published journal article

Without a ride in car country – A comparison of carless households in Germany and California

Transportation Research Part A: Policy and Practice

Publication Date

March 1, 2018

Author(s)

Abstract

One approach to making transportation more sustainable is to transition away from a car-oriented society. Unfortunately, our understanding of the factors that prompt households to voluntarily forgo their motor vehicles is limited. The 2008 Mobility in Germany (MiD) and the 2012 California Household Travel Survey (CHTS) provide an opportunity to start filling this gap by teasing out what built environment and socio-economic variables impact the likelihood that a household is carless (voluntarily or not) in Germany and in California, two car-dependent societies with different carless rates. Results from our generalized structural equation models show that in both Germany and California, households who reside in denser neighborhoods, closer to transit stations, and who have a lower income or fewer children, are more likely to be voluntarily carless. However, households with more education are more likely to be voluntarily carless in Germany, whereas the reverse is true in California. Moreover, employment density and public transit have a higher impact on voluntary carlessness in Germany than in California. Our results also show that different socio-economic groups have substantially different residential location preferences in Germany and in California. These differences may be explained by cultural preferences, historical differences in land use and transportation policies, and by the higher cost of owning a motor vehicle in Germany.

Suggested Citation
Kathrin Kuhne, Suman K. Mitra and Jean-Daniel M. Saphores (2018) “Without a ride in car country – A comparison of carless households in Germany and California”, Transportation Research Part A: Policy and Practice, 109, pp. 24–40. Available at: 10.1016/j.tra.2018.01.021.

working paper

Location and Transportation Strategies in Public Facility Planning

Publication Date

November 1, 1977

Author(s)

Andrew N. White

Working Paper

UCI-ITS-WP-77-8

Abstract

Public facility planning is currently viewed in terms of structuring a service delivery system for optimal provision. Because the spatial process of delivery has been neglected, however, the means of improving service utilization have been narrowly construed as locational in nature. Consequently, facility systems have been modeled and evaluated in terms of supply rather than use, and decentralization has been advocated to the exclusion of alternative spatial patterns. An expanded planning framework regards service delivery as a spatial interaction system and identifies location and transportation as complementary spatial strategies which enhance service utilization and widen the choice of facility pattern. Transportation strategies are more flexible, though, since they directly enhance travel behavior and service accessibility. Moreover, given present planning constraints, transportation strategies have a much wider role to play in improving the effectiveness of future public facility planning and spatial policy. 

Suggested Citation
Andrew N. White (1977) Location and Transportation Strategies in Public Facility Planning. Working Paper UCI-ITS-WP-77-8. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/6sr9z05m.

published journal article

Associations between short-term exposure to wildfire particulate matter and respiratory outcomes: A systematic review

Science of The Total Environment

Publication Date

January 10, 2024

Author(s)

Anqi Jiao, Kathryne Headon, Tianmei Han, Wajeeha Umer, Jun Wu

Abstract

Background The frequency and severity of wildfires have been sharply increasing due to climate change, which largely contributes to ambient particulate matter (PM) pollution. We conducted a systematic review focusing on the short-term relationships between PM attributable to wildfires (wildfire-specific PM) and diverse respiratory endpoints, with a comparison between the effects of wildfire-specific PM vs. all-source/non-wildfire PM. Methods A comprehensive online search for the literature published from 2000 to 2022 was conducted through PubMed, Web of Sciences, Scopus, and EMBASE. We applied search terms related to wildfire smoke and respiratory health outcomes. Results In total, 3196 articles were retrieved, and 35 articles were included in this review. Most studies focused on the associations of wildfire-specific PM with an aerodynamic diameter of ≤2.5 μm (PM2.5) with respiratory emergency department visits or hospitalizations, with a time-series or case-crossover study design. Studies were mostly conducted in the United States, Canada, and Australia. Positive associations of wildfire-specific PM with respiratory morbidity were observed in most studies. Studies that focused on respiratory mortality were limited. Females can be more vulnerable to the respiratory impacts of wildfire PM, while the evidence of vulnerable subpopulations among different age groups was inconclusive. Few studies compared the effects of wildfire-specific vs. all-source/non-wildfire PM, and some reported higher levels of toxicity of wildfire-specific PM, potentially due to its distinct chemical and physical compositions. Asthma and chronic obstructive pulmonary disease were the most studied diseases, and both were adversely affected by wildfire-specific PM. Conclusion To our knowledge, this is the first review that systematically summarized the associations of wildfire-specific PM exposure with adverse respiratory outcomes and compared associations of wildfire-specific vs. all-source/non-wildfire PM. Further investigations may add to the literature by examining the impacts on respiratory mortality and the effects of specific PM components from different types of wildfires.

