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This webinar is led by ITE Safety Council.

Webinar Description:
In the past few years, Big Data has emerged as an important alternative for numerous transportation studies, especially as a source to obtain data retroactively. Big Data appears to be a good source for data collection and integration moving forward, especially in the safety field.

"Incorporating Big Data into Safety Analysis: An Integrated and Proactive Approach" is a Technical Brief developed by the ITE Safety Council and published in August 2022. The document defines Big Data in the context of safety, addresses how Big Data can supplement traditional data as well as how it can improve safety by filling the existing gaps. This report includes a discussion on how Big Data is currently being used to address safety issues, what the available sources for safety professionals are, and what issues still need to be addressed. The report focus areas are data collection and processing, proactive safety approach, driver behavior, and pedestrian and bicycle safety. This presentation provided a summary of the report for transportation professionals.

Learning Objectives:

• Recognize challenges with traditional data collection and processing (e.g., quality of data, being resource- and labor-intensive, the need for standardizing safety data) and learn how Big Data has been used to overcome these issues.
• Explore how Big Data can be used to supplement traditional safety data as an effort to proactively identify candidate locations for safety improvements.
• Identify challenges with pedestrian and bicyclist safety assessment (e.g., lack of exposure data and trip routes) and learn how Big Data can be used to assist decision-making for safety improvements.
• Understand how driver behavior impacts safety and learn how Big Data can help inform roadway design, construction, repair, and improvement to account for driver behavior.
• Explore a case study showing how Big Data was used to identify high-risk locations, and how a jurisdiction can use Big Data to prioritize candidate locations for safety improvements, as well as assess the safety effectiveness of those improvements.
• Learn what existing gaps for safety analysis still exist and what the potential next steps are to combine Big Data and traditional safety data on a collaborative approach to improve safety.

Description

This webinar is led by ITE Safety Council.

Webinar Description:
In the past few years, Big Data has emerged as an important alternative for numerous transportation studies, especially as a source to obtain data retroactively. Big Data appears to be a good source for data collection and integration moving forward, especially in the safety field.

"Incorporating Big Data into Safety Analysis: An Integrated and Proactive Approach" is a Technical Brief developed by the ITE Safety Council and published in August 2022. The document defines Big Data in the context of safety, addresses how Big Data can supplement traditional data as well as how it can improve safety by filling the existing gaps. This report includes a discussion on how Big Data is currently being used to address safety issues, what the available sources for safety professionals are, and what issues still need to be addressed. The report focus areas are data collection and processing, proactive safety approach, driver behavior, and pedestrian and bicycle safety. This presentation will provide a summary of the report for transportation professionals.

Learning Objectives:

• Recognize challenges with traditional data collection and processing (e.g., quality of data, being resource- and labor-intensive, the need for standardizing safety data) and learn how Big Data has been used to overcome these issues.
• Explore how Big Data can be used to supplement traditional safety data as an effort to proactively identify candidate locations for safety improvements.
• Identify challenges with pedestrian and bicyclist safety assessment (e.g., lack of exposure data and trip routes) and learn how Big Data can be used to assist decision-making for safety improvements.
• Understand how driver behavior impacts safety and learn how Big Data can help inform roadway design, construction, repair, and improvement to account for driver behavior.
• Explore a case study showing how Big Data was used to identify high-risk locations, and how a jurisdiction can use Big Data to prioritize candidate locations for safety improvements, as well as assess the safety effectiveness of those improvements.
• Learn what existing gaps for safety analysis still exist and what the potential next steps are to combine Big Data and traditional safety data on a collaborative approach to improve safety.