Travel Demand

How is the COVID-19 Pandemic Shifting Retail Purchases and Related Travel in the Sacramento Region?

Teddy Forscher
Elizabeth Deakin
Joan Walker
Susan Shaheen
2021

A significant portion of the population stayed, and continue to stay, at home due to the COVID-19 pandemic. With more people staying home, online shopping increased along with trips related to pickups and deliveries. To gain a better understanding of the change in retail purchases and related travel, UC Berkeley researchers compared pre-pandemic shopping to pandemic-related shifts in consumer purchases in the greater Sacramento area for nine types of essential and non-essential commodities (e.g., groceries, meals, clothing, paper products, cleaning supplies). In May 2020, the research team...

Who Has Access to E-Commerce During the COVID-19 Pandemic in the Sacramento Region? Implications for Future E-Commerce and Shopping Tripmaking

Teddy Forscher
Elizabeth Deakin
Joan Walker
Susan Shaheen
2021

The COVID-19 pandemic brought about dramatic shifts in travel, including shopping trips. We investigated changes in eshopping for food and non-food items by supplementing an April to May 2018 household travel survey (n=3,956 households) conducted by the Sacramento Area Council of Governments (SACOG) with a May 2020 follow-on panel survey (n=313 households) during one week early in the pandemic. Results demonstrate that impacts from added pickups and deliveries in the SACOG region during the first two months of the COVID-19 pandemic were limited and did not overwhelm curb management at...

VII California: Development and Deployment Proof of Concept and Group-Enabled Mobility and Safety (GEMS)

Misener, Jim
Raja Sengupta
Ahern, Katherine
Gupta, Somak Datta
Dickey, Susan
Kuhn, Tom
Lian, Thang
Manasseh, Christian
Nelson, David
Rezai, Shahram
Sharafsaleh, Ashkan
Shladover, Steven
VanderWerf, Joel
2010

This PATH Research Report covers the (Vehicle-Infrastructure Integration) VII California Development and Deployment (Task Order6217) efforts beginning in 2008 and concluding June 30, 2009. This is a successor to the report for TO 5217and reports theapplications-oriented research subsequent to that work.The report is organized by a synopsis of the background and reasons for the VII California project, then it summarizes some of the antecedent (TO 5217) work: the "Innovative Mobility Showcase" (2005), which established the architecture and, importantly the applications (curve overspeed...

The Quantified Traveler: Using Personal Travel Data to Promote Sustainable Transport Behavior

Jariyasunant, Jerald
Carrel, Andre
Ekambaram, Venkatesan
Gaker, D. J.
Kote, Thejovardhana
Raja Sengupta
Joan Walker
2011

With the advent of ubiquitous mobile sensing and self-tracking groups, travel demand researchers have a unique opportunity to combine these two developments to improve the state of the art of travel diary collection. While the use of mobile phones and the inference of travel diaries from GPS and sensor data allows for lower-cost, longer surveys, we show how the self-tracking movement can be leveraged to interest people in participating over a longer period of time. By compiling personalized feedback and statistics on participants’ travel habits during the survey, we can provide the...

A Casual Analysis of FlexPass: Incentives for Reducing Parking Demand

Tang, Dounan
Lin, Ziheng
Raja Sengupta
2016

A parking incentive program named FlexPass have been conducted in University of California, Berkley. The causal structure underlying employee parking behavior is examined in this study by a randomized controlled trial, where participants receiving treatment were offered incentives for parking less and taking other modes. This field experiment lasted for three months and recruited 392 staff and faculty members. Practicable problems encountered during the study were non-random differential dropout after the group assignment and non-ignorable missing data. Missing data were measured by follow...

Designing for Mode Shift Opportunity with Metropolitan Scale Simulation

Deodhar, Kanaad
Laurence, Colin
Jane Macfarlane
2019

Shifting vehicle drivers to alternate modes is becoming a key focus of city planning groups. Key to understanding how to posit new transit opportunities requires a granular understanding of origin-destination travel demand. By using Mobiliti, a HPC simulation developed at Lawrence Berkeley National Laboratory that populates origins and destinations and simulates their use of the transportation network, that granular understanding can be achieved. This data can be used to understand how current and potential future transit routes serve regional demand and how those services can be improved...

Induced Travel Demand and Induced Road Investment: A Simultaneous Equation Analysis

Cervero, Robert
Mark Hansen
2002

This paper presents simultaneous models that predict induced travel demand and induced road investment using an array of instrument variables reflecting political, environmental, and demographic influences. From a panel data set consisting of 22 years of observations for 34 California urban counties, short-run elasticities are estimated. Both the Vehicle– Miles-Travelled model and the Lane–Miles model feature good statistical fits and highly significant parameter estimates. While the research found strong reciprocal relationships between road investment and travel demand, the elasticity...

Advancing the Science of Travel Demand Forecasting

Joan Walker
Daniel Chatman
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
Marta Gonzalez
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...

Influence of Socioeconomic Factors on Transit Demand During the COVID-19 Pandemic: A Case Study of Bogotá’s BRT System

Caicedo, Juan D.
Joan Walker
Marta Gonzalez
2021

The COVID-19 pandemic restricted most economic and social activities, impacting travel demand for all transportation modes and especially for transit. We hypothesize that the shifts in travel demand varied by socioeconomic status, and we assess the differential impact of COVID-19 in the Bus Rapid Transit (BRT) patronage across various socioeconomic groups in Bogotá. We built a database of frequent transit users with data collected by smartcards in Bogota’s BRT system between January and October 2020. For each user in the database, we labeled their home and work stations. Transactions at...

Share, Collaborate, Benchmark: Advancing Travel Demand Research Through Rigorous Open-source Collaboration

Caicedo, Juan D.
Guirado, Carlos
Marta Gonzalez
Joan Walker
2024

This research foregrounds general practices in travel demand research, emphasizing the need to change our ways. A critical barrier preventing travel demand literature from effectively informing policy is the volume of publications without clear, consolidated benchmarks, making it difficult for researchers and policymakers to gather insights and use models to guide decision-making. By emphasizing reproducibility and open collaboration, we aim to enhance the reliability and policy relevance of travel demand research. We present a collaborative infrastructure for transit demand prediction...