Skip to content
The Institute of Transportation Studies at UC Irvine
  • About
    • Leadership
    • Affiliated Centers
    • IT Resources
    • ITS-Irvine Policies
    • Contact
  • Research
    • Areas of Expertise
    • Publications
    • Projects
    • Requests for Proposals
    • ISERT2026
    • TRIP Program
    • PRIME Program
  • Education
  • People
    • Researchers
    • Administrative Staff
    • Current Students
    • PhD Graduates
    • Past Faculty Associates
  • News & Events
    • News
    • Events
  • About
    • Leadership
    • Affiliated Centers
    • IT Resources
    • ITS-Irvine Policies
    • Contact
  • Research
    • Areas of Expertise
    • Publications
    • Projects
    • Requests for Proposals
    • ISERT2026
    • TRIP Program
    • PRIME Program
  • Education
  • People
    • Researchers
    • Administrative Staff
    • Current Students
    • PhD Graduates
    • Past Faculty Associates
  • News & Events
    • News
    • Events

Sponsor: Caltrans

Proposal for Advancing the Value of the California Household Travel Survey to Caltrans

Status

Complete

Project Timeline

June 30, 2014 - September 30, 2015

Principal Investigator

Jean-Daniel Saphores

Project Team

Craig Rindt, Suman Mitra

Sponsor & Award Number

Caltrans: 74A0777

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

University of California, Irvine,  Institute of Transportation Studies proposes to provide support to Caltrans to enhance the value of the 2010-12 California Household Travel Survey (CHTS). 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 models, but it could also inform Caltrans planning efforts. As such it should be of interest not only to various state and transportation planning agencies across California, but also to staff from the California Department of Transportation (Caltrans). However, the potential value of the CHTS is not always well understood by Caltrans staff. Moreover, 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. In this context, we are proposing to: 1) perform a systematic diagnostic review of the 2010-12 CHTS database for unlikely observations; 2) interview headquarters and district Caltrans staff in three (3) selected Caltrans Districts to better understand how they could benefit from using 2010-12 CHTS data and to help promote the use in their work of CHTS data; 3) provide hands-on statistical training and consulting to selected Caltrans staff in the Office of Travel Forecasting and Analysis in Sacramento and possibly to some district Caltrans staff (for a maximum of twelve (12) staff); 4) provide on-call statistical support to Caltrans staff from the Office of Travel Forecasting and Analysis; and 5) create a reference book of useful statistical commands based on actual case studies to make it easier to put the 2010-12 CHTS to work for Caltrans staff. The work we are proposing will start during 2014 with visits of three (3) district offices to explore how CHTS data could be promoted to planning and modeling staff in Caltrans districts.  Once there is a clear understanding of District and HQ staff needs, training material will be developed to deliver training modules to staff in the Office of Travel Forecasting and Analysis.  The content of the training modules will be determined according to the findings from Headquarters (HQ) and District office visits.  Training will be delivered at UC Irvine and in Sacramento.  Finally, over the course of this project, a reference book of statistical techniques with Caltrans-based examples will be compiled

Related Publications

research report | Sep 2016

Analyzing the 2012 California Household Travel Survey using R: Summary

Read more

An Activity-based Toolbox for Planning Applications with Special Relevance to Transit

Status

Complete

Project Timeline

May 1, 2015 - January 30, 2016

Principal Investigator

Will Recker

Project Team

Neda Masoud, Karina Hermawan

Sponsor, Program & Award Number

Caltrans // UCTC Caltrans Match: 8798
(Subcontract to UC Berkeley)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

This research proposes to develop a comprehensive activity based travel demand forecast model that integrates different variations of discrete choice models, mathematical programming models of activity scheduling and travel choice, fuzzy concepts and machine learning techniques. The research is designed with a main goal of producing an activity-based travel demand toolbox that can be used in practical planning applications. As envisioned, the toolbox will enable users to predict activity patterns and trip chains at both disaggregate and aggregate levels for a study region, analyze public transportation market share, and evaluate the impacts of different policies on travel pattern of individuals. Core codes of the toolbox will be in Matlab and Python, and use Visual Basic for the user interface. The codes will be standalone executable files that have minimum software requirements for execution. As a demonstration of the toolbox, the project will apply the procedures to examine potential modifications to transit services provided by the Orange County Transportation Authority (OCTA). Estimation and validation of the forecast tool will be based on a set of 78 household samples in Orange County, drawn from the California Household Travel Survey data. Scenarios for analysis will be developed in consultation with OCTA.

