published journal article

Particulate matter, traffic-related air pollutants, and circulating C-reactive protein levels: The Multiethnic Cohort Study

Environmental Pollution

Publication Date

September 1, 2023

Author(s)

Meera Sangaramoorthy, Johnny Yang, Chiuchen Tseng, Jun Wu, Beate Ritz, Timothy V. Larson, Scott Fruin, Daniel O. Stram, Seri Park, Adrian A. Franke, Lynne R. Wilkens, Jonathan M. Samet, Loïc Le Marchand, Salma Shariff-Marco, Christopher A. Haiman, Anna H. Wu, Iona Cheng

Abstract

Inhaled particles and gases can harm health by promoting chronic inflammation in the body. Few studies have investigated the relationship between outdoor air pollution and inflammation by race and ethnicity, socioeconomic status, and lifestyle risk factors. We examined associations of particulate matter (PM) and other markers of traffic-related air pollution with circulating levels of C-reactive protein (CRP), a biomarker of systemic inflammation. CRP was measured from blood samples obtained in 1994–2016 from 7,860 California residents participating in the Multiethnic Cohort (MEC) Study. Exposure to PM (aerodynamic diameter ≤2.5 μm [PM2.5], ≤10 μm [PM10], and between 2.5 and 10 μm [PM10-2.5]), nitrogen oxides (NOx, including nitrogen dioxide [NO2]), carbon monoxide (CO), ground-level ozone (O3), and benzene averaged over one or twelve months before blood draw were estimated based on participants’ addresses. Percent change in geometric mean CRP levels and 95% confidence intervals (CI) per standard concentration increase of each pollutant were estimated using multivariable generalized linear regression. Among 4,305 females (55%) and 3,555 males (45%) (mean age 68.1 [SD 7.5] years at blood draw), CRP levels increased with 12-month exposure to PM10 (11.0%, 95% CI: 4.2%, 18.2% per 10 μg/m3), PM10-2.5 (12.4%, 95% CI: 1.4%, 24.5% per 10 μg/m3), NOx (10.4%, 95% CI: 2.2%, 19.2% per 50 ppb), and benzene (2.9%, 95% CI: 1.1%, 4.6% per 1 ppb). In subgroup analyses, these associations were observed in Latino participants, those who lived in low socioeconomic neighborhoods, overweight or obese participants, and never or former smokers. No consistent patterns were found for 1-month pollutant exposures. This investigation identified associations of primarily traffic-related air pollutants, including PM, NOx, and benzene, with CRP in a multiethnic population. The diversity of the MEC across demographic, socioeconomic, and lifestyle factors allowed us to explore the generalizability of the effects of air pollution on inflammation across subgroups.

Suggested Citation
Meera Sangaramoorthy, Juan Yang, Chiuchen Tseng, Jun Wu, Beate Ritz, Timothy V. Larson, Scott Fruin, Daniel O. Stram, Sung-shim Lani Park, Adrian A. Franke, Lynne R. Wilkens, Jonathan M. Samet, Loïc Le Marchand, Salma Shariff-Marco, Christopher A. Haiman, Anna H. Wu and Iona Cheng (2023) “Particulate matter, traffic-related air pollutants, and circulating C-reactive protein levels: The Multiethnic Cohort Study”, Environmental Pollution, 332, p. 121962. Available at: 10.1016/j.envpol.2023.121962.

conference paper

Sharing is caring: Dynamic autonomous vehicle fleet operations under demand surges

Proceedings of the 97th annual meeting of the transportation research board

Publication Date

January 1, 2018

Author(s)

Michael Hyland, Hani Mahmassani

Abstract

Given the emergence and growth of ridesourcing companies, the forthcoming introduction of fully- autonomous vehicles (AVs), and the projected positive impact of AVs on the growth of mobility services, this paper aims to analyze the operational efficiency of two on-demand AV-enabled mobility services (AVeMSs). Specifically, the study compares an AV-enabled shared-ride service, with an AV-enabled traditional ridesourcing (i.e. no shared-rides) service, in terms of handling demand surges, when fleet size is fixed. The authors hypothesize that shared-ride service will significantly outperform traditional ridesourcing service because as demand increases with shared-ride service, the number of feasible shared-ride opportunities increases, effectively increasing the service rate of the shared-ride fleet. To test this hypothesis, the authors employ a dynamic agent-based simulation of travelers, AVs, and an AV fleet operator. The underlying AV fleet control problem is highly-dynamic and stochastic, as traveler requests are unknown to the fleet operator a priori. To solve the dynamic and stochastic optimization problem, the AV fleet operator repeatedly re-solves an online AV-traveler assignment problem based on the current state the system. The simulation results illustrate that under various experimental settings, shared-ride service significantly outperforms ridesourcing service in terms of handling demand surges. At low demand levels, traveler wait times are similar for shared-ride and ridesourcing services. However, as demand increases, average traveler wait times increase more rapidly under ridesourcing service. The results suggest shared-ride service allows fleet operators to better handle demand surges.