Suggested Citation
Anqi Jiao, Kathryne Headon, Tianmei Han, Wajeeha Umer and Jun Wu (2024) “Associations between short-term exposure to wildfire particulate matter and respiratory outcomes: A systematic review”, Science of The Total Environment, 907, p. 168134. Available at: 10.1016/j.scitotenv.2023.168134.

published journal article

Interlaminar Fracture Toughness of CFRP Laminates Incorporating Multi-Walled Carbon Nanotubes

Polymers

Publication Date

June 1, 2015

Author(s)

Elisa Borowski, Eslam Soliman, Usama F. Kandil, Mahmoud Reda Taha

Abstract

Carbon fiber reinforced polymer (CFRP) laminates exhibit limited fracture toughness due to characteristic interlaminar fiber-matrix cracking and delamination. In this article, we demonstrate that the fracture toughness of CFRP laminates can be improved by the addition of multi-walled carbon nanotubes (MWCNTs). Experimental investigations and numerical modeling were performed to determine the effects of using MWCNTs in CFRP laminates. The CFRP specimens were produced using an epoxy nanocomposite matrix reinforced with carboxyl functionalized multi-walled carbon nanotubes (COOH–MWCNTs). Four MWCNTs contents of 0.0%, 0.5%, 1.0%, and 1.5% per weight of the epoxy resin/hardener mixture were examined. Double cantilever beam (DCB) tests were performed to determine the mode I interlaminar fracture toughness of the unidirectional CFRP composites. This composite material property was quantified using the critical energy release rate, GIC. The experimental results show a 25%, 20%, and 17% increase in the maximum interlaminar fracture toughness of the CFRP composites with the addition of 0.5, 1.0, and 1.5 wt% MWCNTs, respectively. Microstructural investigations using Fourier transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS) verify that chemical reactions took place between the COOH–MWCNTs and the epoxy resin, supporting the improvements experimentally observed in the interlaminar fracture toughness of the CFRP specimens containing MWCNTs. Finite element (FE) simulations show good agreement with the experimental results and confirm the significant effect of MWCNTs on the interlaminar fracture toughness of CFRP.

Suggested Citation
Elisa Borowski, Eslam Soliman, Usama F. Kandil and Mahmoud Reda Taha (2015) “Interlaminar Fracture Toughness of CFRP Laminates Incorporating Multi-Walled Carbon Nanotubes”, Polymers, 7(6), pp. 1020–1045. Available at: 10.3390/polym7061020.

book/book chapter

Attitude-Behaviour Relationships in Travel-Demand Modelling

Publication Date

January 1, 1979

Author(s)

Thomas Golob, Abraham D. Horowitz, Martin Wachs
Suggested Citation
Thomas F Golob, Abraham D. Horowitz and Martin Wachs (1979) “Attitude-Behaviour Relationships in Travel-Demand Modelling”, in Behavioural Travel Modelling. 1st ed. Routledge, p. 19. Available at: https://www.taylorfrancis.com/chapters/edit/10.4324/9781003156055-44/attitude-behaviour-relationships-travel-demand-modelling-thomas-golob-abraham-horowitz-martin-wachs.

published journal article

Travel demand of an elderly population: An attitudinal model and some comparisons

Transportation Research Forum

Publication Date

January 1, 1977

Author(s)

Will Recker, P. H. Edelstein
Suggested Citation
W. W. Recker and P. H. Edelstein (1977) “Travel demand of an elderly population: An attitudinal model and some comparisons”, Transportation Research Forum, 18(1).

conference paper

A Linear Programming Approach to Optimize the Multi-hop Ridematching Problem in Peer-to-Peer Ridesharing Systems