Related Publications

policy brief | May 2019

An Activity-based Toolbox for Planning Applications

Read more

Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

Status

Complete

Project Timeline

May 1, 2015 - May 1, 2016

Principal Investigator

r-jayakrishnanR. (Jay) Jayakrishnan

Project Team

Daisik (Danny) Nam, Jiangbo (Gabe) Yu, Roger Lloret-Batlle, Neda Masoud, Sunghi (Sunny) An, Dingtong Yang

Sponsor, Program & Award Number

Caltrans // UCTC Caltrans Match: 65A0529 TO 025
(Subcontract to UC Berkeley)

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

Peer-to-peer ridesharing services are a recently emerging travel option that can help accommodate the growth in urban travel demand, and alleviate some of the current problems such as excessive vehicular emissions. Prior ridesharing projects suggest that the demand for ridesharing is usually shifted from transit, while its true benefits are obtained only if the demand shifts from private autos. This project studies the potential of efficient real-time ride-matching algorithms to augment demand for transit by reducing private auto use. The Los Angeles Metro red line is considered for the case study, since it has recently shown declining ridership. A mobile application with an innovative ride-matching algorithm will be developed as a decision support tool that suggests routes that combine ridesharing and transit. The app also facilitates peer-to-peer communications of users via smart phones. For successful ride-sharing, strategically selecting transit stations is crucial, along with the pricing structure for rides. These can be adjusted dynamically based on the feedback from the app-users. A parametric study of the application of real-time ride-matching algorithms using simulated demand in conjunction with the SCAG model for the selected study area is proposed, along with a limited field study of the peer-to-peer use of the apps.

Related Publications

research report | May 2016

Promoting peer-to-peer ridesharing services as transit system feeders

Read more

Infill Dynamics in Rail Transit Corridors; Challenges and Prospects for Integrating Transportation and Land Use Planning

Status

Complete

Project Timeline

May 12, 2015 - July 7, 2016

Principal Investigator

Jae Hong Kim

Project Team

Wan-Tzu (Ashley) Lo, Jaewoo Cho, Nicholas Branic, Xiaoxia Shi, Andrea Hoff, Yanyan Zhang, Alison Walker, Huy (Joey) Ly, Doug Houston

Sponsor, Program & Award Number

Caltrans // UCTC Caltrans Match: 65A0528 TO 018 A01
(Subcontract to UC Berkeley)

Areas of Expertise

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

Team Departmental Affiliation

Urban Planning and Public Policy

Project Summary

Local and regional planning entities are directing substantial employment and housing growth into transit corridors to achieve the sustainability goals of California Senate Bill 375. Despite the substantial focus on transit investment and infill growth, our knowledge base for understanding near-transit infill land use dynamics remains limited. This research will shed light on whether existing plans will be sufficient to encourage favorable land use changes which reorient growth into transit corridors by examining two critical dynamic processes: (1) transit system improvements/expansions and (2) associated land use changes, particularly infill and redevelopment dynamics. More specifically, the project will (a) develop a historical geo-database of the dynamic changes in transit systems and land use over the last two decades (i.e., 1990s and 2000s) in southern California, (b) identify key transit system and policy factors that can shape and re-shape land use patterns in surrounding areas, and (c) analyze infill and redevelopment dynamics associated with transit system improvements/expansions using a parcel- based land use change model. Results will provide insights into the expected nature and magnitude of impacts of urban rail transit system improvements/expansions on infill and growth, and will support on-going efforts to more effectively integrate transportation and land use planning.

Related Publications

research report | Jun 2016

Infill Dynamics in Rail Transit Corridors: Challenges and Prospects for Integrating Transportation and Land Use Planning

Read more

CTM-based optimal signal control strategies in urban networks

Status

Complete

Project Timeline

March 18, 2015 - January 30, 2017

Principal Investigator

Wenlong Jin

Project Team

Qi-Jian Gan, Shizhe Shen, Xuting Wang, Felipe De Souza, Qinglong (Louis) Yan, Suman Mitra

Sponsor, Program & Award Number

Caltrans // UCTC Caltrans Match: 8760
(Subcontract to UC Berkeley)

