research report

Analyzing the 2012 California Household Travel Survey using R

Publication Date

February 11, 2016

Author(s)

Craig Rindt, Suman Mitra, Jean-Daniel Saphores

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Abstract

The 2010-12 CHTS, which resulted from a statewide, collaborative effort, enabled the collection of travel information from 42,560 Californian households. This rich dataset has helped update regional and statewide travel and will help update environmental models.In 2014, the Institute of Transportation Studies at Irvine (ITS) and Caltrans initiated the “Enhancing the Value of the 2010-12 California Household Travel Survey (CHTS)” contract. This contract was motivated by the idea that potential value of the CHTS is not always well understood by Caltrans staff and that some Caltrans staff from the Office of Travel Forecasting and Analysis may benefit from updating their knowledge of statistical modeling to comfortably query CHTS data and to estimate some common transportation econometrics models.This report provides numerous examples of how to perform various types of statistical analysis on the CHTS. In chapter 2, we discuss the R language and environment for statistical analysis, which was chosen as the primary analysis tool for this project. The following chapters provide specific examples of statistical analysis taken from the contract tasks. In all cases, the actual R code used to perform the analysis is provided, along with detailed discussion of the methods imployed. Chapter 3 describes the Task 1 diagnostic review of the CHTS. In chapter 4, we demonstrate the computation of statistical weights for various subpopulations in the CHTS—a critical component of any analysis involving the CHTS. In chapter 5, we cover the creation of a “linked trip” dataset, which provides a means for analyzing CHTS data in a manner that is compatible with conventional 4-step, trip based models. In chapter 6, we describe the creation of CHTS summary tables generated as part of task 3 work. Finally, chapter 7 describes the solution of a number of statistical queries that were answered under task 4 statistical support tasks.

Suggested Citation

Craig R. Rindt, Suman K. Mitra and Jean-Daniel Saphores (2016) Analyzing the 2012 California Household Travel Survey using R. Final Report. Institute of Transportation Studies, Irvine. Available at: https://escholarship.org/uc/item/9n42t87s.

conference paper

The Rise of Self-Driving: Impacts on the Number, Size, and Location of Warehouses

Proceedings, 104th Annual Meeting of the Transportation Research Board

Publication Date

January 1, 2025

Author(s)

Lu Xu, Dewei Xiao, Saphores， Jean-Daniel

Abstract

With the arrival of autonomous driving technology, the logistics industry, particularly warehousing, is facing unprecedented changes. This study aims to explore how the expected drop in freight transportation costs due to truck automation may affect the number, size, and location of warehouses in a simple framework built around a monocentric city that receives supplies from a “port” located southwest of the city center. We formulated and solved a mixed-integer program that combine a static facility location model with a monocentric city model that provides simple estimates of population density and urban land rents. We found that as freight cost reduction increases from 0% to 90%, the optimum number of warehouses drops from 7 to 1, the average warehouse size expands from 8,125 to 10,833 square feet, drayage truck mileage drops by up to 24% while delivery truck mileage soars by up to 147%, for a net mileage increase of up to 18%. Our methodology and findings should be of interest to warehouse operators, retailers, and policymakers concerned with land use and environmental quality.

Suggested Citation

Lu Xu, Dewei Xiao and Saphores, Jean-Daniel (2025) “The Rise of Self-Driving: Impacts on the Number, Size, and Location of Warehouses”, in Proceedings, 104th Annual Meeting of the Transportation Research Board. Washington, D.C..

conference paper

SLAMSpoof: Practical LiDAR Spoofing Attacks on Localization Systems Guided by Scan Matching Vulnerability Analysis

IEEE International Conference on Robotics and Automation

Publication Date

February 19, 2025

Author(s)

Rokuto Nagata, Kenji Koide, Yuki Hayakawa, Ryo Suzuki, Kazuma Ikeda, Ozora Sako, Qi Alfred Chen, Takami Sato, Kentaro Yoshioka

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Abstract

Accurate localization is essential for enabling modern full self-driving services. These services heavily rely on map-based traffic information to reduce uncertainties in recognizing lane shapes, traffic light locations, and traffic signs. Achieving this level of reliance on map information requires centimeter-level localization accuracy, which is currently only achievable with LiDAR sensors. However, LiDAR is known to be vulnerable to spoofing attacks that emit malicious lasers against LiDAR to overwrite its measurements. Once localization is compromised, the attack could lead the victim off roads or make them ignore traffic lights. Motivated by these serious safety implications, we design SLAMSpoof, the first practical LiDAR spoofing attack on localization systems for self-driving to assess the actual attack significance on autonomous vehicles. SLAMSpoof can effectively find the effective attack location based on our scan matching vulnerability score (SMVS), a point-wise metric representing the potential vulnerability to spoofing attacks. To evaluate the effectiveness of the attack, we conduct real-world experiments on ground vehicles and confirm its high capability in real-world scenarios, inducing position errors of $geq$4.2 meters (more than typical lane width) for all 3 popular LiDAR-based localization algorithms. We finally discuss the potential countermeasures of this attack. Code is available at https://github.com/Keio-CSG/slamspoof

Suggested Citation

Rokuto Nagata, Kenji Koide, Yuki Hayakawa, Ryo Suzuki, Kazuma Ikeda, Ozora Sako, Qi Alfred Chen, Takami Sato and Kentaro Yoshioka (2025) “SLAMSpoof: Practical LiDAR Spoofing Attacks on Localization Systems Guided by Scan Matching Vulnerability Analysis”, in IEEE International Conference on Robotics and Automation. arXiv. Available at: https://ics.uci.edu/~alfchen/pubs/ken_icra25.pdf (Accessed: August 21, 2025).

conference paper

Public Transit Use in Pandemic Year 2022: Which Groups Changed Usage?

