Exploring Large-Scale Crowdsourced Connected Vehicle Data (CVD) to Support Alabama Transportation Decision-Making

Penmetsa, Praveena; Zhang, Zihe; Annimalla, Vamshi Chaitanaya; Hainen, Alex; Liu, Jun

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Exploring Large-Scale Crowdsourced Connected Vehicle Data (CVD) to Support Alabama Transportation Decision-Making

2026-08-03
By Penmetsa, Praveena ; Zhang, Zihe ; Annimalla, Vamshi Chaitanaya

File Language:

English

[PDF - 19.54 MB]

Details

Creators:

Penmetsa, Praveena ; Zhang, Zihe ; Annimalla, Vamshi Chaitanaya ; Hainen, Alex ; Liu, Jun
Corporate Creators:

University of Alabama
Corporate Contributors:

Alabama. Department of Transportation ; United States. Department of Transportation. Federal Highway Administration
Subject/TRT Terms:
Resource Type:

Tech Report
Geographical Coverage:

United States ; Alabama
Edition:

Final Report
Corporate Publisher:

Alabama. Department of Transportation
Abstract:

Connected vehicle data (CVD) provides high-resolution, continuous observations of vehicle trajectories, speeds, and driving events, offering significant advantages over traditional data sources in terms of spatial accuracy, temporal granularity, and behavioral insights. This project explores the potential of large-scale CVD to support data-driven transportation decision-making in Alabama in transportation operation, transportation safety, and transportation planning. The primary objective of this study is to develop a comprehensive analytical framework and practical applications that demonstrate how CVD can be integrated with existing transportation datasets, such as CARE crash data, ALGO incident data, HPMS roadway inventory data, and points of interest (POI) data, to enhance decision-making in transportation planning, operations, and safety. The project establishes scalable methods for processing, aggregating, analyzing, and visualizing large-scale trajectory data, while also addressing key challenges related to data integration and usability for agency applications.
Format:

PDF
Download URL:

https://rosap.ntl.bts.gov/view/dot/93315/dot_93315_DS1.pdf
File Type:

[PDF - 19.54 MB]
Collection(s):

Autonomous Vehicles
Main Document Checksum:

urn:sha-512:f5f8146505fc50898f761e4387e755941d65f8ad9a442627dd0ded5bf66f96e7451f0f1d46d62829cb99e2a7124640e27b2958c37bcea827bcacae7c2ab4f597

File Language:

English

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