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

The objective of this project is to develop optimal signal control strategies in urban networks based on Cell Transmission Model. Traffic in urban networks is getting more and more congested due to the rapid increase in travel demand. Most of the prevailing signal control strategies are developed for uncongested traffic conditions and cannot work properly when traffic gets congested during peak periods. Furthermore, most of them either consider average vehicle arrival rates or model vehicles as queues, and thus, they fail to capture important traffic flow characteristics such as kinematic waves and fundamental speed-density (or flow-density) relations on a road link. To tackle these problems, in this project, we introduce the cell transmission model (CTM) to simulate the evolution patterns of vehicles on a road link. Due to the complexity in the time-discrete control signals at signalized intersections, we develop time-continuous junction models which can correctly approximate the discrete junction outflows under different traffic conditions, capacity constraints, and signal settings. For CTM with the continuous approximate models, we formulate a nonlinear optimal control problem, in which signal settings (green splits) are control variables, and the network flow-rate in the macroscopic fundamental diagram is the objective function. This project provides a systematical framework to determine optimal signal settings for urban networks. Insights from this project can help engineers and policy makers better understand of how the signal settings, route choices, and demand patterns impact the network performance.

Related Publications

research report | Jun 2017

CTM-based optimal signal control strategies in urban networks

Read more

A Unified Framework for Analyzing and Designing Signals for Stationary Arterial Networks

Status

Complete

Project Timeline

May 19, 2015 - January 31, 2017

Principal Investigator

Wenlong Jin

Project Team

Xuting Wang, Yue Zhou, Qinglong (Louis) Yan, Candy Kwan, Shizhe Shen, Anupam Srivastava, Shangyou Zeng

Sponsor, Program & Award Number

Caltrans // UCTC Caltrans Match: UTC Agreement 65A0528
(Subcontract to UC Berkeley)

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

In this research, we propose a unified framework for (1) analyzing dynamical and stationary patterns subject to different control strategies; and (2) designing control strategies based on understanding of traffic patterns. We will describe the evolution of traffic dynamics in a signalized network by the Link Transmission Model (Yperman et al., 2006; Yperman, 2007), which, together with Newell's simplified kinematic wave model (Newell, 1993), is another formulation of the network kinematic wave theory based on the LWR model. In (Jin, 2014), two continuous formulations of LTM were derived from the Hopf-Lax formula for the Hamilton- Jacobi equation of the LWR model. Then we will (1) analytically derive macroscopic fundamental diagrams (MFD) for stationary traffic patterns with different network topologies, road conditions, driving behaviors, and signal settings; (2) quantify congestion mitigation effects of different signal settings, including cycle lengths, green splits,  and offsets, as well as speed limits and road lengths; (3) formulate an optimization problem to find optimal road, speed limit, and signal control parameters under certain demand levels, and (4) develop a set of simple decision-support tools for arterial network improvement.

Related Publications

research report | May 2017

A unified framework for analyzing and designing for stationary arterial networks

Read more

Investigation of Truck Data Collection using LiDAR Sensing Technology along Rural Highways

Status

Complete

Project Timeline

May 1, 2020 - September 30, 2021

Principal Investigator

Stephen Ritchie

Project Team

Andre (Yeow Chern) Tok, Craig Rindt, Koti Allu, Zhe (Jared) Sun

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 131973292
(Subcontract to University of Southern California)
(Also see this project page)

Areas of Expertise

Freight, Logistics, & Supply Chain Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

LiDAR is an emerging technology that can provide detailed point-cloud measurements of objects. The purpose of this study is to investigate the use of LiDAR technology for accurate classification of trucks according to the established FHWA scheme along rural highway corridors as an alternative to in-pavement detector infrastructure - such as inductive loop sensors and piezo-based automatic vehicle classifiers which is not widely deployed along many rural highway corridors - and temporary sensors such as pneumatic road tubes, which expose workers to live traffic. This research will also investigate anonymous tracking of trucks with LiDAR across two locations using advanced algorithms. This can be used to measure spatial activity and travel time performance of trucks along instrumented corridors.

