ITS Berkeley

Analyzing the Economic Benefits and Costs of Smart Growth

Chatman, Daniel G.
Rayle, Lisa
Gabbe, C. J.
Plowman, Johnathan
Sohn, Paul
Crane, Rebecca
Spevack, Anne
Wise, Ella
Stoy, Kelan
Giottonini, M. Paloma
Ordower, Aaron
Crane, Randall
2016

California’s Senate Bill 375, (Chapter 728, Statutes of 2008), aims to reduce transportation related greenhouse gas emissions through more efficient patterns of land development. Advocates claim these smart growth policies will reduce vehicle travel while benefiting residents, cities, and regions in the form of more attractive communities, more affordable housing, and healthier municipal finances. In this study, the authors analyzed the economic impacts of existing smart growth plans similar to those currently being considered and adopted throughout metropolitan California. Through...

An Analysis of the Agglomeration Benefits of Transit Investment: A Case Study of Portland and Dallas

Noland, Robert B.
Chatman, Daniel G.
Klein, Nicholas J.
2013

The objective of this paper is to examine whether new firms are more likely to form near rail transit stations. Two relatively new light-rail systems, one in Portland, Oregon and the other in Dallas, Texas form the basis of the analysis. A geo-coded time-series database of firm births from 1991 through 2008 is analyzed using all firm births, firm births of various sizes, and firm births of specific industry sectors. A random effects negative-binomial model is used to examine associations between proximity to rail stations and other spatially defined variables. Results show that newly...

Advancing the Science of Travel Demand Forecasting

Walker, Joan L.
Chatman, Daniel
Daziano, Ricardo
Erhardt, Gregory
Gao, Song
Mahmassani, Hani
Ory, David
Sall, Elizabeth
Bhat, Chandra
Chim, Nicholas
Daniels, Clint
Gardner, Brian
Kressner, Josephine
Miller, Eric
Pereira, Francisco
Picado, Rosella
Hess, Stephane
Axhausen, Kay
Bareinboim, Elias
Ben-Akiva, Moshe
Brathwaite, Timothy
Charlton, Billy
Chen, Siyu
Circella, Giovanni
El Zarwi, Feras
Gonzalez, Marta
Harb, Mustapha
Mahmassani, Amine
McFadden, Daniel
Moekel, Rolf
Pozdnukhov, Alexei
Sheehan, Maddie
Sivakumar, Aruna
Weeks, Jennifer
Zhao, Jinhua
2019

Travel demand forecasting models play an important role in guiding policy, planning, and design of transportation systems. There is no shortage of literature critiquing the accuracy of model forecasts (see, for example, Pickrell, 1989; Wachs, 1990; Pickrell, 1992; Flyvbjerg, Skamris Holm, and Buhl 2005; Richmond, 2005; Flyvbjerg, 2007; Bain, 2009; Parthasarathi and Levinson, 2010; Welde and Odeck, 2011; Hartgen, 2013; Nicolaisen and Driscoll, 2014; Schmitt, 2016; Odeck and Welde, 2017, and Voulgaris, 2019), not to mention several high-profile lawsuits (Saulwick 2014, Stacey 2015, Rubin...

A Mode Choice Analysis of School Trips in New Jersey

Noland, Robert B.
Park, Hyunsoo
Von Hagen, Leigh Ann
Chatman, Daniel G.
2014

This paper examines the mode choice behavior of children's travel to school based on surveys conducted at a sample of schools in New Jersey. The main focus is on a variety of network design, land use, and infrastructure variables that have typically been associated with walking activity. Using a mixed logit model, it is found that good connectivity, more intense residential land use, and better sidewalk infrastructure are associated with increased walking to school. The use of a mixed logit model allows the examination of individual heterogeneity. Results indicate substantial heterogeneity...

California’s Freeway Service Patrol Program:Management Information System Annual Report Fiscal Year 2018-19

Mauch, Michael
Skabardonis, Alex
2020

The Freeway Service Patrol (FSP) is an incident management program implemented by Caltrans, the California Highway Patrol and local partner agencies to quickly detect and assist disabled vehicles and reduce non-recurring congestion along the freeway during peak commute hours. The first FSP program was piloted in Los Angeles, and was later expanded to other regions by state legislation in 1991. As of June 2018, there were fourteen participating FSP Programs operating in California, deploying 328 tow trucks and covering over 1,823 (centerline) miles of congested California freeways. The...

Bicycle Infrastructure that Extends Beyond the Door: Examining Investments in Bicycle-Oriented Design Through a Qualitative Survey of Commercial Building Owners and Tenants

Orrick, Phyllis
Frick, Karen
Ragland, David R.
2011

This paper presents the results of a qualitative survey of commercial owners, managers, and occupants in the City of Berkeley who have invested in on-site bicycle facilities such as secure parking, showers, changing rooms, and clothing lockers, what we are calling “bicycle-oriented design” (BOD). The sites represent a selection of building types common in the commercial building stock in U.S. cities.The research is designed to answer three questions about the use of BOD: (1) what were motivations behind the decision to invest in BOD (2) what are the challenges and rewards for investing in...

Bounded Rationality in Policy Learning Amongst Cities: Lessons from the Transport Sector

Marsden, Greg
Frick, Karen Trapenberg
May, Anthony D.
Deakin, Elizabeth
2012

The internationalization of policy regimes and the reorganization of the state have provided new opportunities for cities to bypass nation-state structures and work with other cities internationally. This provides greater opportunity for cities to learn from each other and could be an important stimulus to the transfer of policies across the globe. Few studies exist however which focus on the processes that shape the search for policy lessons and how they are affected by the institutional context within which they are conducted. This paper describes research conducted in the field of urban...

Cooperative Cruising: Reinforcement Learning-Based Time-Headway Control for Increased Traffic Efficiency

Veksler, Yaron
Hornstein, Sharon
Wang, Han
Monache, Maria Laura Delle
Urieli, Daniel
2025

The proliferation of connected automated vehicles represents an unprecedented opportunity for improving driving efficiency and alleviating traffic congestion. However, existing research fails to address realistic multi-lane highway scenarios without assuming connectivity, perception, and control capabilities that are typically unavailable in current vehicles. This paper proposes a novel AI system that is the first to improve highway traffic efficiency compared with human-like traffic in realistic, simulated multi-lane scenarios, while relying on existing connectivity, perception, and...

A Nonlocal Degenerate Macroscopic Model of Traffic Dynamics with Saturated Diffusion: Modeling and Calibration Theory

Do, Dawson
Matin, Hossein Nick Zinat
Miti, Masuma Mollika
Monache, Maria Laura Delle
2025

In this work, we introduce a novel first-order nonlocal partial differential equation with saturated diffusion to describe the macroscopic behavior of traffic dynamics. We show how the proposed model is better in comparison with existing models in explaining the underlying driver behavior in real traffic data. In doing so, we introduce a methodology for adjusting the parameters of the proposed PDE with respect to the distribution of real datasets. In particular, we conceptually and analytically elaborate on how such calibration connects the solution of the PDE to the probability transition...