Data

Evaluating the Effects of a Classroom-based Bicycle Education Intervention on Bicycle Activity, Self-Efficacy, Personal Safety, Knowledge, and Mode Choice

Nachman, Elizabeth R.
Rodríguez, Daniel A.
2019

This study provides an evaluation of the impacts of classroom-based adult bicycle education on bicycling activity, confidence and competency self-perceptions while bicycling, knowledge of the bicycling rules of the road, and mode choice in a sample of residents of the San Francisco Bay Area in the US. Changes were measured with self-administered surveys completed before and six weeks after the course intervention. Self-reported data were validated using objective data collected using the Ride Report app. We used multivariable regression analyses to examine changes in self-...

Social Disparities in Flood Exposure and Associations with the Built Environment in 47,187 Urban Neighborhoods in Eight Latin American Countries

Kephart, JL
Bilal, U
Ferreira, A
Gouveia, N
Rodriguez, DA
Barbieri, IS
Miranda, J
Roux, AV Diez
2023
BACKGROUND AND AIM: Climate change is expected to greatly increase population exposure to flooding and related health impacts, particularly in urban areas of the Global South. We aimed to examine within-city social disparities in exposure to flooding within 326 Latin American cities and associated features of the neighborhood environment. METHOD: We used a high spatial resolution dataset of historical flood events from 2000-2018 to describe flood exposure at the neighborhood level for all cities with 100,000+ residents in eight Latin American countries (Argentina, Brazil, Chile, Colombia,...

Tracking the State and Behavior of People in Response to COVID-19 Through the Fusion of Multiple Longitudinal Data Streams

Bouzaghrane, MA
Obeid, H
Hayes, D
Chen, M
Li, M
Parker, M
Rodriguez, D
Frick, K
Sengupta, R
Walker, J
2023

The changing nature of the COVID-19 pandemic has highlighted the importance of comprehensively considering its impacts and considering changes over time. Most COVID-19 related research addresses narrowly focused research questions and is therefore limited in addressing the complexities created by the interrelated impacts of the pandemic. Such research generally makes use of only one of either (1) actively collected data such as surveys, or (2) passively collected data from sources such as mobile phones or financial transactions. So far, only one other study collects both active and passive...

Comparing the Relative Efficacy of Generalized Estimating Equations, Latent Growth Curve Modeling, and Area Under the Curve with a Repeated Measures Discrete Ordinal Outcome …

Rodriguez, Daniel
Verma, R
Upchurch, J
2024
Researchers are often interested in how changes in one variable influence changes in a second variable, requiring the repeated measures of two variables. There are several multivariate statistical methods appropriate for this research design, including generalized estimating equations (GEE) and latent growth curve modeling (LGCM). Both methods allow for variables that are not continuous in measurement level and not normally distributed. More recently, researchers have begun to employ area under the curve (AUC) as a potential alternative when the nature of change is less important than the...

Rail Transit Ridership Changes and COVID-19: Lessons from Station-Area Characteristics

Li, M
Rodriguez, DA
Pike, S
McNally, M
2024

The COVID-19 pandemic has had a significant impact on public transit ridership in the United States, especially for rail transit. Land use, development density, and the pedestrian environment are strongly associated with station-level transit ridership. This study examines how these characteristics affect transit ridership pre- and post-COVID and how they differ across station types based on longitudinal data for 242 rail stations belonging to Bay Area Rapid Transit, San Diego Metropolitan Transit System, Sacramento Regional Transit, and LA Metro between 2019 and 2021. We found...

Empirical Analysis of Traffic Breakdown Probability Distribution with Respect to Speed and Occupancy

Chow, Andy H.F.
Lu, Xiao-Yun
Qiu, Tony Z.
2009

From an operation viewpoint, traffic breakdown (from free-flow) was defined as when the average speed of traffic drops below a certain threshold. It is known that traffic breakdown is a stochastic phenomenon which can happen even when the traffic flow is below the capacity. The capacity has many definitions, such as that in HCM or the average of maximum daily flow. This study investigates the probability of breakdown at certain locations of freeway. The motivation is to find a practical capacity for each freeway section for active traffic control/operation purposes, which could be...

Longitudinal State Estimation For A Four-vehicle Platoon

Merz, A. W.
1995

In this report, the estimation of longitudinal states in a four-wheel platoon is derived, discussed and illustrated numerically. The general procedure in the process is the use of dynamic equations and data, for finding the estimates and root means squared errors in the estimated of the states for each vehicle. The nonlinear dynamics of the platoon are those in the computer code developed by U.C. Berkeley. Several additional parameters require numerical specification, including data and process noise levels. The control algorithm is applied to the estimates rather than to the actual states...

Hybrid Data Implementation: Final Report for Task Number 3643

Khan, Sakib Mahmud, PhD
Fournier, Nicholas, PhD
Mauch, Michael, PhD
Patire, Anthony D, PhD
Skabardonis, Alex, PhD
2020

This report investigates how Caltrans may incorporate third-party vendor data into its established system for performance measurement to improve accuracy of vehicle hours of delay (VHD) estimates and to enable smarter deployment of point-based sensors, such as loops. Methods are evaluated to project data from multiple sources, including multiple vendors and internal data feeds, onto the same domain of analysis so as to compute performance metrics with high fidelity. The recommended VHD estimation method depends on the infrastructure type and the data available. Overall a hybrid approach...

Using Cooperative Adaptive Cruise Control (CACC) to Form High-Performance Vehicle Streams:Simulation Results Analysis

Liu, Hao
Kan, Xingan (David)
Shladover, Steven E.
Lu, Xiao-Yun
2018

This document contains detailed simulation results analysis and discussion for the Federal Highway Administration (FHWA) Exploratory Advanced Research (EAR) project entitled Using Cooperative Adaptive Cruise Control (CACC) to Form High-Performance Vehicle Streams. The objective of this study is to obtain authoritative predictions of traffic impacts of ACC and CACC at various market penetrations and define the CACC operation strategies that create the most capacity and throughput improvement in the freeway traffic stream. A microscopic traffic simulation environment has been developed for...

Cooperative Intersection Collision Avoidance System (CICAS): Signalized Left Turn Assist and Traffic Signal Adaptation

Misener, Jim
Barnes, M.
Chan, Ching-Yao
Cody, Delphine
Dickey, Susan
Goodsell, R.
Gordon, Tim
Kim, Zu Whan
Kuhn, Tom
Lian, Thang
Nelson, David
Nowakowski, Christopher
Nubukawa, K.
Sharafsaleh, Ashkan
Shladover, Steven
Spring, John
VanderWerf, Joel
Zhang, Wei-Bin
Zhang, Liping
Zhou, Kun
2010

The Cooperative Intersection Collision Avoidance (CICAS) program is a multi-year, cooperative research program including federal, state, academic, and industry partners. The goal of the research program is to use ITS technologies to address the problem of intersection crashes. The program is funded through an 80/20 cost share, typically split between the U.S. Department of Transportation (D.O.T.) and a local state D.O.T. The program began in 2003, and has been divided into three functional segments based on crash type. The largest programmatic segment is CICAS-V (Violation) which is led by...