Suggested Citation
Michael F. Hyland and Hani S. Mahmassani (2018) “Sharing is caring: Dynamic autonomous vehicle fleet operations under demand surges”, in Proceedings of the 97th annual meeting of the transportation research board, p. 16p.

published journal article

A mixed integer programming model for a double row layout problem

Computers & Industrial Engineering

Publication Date

February 1, 2020

Author(s)

Junjae Chae, Amelia Regan
Suggested Citation
Junjae Chae and Amelia C. Regan (2020) “A mixed integer programming model for a double row layout problem”, Computers & Industrial Engineering, 140, p. 106244. Available at: 10.1016/j.cie.2019.106244.

conference paper

“I’m Pissed Off With The Whole System”: A Qualitative Analysis of Barriers to Healthcare Access Faced by Low-Income Older Adults in Chicago

Transportation Research Board 103rd Annual Meeting

Publication Date

January 1, 2024

Author(s)

G Bella, Elisa Borowski, A Stathopolous
Suggested Citation
G Bella, Elisa Borowski and A Stathopolous (2024) ““I’m Pissed Off With The Whole System”: A Qualitative Analysis of Barriers to Healthcare Access Faced by Low-Income Older Adults in Chicago”. Transportation Research Board 103rd Annual Meeting.

conference paper

Evaluation of a shared-use electric vehicle program: Integrating a web-based survey with in-vehicle tracking

17th PacRim regional science association meeting, portland

Publication Date

July 1, 2001
Suggested Citation
Ming S Lee, James E Marca, Craig R Rindt, Angela M Koos and Michael G McNally (2001) “Evaluation of a shared-use electric vehicle program: Integrating a web-based survey with in-vehicle tracking”, in 17th PacRim regional science association meeting, portland.

conference paper

On the Cybersecurity of Traffic Signal Control System with Connected Vehicles

100th Transportation Research Board (TRB) Annual Meeting

Publication Date

January 1, 2021

Author(s)

Yiheng Feng, Shihong Huang, Wai Wong, Qi Alfred Chen, Morley Mao, Henry Liu
Suggested Citation
Yiheng Feng, Shihong Huang, Wai Wong, Qi Alfred Chen, Morley Mao and Henry Liu (2021) “On the Cybersecurity of Traffic Signal Control System with Connected Vehicles”. 100th Transportation Research Board (TRB) Annual Meeting, Washington, DC.

published journal article

Re-envisioning the Park-and-Ride concept for the automated vehicle (AV) era with Private-to-Shared AV transfer stations

Transportation Research Part A: Policy and Practice

Abstract

Cities implemented park-and-ride (PNR) systems to decrease congestion in dense urban areas while providing transit options to travelers who live in a city’s low- to medium-density regions. The success of PNR systems is mixed, as they suffer from several disadvantages, namely, the uncertainty of parking locations and infrequent and/or unreliable transit services, and the fact that travelers still need to walk to their destination. Motivated by the premise of PNR systems and the potential of automated vehicles (AVs), to address each of the shortcomings of PNR systems, this study proposes a future system with near-ubiquitous AVs where travelers transfer from privately owned AVs (PAVs) to shared-use, shared-ride AVs (SAVs), called a PAV-SAV transfer system. This study proposes a modeling framework to assess the potential market share of the PAV-SAV transfer system and the network impacts (e.g., congestion, vehicle miles traveled) of the proposed system. Finally, the study identifies good designs for the PAV-SAV transfer system using scenario analysis. The critical design variables are the location of transfer stations, the capacity of SAVs, and the transfer station connector links. For the Greater Los Angeles area, the computational results show a market share for PAV-SAV of almost 18% for person trips terminating in downtown Los Angeles. In all scenarios, the proposed PAV-SAV system decreases vehicle hours traveled (VHT) across the whole network with significant decreases in the urban core. For all designs, the PAV-SAV system decreases vehicle miles traveled (VMT) compared to a network without PAV-SAV transfer stations, albeit only slightly. Locating transfer stations closer to the urban core, increasing vehicle capacities, and connecting transfer stations to both arterial links and highway links improves network performance (i.e., VMT and VHT) and increases the market share of the PAV-SAV system.

Suggested Citation
Younghun Bahk, Michael Hyland and Sunghi An (2024) “Re-envisioning the Park-and-Ride concept for the automated vehicle (AV) era with Private-to-Shared AV transfer stations”, Transportation Research Part A: Policy and Practice, 181, p. 104009. Available at: 10.1016/j.tra.2024.104009.

published journal article

Measuring the Built Environment with Google Street View and Machine Learning: Consequences for Crime on Street Segments

Journal of Quantitative Criminology

Publication Date

September 1, 2022

Author(s)

John R. Hipp, Sugie Lee, Donghwan Ki, Jae Hong Kim

Abstract

Despite theoretical interest in how dimensions of the built environment can help explain the location of crime in micro−geographic units, measuring this is difficult.

Suggested Citation
John R. Hipp, Sugie Lee, Donghwan Ki and Jae Hong Kim (2022) “Measuring the Built Environment with Google Street View and Machine Learning: Consequences for Crime on Street Segments”, Journal of Quantitative Criminology, 38(3), pp. 537–565. Available at: 10.1007/s10940-021-09506-9.