Applying AI to Data Sources to Improve Driver-Pedestrian Interactions at Intersections [Research Brief]

Chakraborty, Subhadeep; Collaborative Sciences Center for Road Safety; University of Tennessee, Knoxville

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

Advanced Search
Custom Query

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:

Clear All

Query Builder

Query box

Clear All

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

ROSA P serves as an archival repository of USDOT-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to ensure public access to scientific information.

i

Applying AI to Data Sources to Improve Driver-Pedestrian Interactions at Intersections [Research Brief]

[PDF-603.27 KB]

English

Details Datasets Related Documents You May Also Like

Details:

Creators:

Chakraborty, Subhadeep
Corporate Creators:

Collaborative Sciences Center for Road Safety ; University of Tennessee, Knoxville

Collaborative Sciences Center for Road Safety ; University of Tennessee, Knoxville Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Artificial Intelligence Crashes Driver-pedestrian Interaction Driving Behavior Edge Cases Fatalities Intersection Crashes Intersections Nighttime Crashes Pedestrian Safety Traffic Lanes Traffic Signals
Publication/ Report Number:

CSCRS-R43
Resource Type:

Brief
Geographical Coverage:

United States
Edition:

Research Brief
Corporate Publisher:

Collaborative Sciences Center for Road Safety
Abstract:

Tragically, roadway crossings sometimes act as killing fields, especially for pedestrian-vehicle collisions; intersections account for 40% of transportation crashes in the United States. To mitigate such incidents, pedestrian safety at intersections must be addressed effectively.
Format:

PDF
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha-512:bb71f6266bfed943f49d1cfc498fec5ca335d159f475c7424128b790738de855b42b0b2edfdd64c9fe0ab25429050271593fd688ef925d831d2faee2e21f1200
Download URL:

https://rosap.ntl.bts.gov/view/dot/77358/dot_77358_DS1.pdf
File Type:

No Additional Files

More +

Applying AI to Data Sources to Improve Driver-Pedestrian Interactions at Intersections [Research Brief]

Details:

Supporting Files

Datasets

Related Documents

You May Also Like