Proceedings, 104th Annual Meeting of the Transportation Research Board

Publication Date

January 1, 2025

Author(s)

Rezwana Rafiq, Michael McNally

Abstract

The outbreak of the COVID-19 pandemic and its subsequent travel restrictions imposed significant impacts on many aspects of our lives and infrastructures, including an unprecedented decrease in public transit service and ridership. Little is known about specific changes in transit use during the pandemic compared to before using national-level data. In this context, we characterized transit users who changed their public transit use and identified the underlying socio-demographics, location, and trip characteristics that affect these changes using data from the recently published 2022 National Household Travel Survey (NHTS). A logistic regression model developed suggests that those with a higher tendency to reduce transit use after the pandemic were females, unemployed, highly educated, teleworkers, driving license holders, couples without children, those forced to reduce travel due to conditions or disability, and those living in denser areas. In addition, users from low-income households showed greater reductions in transit use than those from high-income families. Transit agencies and planning organizations can use the findings of this study to identify transit users based on revealed changes in transit use after the pandemic to formulate appropriate operational and management strategies to address emerging public transit needs.

Suggested Citation

Rezwana Rafiq and Michael G. McNally (2025) “Public Transit Use in Pandemic Year 2022: Which Groups Changed Usage?”, in Proceedings, 104th Annual Meeting of the Transportation Research Board. Washington, D.C..

MS Thesis

Impacts of Accidents on the Analysis of Measures to Reduce Vehicular Emissions

Publication Date

January 1, 2015

Author(s)

Karen Sujata

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Abstract

The Long Beach Freeway Corridor Improvement Project was started to address concerns regarding increasing air pollutant emissions and traffic congestion, which are partly due to increases in truck volumes and high accident rates. In addition to these efforts, a non-profit organization called PierPass was created in 2005 by the marine terminal operators at the ports of Los Angeles and Long Beach. The PierPass program aimed to alleviate congestion, security and air quality issues experienced by the ports and freeways by incentivizing freight movements during off-peak hours. This paper explores whether it is important to model accidents when analyzing the environmental benefits of policies designed to reduce air pollution from trucks with an application to PierPass. A microscopic traffic simulation model of the freeway network containing the I-710 freeway was utilized to simulate truck accidents under uniquely identified scenarios based on frequent conditions. Then, vehicular emissions for seven common air pollutants were calculated and compared to a no-accident scenario to quantify the effects of accidents on pollutant emission. Results showed that the introduction of incidents slightly increased the average vehicular speeds and slightly decreased the total amount of emissions; however, the effect of incidents may be more pronounced on a network that is not already known to be heavily congested.

Suggested Citation

Karen Sujata (2015) Impacts of Accidents on the Analysis of Measures to Reduce Vehicular Emissions. MS Thesis. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991022552269704701.

MS Thesis

Applying Smart Grid technologies to the secondary distribution system / by Renee Gail Cinar.

Publication Date

January 1, 2014

Author(s)

Renee Cinar

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Abstract

Today’s aging electric delivery infrastructure is undergoing an extreme makeover. The current system has inefficiencies, is congested and unable to meet future power reliability, quality, sustainability (e.g., more renewable power) and security needs. The massive effort to modernize the nation’s electricity delivery system is collectively known as the “Smart Grid.” Transition to a smarter grid will occur over time. This research addresses one area of electric power system modernization, namely the impacts that high penetrations of distributed energy resources (DER), such as solar and batteries, and plug-in electric vehicles (PEVs) could have on the distribution system by (1) evaluating the effect of introducing large amounts of DER and PEV charging on a secondary distribution circuit and (2) developing, applying and evaluating smart grid management scenarios which can reduce consumer electricity costs and flatten residential load profiles. The improved load profiles presented herein demonstrate that traditional residential load profiles can be purposefully reshaped when rooftop solar, energy storage, and plug-in electric vehicles are introduced into the circuit. Through various battery charging and discharging scenarios and controlled electric vehicle charging, residential loads can be reduced to almost zero, flattened, or behave as a distributed generator. By allowing excess solar generation to flow back onto the grid or dispatching batteries during peak load times, the load profile of an individual home or secondary distribution transformer can be altered in a manner that benefits the distribution grid.

Suggested Citation

Renee Gail Cinar (2014) Applying Smart Grid technologies to the secondary distribution system / by Renee Gail Cinar.. MS Thesis. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_1640768890.

Phd Dissertation

Essays on the competitive dynamics of innovation and product quality / Michael Stefan Mills.

