WEEK 5 – ITS Student Seminar

Travel patterns change and effectiveness of TDM in California, by Sungsu Yoon

The purpose of this research is to improve current travel demand model with up-to-date inputs and to contribute enhancement of needed sub-modules to forecast regional travel demands more accurately. Core structure of this research is deriving update Origin-Destination (OD) matrix for traditional regional four-steps travel demand model and then compare scenario results with major transportation demand measurements to see the impacts of inputs and update. Alternative scenario will have update OD matrix from the enhanced mode choice data based on the analysis of the latest or current travel behavior changes in the region. And other sources such as years of Household Travel Survey and employment based travel demand control programs also will be analyzed and be utilized by the needs. As an introduction, research will review two different travel surveys between 2001 and 2011 to see whether there is any travel mode pattern change among different survey years. Based on travel behavior changes (mode choice pattern changes and trip length, vehicle occupancy) from different demographic generations, there should be an updates on travel demand parameters and assumptions regarding travel demand modeling inputs and ratio of parameters. CHTS analysis will be direct source of the socioeconomic (SED) analysis but additional SED forecasts from SCAG would be supplemental resource to derive appropriate trip generation and distribution ratios in the demand modeling. Based on the update mode choice pattern and rate, research will derive update mode choice results by major modes (drive alone and carpools, active transportation) and OD matrix among research area by designated travel analysis zone (TAZ). In addition, to execute the latest travel mode share analysis, research will upgrade network systems which also include alternative active transportation systems such as biking or walking as needed. Regarding methodology, research will utilize previous modules and theoretical methods from well-established programs like as the TRIMMS (Trip Reduction Impacts for Mobility Management Strategies) and EPA’s COMMUTER model and other Travel Demand Management (TDM) measures. Analyzing and measuring impacts of specific TDM strategies and programs are important part of this research to derive update ratio of mode shares in each TAZ. After mode choice and OD matrix results are update, research will use those update OD results as seed matrices for assignment stage. And then once assignment results are ready, we could analyze impacts from travel pattern changes through comparing results of baseline case (current travel demand model result) and update scenario result which was developed from the latest trend of travel pattern. As a quantifying analysis, research will measure major travel demand factors (VMT, VHT and Delays) and major environmental measures (emission analysis) to know the performance of scenario plan.

Traffic congestion and fragmentation of metropolitan governance, by Gavin Ferguson

Metropolitan transportation planning in the United States is growing more fragmented and decentralized as a result of stagnant federal funding for transportation. How will the increasingly decentralized provision of transportation affect urban transportation systems? Although many argue that inter-jurisdictional conflicts will prevent the kind of coordination needed to address regional problems such as traffic congestion and air pollution, thus necessitating more centralized authority, there have been no econometric studies to support this claim. The present study begins to address this gap in the literature with an analysis of the relationship between decentralization and traffic congestion. A panel data analysis was conducted using data on U.S. metropolitan statistical areas spanning the years 1982 to 2011. The results showed a positive elasticity estimate of annual person-hours of delay per capita with respect to number of city governments per capita of 0.632. This estimate implies that decentralization contributed an extra 37 million hours of delay in 2011 across the 97 MSAs included in the analysis.

Week 4 – ITS Student Seminar

Measuring Perceived Travel Time Uncertainty In Transportation Modeling and Simulation by Gabriel Yu.

Measuring and incorporating perceived travel time uncertainty in transportation modelings is a desired topic in recent TRB research needs, which is especially critical in improving DTA, ABM, project(s) evaluation, and understanding better of travel behavior. This short speak will talk about motivations, existing methods, and the proposed methods in the efforts of measuring perceived travel time uncertainty. Sensation, category-based perception, and information will be introduced. The proposed Information entropy measurement will be followed by a simple application on static path-based traffic assignment and an extension to quantum cognitive models. 

Proactive vehicle routing with inferred demand to solve the bikesharing rebalancing problem by Robert Regué

Bikesharing suffers from the effects of fluctuating demand that leads to system inefficien- cies. We propose a framework to solve the dynamic bikesharing repositioning problem based on four core models: a demand forecasting model, a station inventory model, a redis- tribution needs model, and a vehicle-routing model. The approach is proactive instead of reactive, as bike repositioning occurs before inefficiencies are observed. The framework is tested using data from the Hubway Bikesharing system. Simulation results indicate that system performance improvements of 7% are achieved reducing the number of empty and full events by 57% and 76%, respectively, during PM peaks. 

Week 3 – ITS Student Seminar

Advocacy in Action: Understanding the Influence of Advocacy Organizations on Local Affordable Housing Policy in the U.S.

Financial support for affordable housing competes with many other municipal priorities. This work seeks to explain the variation in support for affordable housing among U.S. cities with populations of 100,000 or more. Using multivariate statistical analysis, this research investigates political explanations for the level of city expenditures on housing and community expenditures with a particular interest in the influence of housing advocacy organizations (AOs). Data for the model were gathered from secondary sources including the U.S. Census and the National Center for Charitable Statistics. Among other results, the analysis indicates that, on average, the political maturity of AOs has a statistically significant, positive effect on local housing and community development expenditures.

Anaid Yerena

Department of Planning, Policy & Design, University of California, Irvine.