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Ridehailing & Congestion: How Big Data Can Help Understand the Impacts of Gig Driving on Traffic
Abstract
The ridehailing phenomenon kickstarted by Uber and Lyft less than 10 years ago is widely prevalent in several communities across the US. Many communities are asking questions about the impact of ridehailing on other transportation aspects such as transit ridership, roadway congestion and curb space management in the core areas of cities and communities. Data from ridehailing companies has been hard to come by, which makes it challenging to conduct analysis to answer some of these questions.
StreetLight Data processed billions of location data points from smartphone apps (Location Based Services or LBS data) for all modes (personal vehicle, transit, bike and ped) as well as gig driving apps to analyze the interaction between gig trips and rest of the traffic. Gig trips are created from the gig app location data and validated for intuitive patterns such as activity by area type and time of day. In this presentation, Matt Pettit of StreetLight Data, will walk attendees through the methodology and findings of a comprehensive ridehailing analysis conducted by StreetLight Data.
Ridehailing trips are mapped onto total vehicle trips along with contextual data such as concentration of commercial points of interest (such as restaurants, tourism, etc.). Different types of areas within a city are analyzed in more detail to understand the level and nature of interaction between ridehailing and total traffic. In addition to such spatial analysis to establish correlation, regression and other econometric analysis are explored to determine the relationship and its significance between different transportation, land use and demographic variables with levels of ridehailing and congestion. Transportation variables such as transit service and network density, among others are considered.
By the end of the session, attendees will walk away understanding how analytics derived from mobile devices can help local and state officials and new mobility planning organizations better prepare for the rapid expansion of ridehailing across the country.
Ridehailing & Congestion: How Big Data Can Help Understand the Impacts of Gig Driving on Traffic
Category
New Mobility Services
Description
Presenter: Matthew Pettit
Agency Affiliation: StreetLight Data
Session: Interactive Forum - Sustainability and Emerging Transportation Technologies
Date: 6/1/2022, 10:30 AM - 12:00 PM
Presenter Biographical Statement: Matt has 10 years of experience working on interdisciplinary teams across government, engineering consulting, and data/software vendors, within and outside the transportation industry. Before joining StreetLight Data as a Product Manager, Matt helped Virginia DOT operationalize the first-ever state-level project prioritization program using multi-modal accessibility as a factor. Matt holds an MS in Civil Engineering from Northwestern University, focusing in Transportation Systems Analysis & Planning.