Publication Date

January 1, 2014

Author(s)

Michael Mills

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Abstract

Firms compete through means other than pricing and advertising. In particular, firms compete through manipulating the quality of their products. In the pharmaceutical industry, firms compete by innovating to create a better quality medicine. The first chapter examines pharmaceutical firms’ strategic response to innovate. The comparison of words used in job advertisements to words used in the International Classification of Diseases are analyzed to measure the amount of innovative activity a firm conducts in a given disease category. From this novel dataset, the results indicate that a firm increases its innovative activity due to its competitors’ increase in innovative action. The second chapter extends a model with vertically differentiated products to include a “brand” firm’s incentive to market a medium quality product (pseudo-generic) to compete with their original high quality product and a competitor’s low quality product. Under certain assumptions of consumer heterogeneity, an incumbent firm will market a pseudo-generic only when it can deter the entry of multiple competitors. The third chapter looks at quality competition in the airline industry by analyzing the changes in the total flight frequency for a city-pair due to the merger of two airlines. The results suggest that a merger can decrease flight frequency by as much as 97 flights per month on some routes. The decreases in flight frequency are almost entirely due to the merger removing a competitor (one of the merging partners) from the route. Consequently, the total change in frequency on most routes is less severe or insignificant all together

Suggested Citation

Michael Stefan Mills (2014) Essays on the competitive dynamics of innovation and product quality / Michael Stefan Mills.. PhD Dissertation. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991001203329704701.

MS Thesis

An approach to subarea identification for corridor management analysis

Publication Date

January 1, 2009

Author(s)

David Nieto

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Suggested Citation

David Barral. Nieto (2009) An approach to subarea identification for corridor management analysis. MS Thesis. University of California, Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/17uq3m8/alma991023089429704701.

policy brief

The Missing Link in Automated Vehicle Safety: Projected Braking and Realistic Driving Behavior

Publication Date

January 1, 2025

Associated Project

Examining the Safety and Efficiency Implications of Several Autonomous Car-following Models

Author(s)

Wenlong Jin

Policy Brief

UC-ITS-2022-39

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data Safety, Public Health, & Mobility Justice

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Abstract

As more automated vehicles (AVs) gradually appear on our roads, they must be able to safely interact with human drivers as well as existing infrastructure designed with human drivers in mind. Current car-following computer models—which determine how AVs adjust their speed and position relative to other vehicles—often struggle to replicate human driving patterns. This deficiency could lead to unpredictable AV behavior, potentially increasing crash risks, disrupting traffic flow, and creating problems at traffic lights and intersections designed for human drivers. If AVs brake much earlier or later than humans, drivers may be caught in ‘dilemma zones’ — unable to safely stop or proceed through the intersection. To address these challenges, the research team conducted a comprehensive analysis of existing car-following models and developed a novel multi-phase projection-based model that ensures safety while exhibiting human-like driving characteristics.

Suggested Citation

Wen-Long Jin (2025) The Missing Link in Automated Vehicle Safety: Projected Braking and Realistic Driving Behavior. Policy Brief UC-ITS-2022-39. UC ITS / ITS-Irvine. Available at: https://doi.org/10.7922/g2j101j6 (Accessed: November 3, 2025).

Related Publications

Preprint Journal Article | May 2025

Provably safe and human-like car-following behaviors: Part 1. Analysis of phases and dynamics in standard models

MS Thesis

The Political Process of Regional Transportation Finance: A study of regional coordination in the polycentric and politically fragmented San Francisco Bay Area

Publication Date

January 1, 2011

Author(s)

David Weinreich

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Abstract

Over the last 20 years, transportation finance in California has become increasingly balkanized. State and federal gas tax rates have not kept up with inflation, and, increasingly, counties have raised their own sales taxes to improve local transportation facilities, resulting in more county-level decisions and less regional coordination. Yet current literature indicates that regional transportation planning is a necessary element in reducing VMT and our carbon footprint. Looking at a unique instance where the 26 transit operator San Francisco Bay Area was able to develop a single transportation financing plan funded by a $1 increase in bridge tolls, this paper seeks to learn how a regional funding proposal can happen in a polycentric and politically fragmented region such as the Bay Area. Using a combination of interviews and archival research, this paper discusses the multi-stage process through which the proposal passed; makes conclusions as to what was necessary for its success; and makes recommendations as to how feasible it would be for other regions to consider similar regional funding methods. It expands the concept of the political entrepreneur to the multi-state process of passing a regional transportation finance measure, and concludes that the current county sales tax law is not sufficient to accommodate regional transportation funding proposals, without direct legislative approval and the strong initiative of an entrepreneur. Absent a change in state law, regional measures are likely to be infrequent—dependent on a political entrepreneur to take the initiative needed to pass them.

Suggested Citation

David Philip Weinreich (2011) The Political Process of Regional Transportation Finance: A study of regional coordination in the polycentric and politically fragmented San Francisco Bay Area. MA Thesis. UC Irvine. Available at: https://uci.primo.exlibrisgroup.com/permalink/01CDL_IRV_INST/u4evf/cdi_proquest_journals_874289517.