A Data-Driven Safety Dashboard Assessing Maryland Statewide Density Exposure of Pedestrians, Bicycles, and E-Scooters

This project’s ultimate deliverable is a functional Vulnerable User Density Dashboard (https://mti.umd.edu/sdi) for the state of Maryland. The dashboard uses mobile device location data and electric scooter volume data to reflect pedestrian, bicycle, and electric scooter travel volumes and their exposure to roadway safety risk across all roadways in the State. The team develops advanced statistical models to study and predict pedestrian and bicycle involved crashes in a first of its kind effort to generate vulnerable roadway user risk at the link level. The results indicate high correlation between estimated volumes and observed frequency of crashes. This estimated volume and exposure data fills an important gap in understanding the spatial and temporal distributions of pedestrian and bicycle activities. Through this dashboard engineers, planners, and stakeholders can quickly identify safety risk hotspots for vulnerable road users across Maryland and start parsing out why certain locations with high volumes have less crashes. This data-driven dashboard uses emerging data sources and cutting-edge big-data analytics to derive volume estimates and crash risk predictions. It can be used by different stakeholders for situational awareness and traffic analyses of vulnerable users, i.e., pedestrians and bicycles. The predicted risk exposures and hotspots will support relevant decisions such as identifying locations for improvements and implementing pedestrian and bicycle safety countermeasures.

• Dataset URL:
  • https://github.com/umdcxiong/MDOT_SHA_Safety_Data_Initiative
• Record URL:
  • https://rosap.ntl.bts.gov/view/dot/61218
• Dataset URL:
  • https://rosap.ntl.bts.gov/view/dot/61320
• Supplemental Notes:
  • Supporting datasets available at: https://github.com/umdcxiong/MDOT_SHA_Safety_Data_Initiative; https://rosap.ntl.bts.gov/view/dot/61320
• Corporate Authors:

  University of Maryland, College Park

  Department of Civil and Environmental Engineering
  College Park, MD  United States  20742

  Maryland Transportation Institute

  Department of Civil and Environmental Engineering
  College Park, MD  United States  20742

  Maryland Department of Transportation

  State Highway Administration, 707 N Calvert Street
  Baltimore, MD  United States  21202

  University of Maryland, Baltimore

  500 West Baltimore Street
  Baltimore, MD  United States  21201

  Maryland Department of Transportation

  Motor Vehicle Administration
  Glen Burnie, MD  United States  21062

  Department of Transportation

  Office of the Secretary
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Xiong, Chenfeng
  • Mahmoudi, Jina
  • Luo, Weiyu
  • Yang, Mofeng
  • 0000-0002-0525-7978
  • Zheng, Jianyang
  • Delion, Carole
• Publication Date: 2021-8-31

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Appendices; Figures; Maps; References; Tables;
• Pagination: 45p

Subject/Index Terms

• TRT Terms: Crash exposure; Cyclists; High risk locations; Location data; Pedestrians; Scooters
• Geographic Terms: Maryland
• Subject Areas: Data and Information Technology; Pedestrians and Bicyclists; Safety and Human Factors;

Filing Info

• Accession Number: 01843686
• Record Type: Publication
• Contract Numbers: 69A34520501050620
• Files: NTL, TRIS, ATRI, USDOT, STATEDOT
• Created Date: Apr 25 2022 10:07AM