published journal article
Area of Expertise: Unspecified
conference paper
An Ensemble Approach to Truck Body Type Classification using Deep Representation Learning on 3D Point Sets
100th Transportation Research Board (TRB) Annual Meeting
Publication Date
Suggested Citation
Yiqiao Li, Koti R Allu, Zhe Sun, Andre Tok, Guoliang Feng and Stephen G. Ritchie (2021) “An Ensemble Approach to Truck Body Type Classification using Deep Representation Learning on 3D Point Sets”. 100th Transportation Research Board (TRB) Annual Meeting, Washington, DC.published journal article
Beginning the transformation
Mechanical Engineering
Publication Date
Author(s)
Suggested Citation
Mark Williams and Scott Samuelsen (2006) “Beginning the transformation”, Mechanical Engineering, 128(05), pp. 40–43. Available at: 10.1115/1.2006-may-4.Phd Dissertation
Orientation to Work and Grievance Behavior
Publication Date
Author(s)
Suggested Citation
Daniel Ralph Dalton (1979) Orientation to Work and Grievance Behavior. PhD Dissertation. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_302907437.published journal article
Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications
Transportation Research Part C: Emerging Technologies
Publication Date
Author(s)
Suggested Citation
Gerard Aguilar Ubiergo and Wen-Long Jin (2016) “Mobility and environment improvement of signalized networks through Vehicle-to-Infrastructure (V2I) communications”, Transportation Research Part C: Emerging Technologies, 68, pp. 70–82. Available at: 10.1016/j.trc.2016.03.010.published journal article
Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018–2020: Implications for Environmental Justice in the Context of Climate Change
Climate
Publication Date
Author(s)
Abstract
Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018–2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 μg/m3 showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.
Suggested Citation
Shahir Masri, Yufang Jin and Jun Wu (2022) “Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018–2020: Implications for Environmental Justice in the Context of Climate Change”, Climate, 10(10), p. 145. Available at: 10.3390/cli10100145.conference paper
Detecting Data Spoofing in Connected Vehicle based Intelligent Traffic Signal Control using Infrastructure-Side Sensors and Traffic Invariants
2023 IEEE Intelligent Vehicles Symposium (IV)
Publication Date
Author(s)
Abstract
Connected Vehicle (CV) technologies are under rapid deployment across the globe and will soon reshape our transportation systems, bringing benefits to mobility, safety, environment, etc. Meanwhile, such technologies also attract attention from cyberattacks. Recent work shows that CV-based Intelligent Traffic Signal Control Systems are vulnerable to data spoofing attacks, which can cause severe congestion effects in intersections. In this work, we explore a general detection strategy for infrastructure-side CV applications by estimating the trustworthiness of CVs based on readily-available infrastructure-side sensors. We implement our detector for the CV-based traffic signal control and evaluate it against two representative congestion attacks. Our evaluation in the industrial-grade traffic simulator shows that the detector can detect attacks with at least 95% true positive rates while keeping false positive rate below 7% and is robust to sensor noises.
Suggested Citation
Junjie Shen, Ziwen Wan, Yunpeng Luo, Yiheng Feng, Z. Morley Mao and Qi Alfred Chen (2023) “Detecting Data Spoofing in Connected Vehicle based Intelligent Traffic Signal Control using Infrastructure-Side Sensors and Traffic Invariants”, in 2023 IEEE Intelligent Vehicles Symposium (IV). 2023 IEEE Intelligent Vehicles Symposium (IV), pp. 1–8. Available at: 10.1109/IV55152.2023.10186689.published journal article
Mitigating climate change through transportation and land use policy: Opportunities and challenges
Environmental Law Reporter
Publication Date
Author(s)
Suggested Citation
Alejandro E. Camacho, Melissa L. Kelly, Nicholas J. Marantz and Gabriel Weil (2019) “Mitigating climate change through transportation and land use policy: Opportunities and challenges”, Environmental Law Reporter, 49(5), pp. 10473–10492. Available at: https://www.elr.info/articles/elr-articles/mitigating-climate-change-through-transportation-and-land-use-policy.book/book chapter
A Review of the Ridership Prediction Models for the California High Speed Rail
Publication Date
Author(s)
Suggested Citation
Samer Madanat, D. Brownstone and M. Hansen (2020) “A Review of the Ridership Prediction Models for the California High Speed Rail”, in A Review of the Ridership Prediction Models for the California High Speed Rail. CA HSR Authority and the State Senate Transportation and Housing Committee.published journal article
Design and analysis of battery-aware automotive climate control for electric vehicles
ACM Trans. Embed. Comput. Syst.
Publication Date
Author(s)
Abstract
Electric Vehicles (EV) as a zero-emission means of transportation encounter challenges in battery design that cause a range anxieties for the drivers. Besides the electric motor, the Heating, Ventilation, and Air Conditioning (HVAC) system is another major contributor to the power consumption that may influence the EV battery lifetime and driving range. In the state-of-the-art methodologies for battery management systems, the battery performance is monitored and improved. While in the automotive climate control, the passenger’s thermal comfort is the main objective. Hence, the influence of the HVAC power on the battery behavior for the purpose of jointly optimized battery management and climate control has not been considered. In this article, we propose an automotive climate control methodology that is aware of the battery behavior and performance, while maintaining the passenger’s thermal comfort. In our methodology, battery parameters and cabin temperature are modeled and estimated, and the HVAC utilization is optimized and adjusted with respect to the electric motor and HVAC power requests. Therefore, the battery stress reduces, while the cabin temperature is maintained by predicting and optimizing the system states in the near-future. We have implemented our methodology and compared its performance to the state-of-the-art in terms of battery lifetime improvement and energy consumption reduction. We have also conducted experiments and analyses to explore multiple control window sizes, drive profiles, ambient temperatures, and modeling error rates in the methodology. It is shown that our battery-aware climate control can extend the battery lifetime by up to 13.2% and reduce the energy consumption by up to 14.4%.