Related Publications

working paper | Aug 2020

Lidar Based Reconstruction framework for Truck Surveillance

Read more
research report | Sep 2021

Investigation of Truck Data Collection using LiDAR Sensing Technology Along Rural Highways

Read more

Impacts of connected and autonomous vehicles on the performance of signalized networks: A network fundamental diagram approach

Status

Complete

Project Timeline

March 15, 2020 - December 31, 2021

Principal Investigator

Wenlong Jin

Project Team

Ximeng Fan

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 131007028SCON-00002365
(Subcontract to University of Southern California)
(Also see this project page)

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

The objective of this research is to evaluate the impacts of connected and autonomous vehicles (CAVs) on the performance of signalized networks at the aggregate level. CAVs are expected to improve alleviate traffic congestion, but their impacts are usually evaluated at the microscopic level, for example, through the design of optimal vehicle trajectories or optimal operation of individual intersections. In this proposal, we aim to develop a new performance evaluation framework through network fundamental diagrams (NFD), which capture the relationship between the average flow-rate and density at the network level. In particular, we will study how individual advisory speed limits of connected vehicles and different start-up and clearance behaviors of autonomous vehicles can increase the network capacity and reduce the start-up and clearance lost times. This research will take advantage of a microscopic simulation platform based on Newell's car-following model that incorporates different bounded acceleration (start-up) and aggressiveness (clearance). Connected vehicles' individual advisory speed limits are determined by a feedback control strategy which incorporates traffic signal information and loop detector data. Different start-up and clearance behaviors of autonomous vehicles are implemented by changing their acceleration bounds and aggressiveness when traffic lights turn yellow. Under each combination of technologies, we determine the NFD in time-independent stationary states with periodic vehicle trajectories. A goal is to determine whether their impacts are additive or alternative.

Related Publications

research report | Dec 2021

Impacts of connected and autonomous vehicles on the performance of signalized networks: A network fundamental diagram approach

Read more
policy brief | Dec 2021

Impacts of connected and autonomous vehicles on the performance of signalized networks: A network fundamental diagram approach

Read more

A Smart Mobility Platform with Fair Congestion Pricing and Efficiently Distributed Incentives to Equitably Reduce VMT

Status

Complete

Project Timeline

January 1, 2021 - December 31, 2021

Principal Investigator

r-jayakrishnanR. (Jay) Jayakrishnan

Project Team

Michael Hyland, Daisik (Danny) Nam, Siwei Hu, Pengyuan Sun

Sponsor, Program & Award Number

Caltrans // PSR UTC Caltrans Match: 139335916
(Subcontract to University of Southern California)
(Also see this project page)

Areas of Expertise

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

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

This proposal is to study the benefit of considering heterogeneity of travelers in finding dynamic congestion pricing, so as to design a smart mobility platform for transportation efficiency and fair allocation of transportation supply. Transportation planning and policies in California are arriving at the conclusion that congestion pricing schemes hold the key to change the behavior of drivers and improve the efficiency of the transportation system. Fairness is also of a critical importance in the design of transportation policies. Current congestion pricing schemes may cause social barriers for low‐income populations. We reform traditional congestion pricing schemes to ensure both the efficiency of transportation systems and the fairness of congestion pricing policies. We devise a smart mobility platform where travelers who want a faster travel option pay, and travelers willing to yield his/her fastest option receive incentives. We employ envy‐theory, rather well known in Economics but only recently introduced to Transportation analysis, as a behavioral paradigm for fairness. The envy mechanism, consists of two main modules: 1) pricing module to find the optimal tolls/incentives where the individual‐ level of envy for each travel option is minimized and 2) the dynamic traffic assignment module to identify various travel options for a systemwide optimized traffic pattern. We propose expanding available sustainable transportation alternatives to investigate the potential of the mobility platform in multiple travel modes. We expect to provide a policy recommendation of fair tolls/incentives where personal vehicle drivers pay tolls for the ‘best’ paths through the network, and the revenue from tolls is fairly distributed to users willing to travel on shared‐travel modes instead of personal vehicles. The research will result in utilities that can be further developed for a user‐friendly decision‐support tool for policymakers considering congestion pricing options in California and elsewhere.

Related Publications

research report | Apr 2022

A Smart Mobility Platform to Analyze Fair Congestion Pricing with Traded Incentives and its VMT Impact

Read more

California Truck Data Collection Improvement Project

Status

Complete

Project Timeline

June 1, 2019 - February 28, 2022

Principal Investigator

Stephen Ritchie

Project Team

Andre (Yeow Chern) Tok, Yiqiao Li

Sponsor & Award Number

Caltrans: 74A1105

Areas of Expertise

Freight, Logistics, & Supply Chain Intelligent Transportation Systems, Emerging Technologies, & Big Data

