METRANS Partners with City of Long Beach to Launch ITS Test Bed

The National Metropolitan Transportation Center (METRANS) Tier 1 University Transportation Center is bringing next generation micro-sensor technology toward real-world implementation through an innovative partnership with the City of Long Beach Public Works Department and California State University, Long Beach (CSULB). Since 2012, METRANS has worked to develop a micro-wireless sensing system to be implanted underneath the pavement of roadways to detect and classify vehicles. METRANS has received grants from the DENSO Foundation for Smart Sensing technology education and training, and from the California Department of Transportation (Caltrans) to design a smaller, more efficient way to monitor and classify freeway and road traffic

Innovation on Job Accessibility With General Transit Feed Specification (GTFS) Data

This paper investigates job access in Los Angeles County via public transportation. We develop a measure of accessibility based on travel time, via transit, to jobs. We use open source General Transit Feed System (GTFS) data to model the transit network and interface with a variety of computing tools including JavaScript, ArcPy for ArcGIS and statistical packages to measure the number of jobs accessible from these tracts within a 60-minute commute time. The result is a method that leverages GTFS data to allow us to simulate job access with different transit investments. We measure transit job access from these tracts for three scenarios. Each scenario compares transit job access with completed or proposed additions to the Los Angeles Metro network relative to the status quo. We illustrate that job access measures can go beyond the common \u201cstatic\u201d measures of access over existing networks and be used to evaluate different transit investment scenarios. Our results suggest that the opening of the Expo Phase II light rail line increased job access in tracts that contain a higher percentage of opportunity youth populations and the opening of the proposed Crenshaw Extension promises to increase transit job access even further

Public-Private Partnerships in California: Phase II Report: Section II: Criteria for Evaluating P3 Projects

In this section of our report we develop criteria for evaluating the potential for a project to be delivered as a P3. We started by researching past attempts at P3 evaluation. We found no published research that offers a list of criteria for predicting the success of a proposed P3. Therefore, we reviewed studies of P3s and, developed a framework for evaluating P3s' potential for success. Using data from 100 P3 projects, we apply our framework to identify the attributes present in successful P3 projects. While we attempt to tease out the common attributes of successful P3s, the presence of said attributes in planned P3s will not necessarily induce nor predict success. We hope that our research will become part of a broader tool kit that public sponsors and private partners can use to evaluate potential projects' suitability as P3s

A Primer on Coastal Transportation System Resilience and Adaptation to Sea Level Rise on O\u2018ahu Using Living Shorelines and Green Infrastructure [Brief]

This primer provides a methodology to identify relevant living shorelines and green infrastructure strategies for protection of various types of tropical island coastal built environments, illustrated through three sites in Hawai\u2018i. The goal is to slow coastal erosion and reduce flooding so that coastal transportation ways can remain operational during the coming decades. The primer is intended to inform and aid decision-making by Hawai\u2018i\u2019s government planners and policy makers, private landowners, developers, design teams (urban planners, architects, landscape architects, civil engineers, transportation engineers, etc.)

Displacement and Commuting in the San Francisco Bay Area and Beyond: An Analysis of the Relationship Between the Housing Crisis, Displacement, and Long Commutes

Caltrans: 65A0674 and US DOT: 69A3551747109We use four data sets to study supercommuting in the San Francisco Bay Area and Central Valley of California. We follow previous research in defining supercommuting as commutes longer than 50 miles or 90 minutes one-way. The San Francisco Bay Area has some of the highest housing costs in the United States, and anecdotal evidence has long suggested that households might move from the Bay Area to Central Valley counties, possibly enduring long commutes if they cannot move their job at the same time. Yet evidence on a link between supercommuting and house prices has been limited by data availability. We use the data first to demonstrate that the supercommute is far from uncommon, with some Central Valley counties having supercommuting rates that approach 10 percent of all county commutes. We use data on household moves, from zip code tabulation area to zip code tabulation area (ZCTA to ZCTA), to examine how supercommuting rates at the ZCTA level are linked to flows of in-migration from the Bay Area into the Central Valley. We find evidence that suggests that ZCTAs with higher in-migration flows from the Bay Area have higher supercommuting rates

Evaluating Accessibility of Los Angeles Metropolitan Area Using Data-Driven Time-Dependent Reachability Analysis

