Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Realistic Artificial Datasets: Objective Evaluation of Data-Driven Safety Analysis Models

Filetype[PDF-1.31 MB]


  • English
    • Details You May Also Like

    Details:

    • Corporate Creators:
      Federal Highway Administration (U.S.)
    • Subject/TRT Terms:
    • Publication/ Report Number:
      FHWA-HRT-20-047
    • Resource Type:
      Brief
    • Geographical Coverage:
      United States
    • Corporate Publisher:
      Federal Highway Administration (U.S.)
    • Abstract:
      Crashes occur because of complex interactions between multiple variables, including driver behavior, environmental context, roadway design, and vehicle dynamics. Datadriven safety analysis (DDSA) models help State and local agencies quantify safety data, identify high-risk roadway features, and predict the effects of proposed safety measures. However, even when a model performs well overall, it may not accurately represent the interactions between variables for a specific location or crash because the underlying relationships in the real world are unknown. One proposed solution is to generate realistic artificial datasets (RAD) with predetermined safety relationships built into them. Since these are known, the RAD can serve as a testbed, revealing how well a model reflects those underlying cause and effect relationships
    • Format:
      PDF
    • Collection(s):
    • Main Document Checksum:
    • Download URL:
    • File Type:

    Supporting Files

    • No Additional Files

    More +

    You May Also Like

    Checkout today's featured content at rosap.ntl.bts.gov

    Version 3.26