Team Departmental Affiliation

Civil and Environmental Engineering

Project Summary

A range of legislative and policy changes over the last several years have significantly altered the requirements for State transportation planning and programming, necessitating substantial improvement in travel forecasting and modeling practices to support a new mission and increased responsibilities.  These changes included SB 375 (sustainable community), SB 743 (CEQA reform), SB 391 (California Transportation Plan), and Map 21 (California Freight Mobility Plan) that require more robust quantitative and analytic evaluation to describe the relative performance of transportation policies, strategies and programs.  The emphasis on system planning products such as the Interregional Transportation Strategic Plan (ITSP), interstate rail and freight movement demands an integrated multimodal approach to system planning which necessitates travel behavior data analysis and travel demand.   Since the passage of AB 32 in 2006 and subsequent passages of SB 375, SB 391 and MAP 21, Caltrans has been developing state-of-the-practice travel demand modeling tools to support theses legislations.  The California Statewide Travel Demand Model (CSTDM) and the California Statewide Freight Forecasting Model (CSFFM) are modeling tools that will assist in developing strategies to reduce Greenhouse Gas (GHG) emissions to support the Administration’s goals and targets.  In order to maintain state-of-the-practice tools, adequate truck data is needed to improve and enhance the CSTDM and the CSFFM to provide meaningful analysis for Caltrans freight projects. The California Truck Data Collection Improvement Project will restore operations of the Truck Activity Monitoring System (TAMS).  A subset of the existing sites will be selected for full lane-coverage expansion to ensure that all trucks are captured at those locations.  In addition, this study will explore the integration of additional data sources with TAMS to provide truck trip activity data.  This investigation has the potential to provide a better understanding of truck trip patterns by industry, which can further validate the truck trip matrices and route assignment of the CSFFM. The data generated from this study will be utilized for calibration and validation of the next update of the CSTDM and CSFFM which will be used by Caltrans Headquarters and Districts, Metropolitan Transportation Agencies, Regional Transportation Planning Agencies, other State agencies such as the California Air Resources Board and the California Energy Commission. This data will also be used to enhance and update existing planning databases within Caltrans.

Posts navigation

Older posts
Newer posts
When autocomplete results are available use up and down arrows to review and enter to go to the desired page. Touch device users, explore by touch or with swipe gestures.

Recent Posts

  • Dr. Sarah L. Catz featured in WalletHub’s recent Article about Best & Worst States to Drive in
  • Research in Motion: Evaluating Equity in Transportation and Hazard Preparedness Plans: A Multi-Level Governance Approach
  • Research in Motion: Using a “Bathtub Model” to Analyze Travel Can Protect Privacy While Providing Valuable Insights
  • Research in Motion: The Missing Link in Automated Vehicle Safety: Projected Braking and Realistic Driving Behavior
  • PRIME Alumni Spotlight: Miles Shaffie

Recent Comments

No comments to show.

Archives

  • January 2026
  • November 2025
  • October 2025
  • September 2025
  • August 2025
  • July 2025
  • June 2025
  • May 2025
  • February 2025
  • January 2025
  • October 2024
  • September 2024
  • August 2024
  • July 2024
  • June 2024
  • May 2024
  • April 2024
  • February 2024
  • December 2023
  • November 2023
  • September 2023
  • April 2023
  • November 2022
  • October 2022
  • September 2022
  • May 2022
  • April 2022
  • March 2022
  • February 2022
  • January 2022
  • November 2021
  • October 2021
  • August 2021
  • April 2021
  • January 2021
  • December 2020
  • November 2020
  • August 2020
  • July 2020
  • June 2020
  • May 2020
  • April 2020
  • March 2020
  • February 2020
  • January 2020
  • December 2019
  • November 2019
  • May 2019
  • April 2019
  • February 2019
  • January 2019
  • December 2018
  • November 2018
  • October 2018
  • September 2018
  • May 2018
  • April 2018
  • March 2018
  • February 2018
  • January 2018

Categories

  • Award
  • News
  • Research in Motion
  • Spotlight

Anteater Instruction and Research Bldg (AIRB)
Irvine, CA 92697
Phone: 949-824-5989 | Fax: 949-824-8385

  • linkedin
Subscribe to the ITS- Irvine mailing list Subscribe to Events Calendar

About

  • Leadership
  • Affiliated Centers
  • ITS-Irvine Policies
  • Contact Us

Research

  • Areas of Expertise
  • Publications
  • Projects
  • Requests for Proposals

People

  • Researchers
  • Administrative Staff
  • Current Students
  • PhD Graduates
  • Past Faculty Associates

Press

  • News
  • Events

©2026 ITS-Irvine