Modeling

Bridging the Income and Digital Divide with Shared Automated Electric Vehicles

Lazarus, Jessica
Bauer, Gordon, PhD
Greenblatt, Jeffery, PhD
Shaheen, Susan, PhD
2021

This research investigates strategies to improve the mobility of low-income travelers by incentivizing the use of electric SAVs (SAEVs) and public transit. We employ two agent-based simulation engines, an activity-based travel demand model of the San Francisco Bay Area, and vehicle movement data from the San Francisco Bay Area and the Los Angeles Basin to model emergent travel behavior of commute trips in response to subsidies for TNCs and public transit. Sensitivity analysis was conducted to assess the impacts of different subsidy scenarios on mode choices, TNC pooling and match rates,...

Casual Carpooling in the San Francisco Bay Area: Understanding User Characteristics, Behaviors, and Motivations

Shaheen, Susan, PhD
Chan, Nelson
Gaynor, Theresa
2016

Casual carpooling is an informal form of commuter ridesharing operating in Washington, D.C.; Houston, Texas; and San Francisco, California. In contrast to new forms of shared-use mobility, casual carpooling has been in existence for over 30 years and uses no information communication technology, and is entirely run informally by its users. Researchers have been fascinated by this phenomenon and have conducted studies in the past, but there remains a lack of up-to-date quantitative data. This study examines the motivations and behaviors of casual carpoolers in the San Francisco Bay Area to...

Mobility on Demand Planning and Implementation: Current Practices, Innovations, and Emerging Mobility Futures

Shaheen, Susan
Cohen, Adam
Broader, Jacquelyn
Davis, Richard
Brown, Les
Neelakantan, Radha
Gopalakrishna, Deepak
2020

This report provides Mobility on Demand (MOD) planning and implementation practices and tools to support communities. The report discusses different stakeholders in the MOD ecosystem and the role of partnerships in filling spatial, temporal, and other service gaps. Additionally, the report discusses how MOD can be integrated into transportation planning and modeling. The report also discusses shared mobility implementation considerations, such as rights-of-way management, multimodal integration, data sharing, equity, labor impacts, and the role of pilot evaluations. Finally, the report...

Shared Mobility Policy and Modeling Workshop

Shaheen, Susan, PhD
Cohen, Adam
Farrar, Emily
2019

The market for personal mobility is changing rapidly due to shifting social and cultural trends, as well as technological advances, such as smartphones, information processing, widespread data connectivity, sharing, and vehicle automation. Shared, on-demand mobility represents a sustainable vision for future mobility with a reliable network of multimodal options that are available to all travelers. On March 22, 2019, the Local Government Commission (LGC) and the Transportation Sustainability Research Center (TSRC) at the University of California, Berkeley hosted the Caltrans Shared...

Micromobility Evolution and Expansion: Understanding How Docked and Dockless Bikesharing Models Complement and Compete – A Case Study of San Francisco

Lazarus, Jessica
Pourquier, Jean Carpentier
Feng, Frank
Hammel, Henry
Shaheen, Susan
2020

Shared micromobility – the shared use of bicycles, scooters, or other low-speed modes – is an innovative transportation strategy growing across the United States that includes various service models such as docked, dockless, and e-bike service models. This research focuses on understanding how docked bikesharing and dockless e-bikesharing models complement and compete with respect to user travel behaviors. To inform our analysis, we used two datasets from February 2018 of Ford GoBike (docked) and JUMP (dockless electric) bikesharing trips in San Francisco. We employed three methodological...

Developing Transportation Response Strategies for Wildfire Evacuations via an Empirically Supported Traffic Simulation of Berkeley, California

Zhao, Bingyu
Wong, Steven D.
2021

Government agencies must make rapid and informed decisions in wildfires to safely evacuate people. However, current evacuation simulation tools for resource-strapped agencies largely fail to compare possible transportation responses or incorporate empirical evidence from past wildfires. Consequently, we employ online survey data from evacuees of the 2017 Northern California Wildfires (n=37), the 2017 Southern California Wildfires (n=175), and the 2018 Carr Wildfire (n=254) to inform a policy-oriented traffic evacuation simulation model. We test our simulation for a hypothetical wildfire...

Willingness of Hurricane Irma Evacuees to Share Resources: A Multi-Modeling Approach

Wong, Steven D.
Yu, Mengqiao
Kuncheria, Anu
Shaheen, Susan A.
Walker, Joan L.
2022

Recent technological improvements have greatly expanded the sharing economy (e.g., Airbnb, Lyft, and Uber), coinciding with growing need for transportation and sheltering resources in evacuations. To understand influencers on sharing willingness in evacuations, we employed a multi-modeling approach across four sharing scenarios using three model types: 1) four binary logit models that capture each scenario separately; 2) a multi-choice latent class choice model (LCCM) that jointly estimates multiple scenarios via latent classes; and 3) a portfolio choice model (PCM) that estimates...

Fleeing from Hurricane Irma: Empirical Analysis of Evacuation Behavior Using Discrete Choice Theory

Wong, Steven D.
Pel, Adam J.
Shaheen, Susan A.
2020

This paper analyzes the observed decision-making behavior of a sample of individuals impacted by Hurricane Irmain2017(n = 645) by applying advanced methods based in discrete choice theory. Our first contribution is identifyingpopulation segments with distinct behavior by constructinga latent class choice model for the choice whether to evacuate or not. We find two latent segments distinguished by demographics and risk perception that tend to be either evacuation-keen or evacuation-reluctant and respond differently to mandatory evacuation orders.Evacuees subsequently face a multi-...

Forecasting Truck Parking Using Fourier Transformations

Sadek, Bassel A.
Martin, Elliot W.
Shaheen, Susan A.
2020

Truck-based transportation is the predominant mode used to transport goods and raw materials within the United States. While trucks play a major role in local commerce, a significant portion of truck activity is also long haul in nature. Long-haul truck drivers are continuously faced with the problem of not being able to secure a safe parking spot since many rest areas become fully occupied, and information about parking and availability is limited. Truck drivers faced with full parking lots/facilities either continue driving until a safe parking spot is located or park illegally....