USDOT Grant 69A3551747114This project is to investigate how accessibility of city blocks is quantified through the transport systems and real traffic flow data from the Los Angeles Metropolitan Area. The authors investigate the reachability problem and provide a solution with a functional system that is capable of visualizing the reachability map (isochrone). Unlike other studies, this approach is data-driven and does not depend on mathematical graph-theory to compute the isochrone which requires intensive computation. Instead, it focuses on directly processing the large amount of traffic flow data that the Integrated Media Systems Center at USC has collected from the Regional Integration of Intelligent Transportation Systems (RIITS) for more than 10 years under the Center\u2019s existing Archived Traffic Data Management System (ADMS) project. The reachability map construction is based on vehicle trajectories so the researchers devised the Data-Driven Trajectory Generator (DDTG), a data-driven, model-free, and parameter-less algorithm for generating realistic vehicle trajectory datasets from ADMS data. Since real world traffic is incomplete with lots of temporal and spatial missing data, the researchers studied imputation and interpolation methods to complete the dataset. Their experiments with real-world trajectory and traffic data show that the datasets generated by DDTG follow distributions that are very close to the distributions of a real trajectory dataset. Furthermore, to demonstrate the results from the proposed research, a web application was developed in which users can select a location, travel time, and the time of year to see the evaluated accessibility info in the form of an isochrone map. The outcomes of this project\u2014synthetic vehicle trajectory dataset and reachability map construction\u2014will be helpful in evaluating accessibility of city blocks for transport systems over a large area, essential for policymakers for effective city planning as well as to improve the well-being of citizens

Integrated Hazard Vulnerability Assessment and Mitigation Framework with Mixed Reality for Transportation Infrastructures

USDOT Grant 69A3551747109The USDOT's top concerns are deterioration of transportation infrastructure and how it affects overall structural performance over time. Transportation infrastructures become more vulnerable to various natural hazards and calamities owing to the structural degradation caused by physical or chemical factors. Accurate assessment of structural performance under extreme events and potential performance degradation due to any damages reported from routine infrastructure inspection is required to increase the resilience of such deteriorating transportation systems. Additionally, information about how the detected defects would impact overall infrastructure performance should be easily accessible for decision-makers and stakeholders to maintain and operate the transportation system properly. To readily check the location of significant damages, their effects on infrastructure hazard vulnerability and the projected economic and life losses from an expected hazard, an enhanced and interactive hazard risk management framework for transportation infrastructures is urgently needed. The objective of this project is to provide an integrated hazard vulnerability assessment and mitigation framework for transportation infrastructures with mixed reality (MR) and progressive vulnerability evaluation. Engineers will be able to monitor damage and degradation propagation over time, reduce hazard risk, predict the remaining lifetime of transportation infrastructure, and optimize maintenance time and cost with the help of the suggested framework. The analysis results from complex structural performance assessment will be more easily accessible and more understandable for decision-makers with the aid of MR technology

Transit-Oriented Development Opportunities Among Failing Malls

This paper explores opportunities for the redevelopment of failing regional shopping malls as Transit-Oriented Developments (TODs) to improve transit ridership, focusing on Southern California. In effect, the study suggests an alternative to the typical sequence of first providing transit infrastructure and then changing land uses and densities to develop a TOD around new transit stations. Instead, the study suggests that failing shopping malls can provide the footprint for their redevelopment as TODs that could then be linked to transit lines

Impacts of Connected and Autonomous Vehicles on the Performance of Signalized Networks: A Network Fundamental Diagram Approach

USDOT Grant 69A3551747109Many eco-driving strategies through speed control using constrained optimization algorithms have proven effective on signalized roads. However, heuristic speed limit control strategies and understanding of their overall performance across congestion levels remain an unexplored topic. In this work, we systematically study the performance of an eco-driving strategy based on Vehicle-to-Infrastructure (V2I) communication via the advisory speed limit (ASL), a speed limit designed for individual vehicles based on the idea of making vehicles enter signalized intersections at saturated headway intervals. The theoretical performance of our algorithm to vehicle trajectories is analyzed across different congestion levels. By simulating with the BA Newell\u2019s car-following model, the simplified Gipps model, and the Krauss model, calculated network fundamental diagrams (NFDs) and results of the Virginia Tech Microscopic Energy and Emission (VT-micro) model reveal an improvement in system mobility by nearly 10% and a reduction in fuel consumption by up to about 45% in the saturated condition. We further consider different market penetration rates (MPRs) and ASL implementation areas and show our algorithm can lead to about 35% fuel consumption reduction even with a 10% MPR. We recommend an ASL implementation area of about 100 meters, which can well balance the algorithm efficacy and computation cost

Optimum Routing of Freight in Urban Environments Under Normal Operations and Disruptions Using a Co-Simulation Optimization Control Approach [Research Brief]

DTRT13-G-UTC57The complexity and dynamics of multimodal freight transportation together with the unpredictability of incidents, disruptions and demand changes make the optimum routing of freight a challenging task. Optimum routing decisions in a multimodal transportation rely on the estimation of the dynamical states of the multimodal traffic network