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Sponsor: Caltrans

Field Investigation of Advanced Vehicle Reidentification Techniques and Detector Technologies-Phase 2

Status

Complete

Project Timeline

January 1, 2001 - December 31, 2002

Principal Investigator

Stephen Ritchie

Project Team

Seri Park, Shin-Ting (Cindy) Jeng, Cheol Oh, Andre (Yeow Chern) Tok

Sponsor, Program & Award Number

Caltrans // PATH: TO 4122
(Subcontract to UC Berkeley)

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Civil and Environmental Engineering

Related Publications

research report | Mar 2005

Field Investigation of Advanced Vehicle Reidentification Techniques and Detector Technologies - Phase 2

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TRACER: In-vehicle, GPS-based, Wireless Technology for Traffic Surveillance and Management

Status

Complete

Project Timeline

January 1, 1900 - July 31, 2003

Principal Investigator

Michael McNally

Project Team

James Marca, Craig Rindt, Angela Koos

Sponsor, Program & Award Number

Caltrans // PATH: TO 4120

Team Departmental Affiliation

Civil and Environmental Engineering

Related Publications

research report | Jul 2003

TRACER: In-vehicle, GPS-based, Wireless Technology for Traffic Surveillance and Management

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conference paper | Jan 2002

The Tracer Data Collection System: Implementation and Operational Experience
Transportation Research Board 82nd Annual Meeting

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Non-myopic path-finding for shared-ride vehicles : A bi-criterion best-path approach considering travel time and proximity to demand

Status

Complete

Project Timeline

January 1, 2020 - March 31, 2021

Principal Investigator

Michael HylandMichael Hyland

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 128990496
(Subcontract to University of Southern California)
(Also see this project page)
(Also see the UC ITS page)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

The goal of this research project is to improve the operational efficiency of shared-ride mobility-on-demand services (SRMoDS). SRMoDS ranging from UberPool to micro-transit have the potential to provide travelers mobility benefits that are comparable to existing ride-hailing services without shared rides such as UberX, but at a lower cost and with fewer harmful externalities. To meet the project's goal, this study proposes a bi-criteria network pathfinding approach that considers proximity to potential future traveler requests in addition to travel time. This pathfinding approach was built on top of state-of-the-art dynamic vehicle routing and matching modules. The study tests the proposed pathfinding approach using the network of the Anaheim, CA. The results indicate that the proposed bi-criteria approach can potentially reduce both traveler waiting and in-vehicle travel time; however, the effectiveness depends on several factors. Important factors include the relative supply-demand imbalance as well as several hyperparameters in the optimization-based control policy. Moreover, the results indicate that the bi-criteria policy is only advisable when the SRMoDS vehicle has one or fewer in-vehicle passengers. Although the operational benefits found in this study are relatively small, future research efforts related to tuning hyperparameters should allow bi-criteria pathfinding to significantly improve SRMoDS.

Related Publications

research report | Apr 2021

Non-myopic pathfinding for shared-ride vehicles: A bicriteria best-path approach considering travel time and proximity to demand

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policy brief | Apr 2021

Non-myopic pathfinding for shared-ride vehicles: A bicriteria best-path approach considering travel time and proximity to demand

Read more

Software and Hardware Systems for Autonomous Smart Parking Accommodating both Traditional and Autonomous Vehicles

Status

Complete

Project Timeline

February 5, 2020 - April 1, 2021

Principal Investigator

Mohammad Al Faruque

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 129674159
(Subcontract to University of Southern California)
(Also see this project page)

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Electrical Engineering and Computer Science

Project Summary

Parking infrastructure is suffering from congestion as the number of vehicles circulating in urban areas is growing and expansion is not a cost-effective solution. In parallel, developments in autonomous vehicle technology mean that driverless vehicles are predicted to be in circulation by the 2020s and makeup 40% of vehicle travel by the 2040s. Expected benefits of autonomous vehicle travel include reduced congestion through vehicle sharing and reduced walking distance for passengers who can be dropped off chauffeur-style by autonomous vehicles. However, empty vehicle cruising, or the case in which autonomous vehicles cannot efficiently locate parking and circle instead, can potentially increase congestion. Given that this new technology has the potential to exacerbate existing congestion issues, it is necessary to develop a solution for parking congestion integrated with autonomous vehicles. Our project addresses this issue by providing a full-stack solution including sensors to monitor occupancy, Fog systems to perform local data pre- processing, and SDR radios to communicate with autonomous vehicles.

