-4076(90)90078-8.

published journal article

Abstract C052: Association between benzene, a hazardous air pollutant, and lung cancer risk: The Multiethnic Cohort Study

Cancer Epidemiology, Biomarkers & Prevention

Publication Date

June 1, 2020

Author(s)

Iona Cheng, Chiuchen Tseng, Jun Wu, Johnny Yang, Salma Shariff-Marco, Jennifer Jain, Seri Park, Scott Fruin, Timothy Larson, Scarlett Lin Gomez, Lynne Wilkens, Daniel Stram, Loic Le Marchand, Beate Ritz, Anna H Wu

Abstract

Background: Benzene is classified as a Group 1 carcinogen in humans. A major pathway of benzene exposure is through inhalation of ambient air contaminated by emissions from motor vehicle exhaust, gas stations, industry, tobacco smoke, and other consumer products. Prior studies of benzene and lung cancer have been limited largely to occupational studies. We examined the association between outdoor air exposure to benzene and lung cancer risk in the large population-based Multiethnic Cohort Study (MEC), including four major U.S. racial/ethnic groups—African Americans, Latinos, Japanese Americans, and Whites. Methods: Ambient benzene exposure was estimated from EPA data from air monitoring stations that were within 20 km of residences of 97,288 MEC participants, largely from Los Angeles County, from the time-period of recruitment (1993-1996) through 12/31/2013. Cox proportional hazards models were used to examine the associations between time-varying benzene exposure and lung cancer risk (cases=2796), adjusting for age, sex, race/ethnicity, smoking, family history of lung cancer, marital status, education, occupation, use of nonsteroidal anti-inflammatory drugs, body mass index, alcohol consumption, physical activity, intake of total calorie, red and processed meats, and neighborhood (block group) socioeconomic status. Stratified analyses were conducted by sex, race/ethnicity, and smoking status. In addition, subgroup analysis was conducted by histologic cell-type (adenocarcinoma, squamous cell carcinoma, small cell carcinoma, large cell, and not otherwise specified carcinoma). Results: Ambient benzene exposure was associated with increased risk of lung cancer (per 1 ppb hazard ratio (HR)=1.18; 95% CI: 1.03-1.35). Slightly higher hazard ratios were observed in females (HR=1.28; 95% CI: 1.05-1.56) in comparison to males (HR=1.12; 95% CI: 0.92-1.35). There was evidence of heterogeneity in associations by race/ethnicity (p heterogeneity=0.02). Specifically, benzene exposure was associated with increased lung cancer risk among African Americans, Japanese Americans, and Latinos (HR ranged 1.18 to 1.42 per 1 ppb), but was inversely associated with risk among Whites. Also, similar associations were seen among ever smokers (HR=1.19; 95% CI: 1.03-1.37) and never smokers (HR=1.25; 95% CI: 0.82-1.89). Across histologic-cell types, a borderline statistically significant association was seen with adenocarcinoma, the most common cell type (HR=1.25, 95% CI: 0.99-1.58). A smaller hazard ratio was observed for squamous cell carcinoma, the stronger smoking-related cell type (HR=1.09, 95% CI: 0.81-1.47). Conclusions: Benzene exposure adversely impacts the risk of lung cancer in the general population but particularly in non-Whites after adjusting for smoking, occupational and other exposures. Additional large population-based studies are needed to confirm this finding and reinforce the need for stringent clear air laws.Citation Format: Iona Cheng, Chiuchen Tseng, Jun Wu, Juan Yang, Salma Shariff-Marco, Jennifer Jain, S. Lani Park, Scott Fruin, Timothy Larson, Scarlett Lin Gomez, Lynne Wilkens, Daniel Stram, Loic Le Marchand, Beate Ritz, Anna H Wu. Association between benzene, a hazardous air pollutant, and lung cancer risk: The Multiethnic Cohort Study [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr C052.

Suggested Citation
Iona Cheng, Chiuchen Tseng, Jun Wu, Juan Yang, Salma Shariff-Marco, Jennifer Jain, S. Lani Park, Scott Fruin, Timothy Larson, Scarlett Lin Gomez, Lynne Wilkens, Daniel Stram, Loic Le Marchand, Beate Ritz and Anna H Wu (2020) “Abstract C052: Association between benzene, a hazardous air pollutant, and lung cancer risk: The Multiethnic Cohort Study”, Cancer Epidemiology, Biomarkers & Prevention, 29(6_Supplement_2), p. C052. Available at: 10.1158/1538-7755.DISP19-C052.

Preprint Journal Article

Impact Evaluation of Falsified Data Attacks on Connected Vehicle Based Traffic Signal Control

Publication Date

October 9, 2020

Author(s)

Shihong Ed Huang, Wai Wong, Yiheng Feng, Qi Alfred Chen, Z. Morley Mao, Henry Liu

Report Number

arXiv:2010.04753

Abstract

Connected vehicle (CV) technology enables data exchange between vehicles and transportation infrastructure and therefore has great potentials to improve current traffic signal control systems. However, this connectivity might also bring cyber security concerns. As the first step in investigating the cyber security of CV-based traffic signal control (CV-TSC) systems, potential cyber threats need to be identified and corresponding impact needs to be evaluated. In this paper, we aim to evaluate the impact of cyber attacks on CV-TSC systems by considering a realistic attack scenario in which the control logic of a CV-TSC system is unavailable to attackers. Our threat model presumes that an attacker may learn the control logic using a surrogate model. Based on the surrogate model, the attacker may launch falsified data attacks to influence signal control decisions. In the case study, we realistically evaluate the impact of falsified data attacks on an existing CV-TSC system (i.e., I-SIG).

Suggested Citation
Shihong Ed Huang, Wai Wong, Yiheng Feng, Qi Alfred Chen, Z. Morley Mao and Henry X. Liu (2020) “Impact Evaluation of Falsified Data Attacks on Connected Vehicle Based Traffic Signal Control”. arXiv. Available at: http://arxiv.org/abs/2010.04753 (Accessed: October 11, 2023).