102nd Transportation Research Board Annual Meeting 2023

Publication Date

January 1, 2023
Suggested Citation
Sunghi An, R. Jayakrishnan and Younghun Bahk (2023) “A Linear Programming Approach to Optimize the Multi-hop Ridematching Problem in Peer-to-Peer Ridesharing Systems”. 102nd Transportation Research Board Annual Meeting 2023.

published journal article

Integrating resident digital sketch maps with expert knowledge to assess spatial knowledge of flood risk: A case study of participatory mapping in Newport Beach, California

Applied Geography

Publication Date

September 1, 2016

Author(s)

Wing Cheung, Doug Houston, Jochen E. Schubert, Victoria Basolo, David Feldman, Richard Matthew, Brett F. Sanders, Beth Karlin, Kristen A. Goodrich, Seth Contreras, Adam Luke
Suggested Citation
Wing Cheung, Douglas Houston, Jochen E. Schubert, Victoria Basolo, David Feldman, Richard Matthew, Brett F. Sanders, Beth Karlin, Kristen A. Goodrich, Santina L. Contreras and Adam Luke (2016) “Integrating resident digital sketch maps with expert knowledge to assess spatial knowledge of flood risk: A case study of participatory mapping in Newport Beach, California”, Applied Geography, 74, pp. 56–64. Available at: 10.1016/j.apgeog.2016.07.006.

research report

Changes in transit use and service and associated changes in driving near a new light rail transit line

Publication Date

May 1, 2015

Abstract

Los Angeles is pursuing an ambitious rail transit investment program with plans to open six new lines by 2019. This report provides policy makes and planners a better understanding of the potential impacts of Los Angeles Metroâ??s rail transit investment program by assessing the changes in transit use of nearby residents and nearby bus service associated with the Expo Line, the first of the six new lines. The findings indicate that changes in bus service that are coincident with the introduction of new light rail transit can negatively affect the overall transit ridership in the corridor. In addition, households living near new Expo Line light rail stations reduced their vehicle miles traveled (VMT), but those households living near bus stops that were eliminated as part of the service change increased their VMT.

Suggested Citation
Hilary Nixon, Marlon Boarnet, Doug Houston, Steven Spears and Jeongwoo Lee (2015) Changes in transit use and service and associated changes in driving near a new light rail transit line, p. 63p.

published journal article

Truck body type classification using a deep representation learning ensemble on 3D point sets

Transportation Research Part C: Emerging Technologies

Abstract

Understanding the spatiotemporal distribution of commercial vehicles is essential for facilitating strategic pavement design, freight planning, and policy making. Hence, transportation agencies have been increasingly interested in collecting truck body configuration data due to its strong association with industries and freight commodities, to better understand their distinct operational characteristics and impacts on infrastructure and the environment. The rapid advancement of Light Detection and Ranging (LiDAR) technology has facilitated the development of non-intrusive detection solutions that are able to accurately classify truck body types in detail. This paper proposes a new truck classification method using a LiDAR sensor oriented to provide a wide field-of-view of roadways. In order to enrich the sparse point cloud obtained from the sensor, point clouds originating from the same truck across consecutive frames were grouped and combined using a two-stage vehicle reconstruction framework to generate a dense three-dimensional (3D) point cloud representation of each truck. Subsequently, PointNet – a deep representation learning algorithm – was adopted to train the classification model from reconstructed point clouds. The model utilizes low-level features extracted from the 3D point clouds and detects key features associated with each truck class. Finally, model ensemble techniques were explored to reduce the generalization error by averaging the results of seven PointNet models and further enhancing the overall model performance. The optimal number of models in the ensemble was determined through a comprehensive sensitivity analysis with the consideration of the average correct classification rate (CCR), the variability of the prediction results, and the computation efficiency. The developed model is capable of distinguishing passenger vehicles and 29 different truck body configurations with an average CCR of 83 percent. The average correct classification rate of the developed method on the test dataset was 90 percent for trucks pulling a large trailer(s).

Suggested Citation
Yiqiao Li, Koti Reddy Allu, Zhe Sun, Andre Y. C. Tok, Guoliang Feng and Stephen G. Ritchie (2021) “Truck body type classification using a deep representation learning ensemble on 3D point sets”, Transportation Research Part C: Emerging Technologies, 133, p. 103461. Available at: 10.1016/j.trc.2021.103461.