Related Publications

research report | Apr 2021

Software and Hardware Systems for Autonomous Smart Parking Accommodating Both Traditional and Autonomous Vehicles

Read more
policy brief | Mar 2021

Software and Hardware Systems for Autonomous Smart Parking Accommodating both Traditional and Autonomous Vehicles

Read more

Analysis of Activity-Travel Patterns and Tour Formation of Transit Users

Status

Complete

Project Timeline

May 1, 2020 - April 30, 2021

Principal Investigator

Michael McNally

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 131259320
(Subcontract to University of Southern California)
(Also see this project page)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation Travel Behavior, Land Use, & the Built Environment

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

This study analyzed the complex travel behavior of transit users by expanding conventional trip-based approaches by considering full activity-travel tours and patterns as basic units of analysis. A tour was defined as a sequence of trips that begins and ends at home and a pattern was defined as an entire day's sequence of activities and associated travel. We considered basic descriptive analyses to first analyze work tours-the tours that contain at least one work activity-of transit commuters and then used Structural Equation Modeling to identify the factors that determine the work tour choices. Latent Class Analysis (LCA) was then used to describe the pattern behaviors of all transit users. The results obtained using the 2017 National Household Travel Survey dataset suggested that 80 percent of work tours consisted of seven dominant tours and that work tour choice was influenced by a set of socio-demographics, built environment, and activity-travel characteristics. The LCA model suggested that transit users can be divided into five distinct classes, namely regular 9-to-5 commuters, after-work stop commuters, multimodal multiple trip makers, morning non-work travelers, and recurrent transit users, where each class had a representative activity-travel pattern. The results can help transit agencies to identify transit user groups with particular activity patterns and to consider market strategies to address user travel needs and to improve the quality of services provided.

Related Publications

published journal article | Jun 2022

A structural analysis of the work tour behavior of transit commuters
Transportation Research Part A: Policy and Practice

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policy brief | Apr 2021

Analysis of Activity Travel Patterns and Tour Formation of Transit Users

Read more
research report | Apr 2021

Analysis of Activity-Travel Patterns and Tour Formation of Transit Users

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Public Transportation , Transportation Network Companies (TNC) and Active Modes: An analysis based on 2009 and 2017 NHTS

Status

Complete

Project Timeline

May 1, 2020 - June 30, 2021

Principal Investigator

Jean-Daniel Saphores

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 131973040
(Subcontract to University of Southern California)
(Also see this project page)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

To better understand how TNCs likely impacted transit ridership before Covid-19, investigate how Covid-19 affected other modes, and elicit obstacles to a resurgence of transit after the pandemic, we analyzed data from the 2017 National Household Travel Survey, and from an IPSOS survey administered in May 2021 for this project.   Our Results show that TNCs are attracting younger, more affluent, and better educated urban households, many of whom are also served by transit. Lower-income households who reside in core urban areas served by transit are less likely to switch to TNCs. Our analysis suggests that driving but especially transit and TNCs, could see substantial drops in popularity after the pandemic ends or moves to the background like the flu. Many Hispanics, Asians, and women intend to use transit less. Although walking and biking should increase, many Hispanics, African Americans, and Asians plan on walking/biking less.   Key obstacles to a resurgence of transit include insufficient reach and frequency. African Americans and Asians have lingering health concerns, and women are more likely to worry about personal safety. In addition to addressing these concerns, effective transit policies need to be integrated into a comprehensive framework designed to achieve California's social and environmental goals.

Related Publications

policy brief | Apr 2022

Public Transportation, Transportation Network Companies (TNCs), and Active Modes

Read more
research report | Jan 2022

Public Transportation, Transportation Network Companies (TNCs), and Active Modes

Read more
published journal article | Dec 2023

Covid-19, intentions to change modes, and how they materialized - Results from a random survey of Californians
Transportation Research Part A: Policy and Practice

Read more

Transit Connectivity in Urban Areas

Status

Complete

Project Timeline

June 1, 1979 - May 31, 1980

Principal Investigator

Will Recker

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Civil and Environmental Engineering

Long Range Plan for Development and Implementation of Artificial Intelligence/Expert Systems Technology at Caltrans

Status

Complete

Project Timeline

June 1, 1987 - December 31, 1987

Principal Investigator

Stephen Ritchie

Areas of Expertise

Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Civil and Environmental Engineering

An Evaluation of the Effect of Overhead Sign Lighting of Freeway Accident Rates

Status

Complete

Project Timeline

June 15, 1987 - December 31, 1987

Principal Investigator

Will Recker

Areas of Expertise

Safety, Public Health, & Mobility Justice

Team Departmental Affiliation

Civil and Environmental Engineering

A Prototype Real-Time Expert System for Traffic Operations Center Decision Support

Status

Complete

Project Timeline

November 1, 1991 - June 30, 1993

Principal Investigator

Stephen Ritchie

Team Departmental Affiliation

Civil and Environmental Engineering

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