Modeling

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...

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....