Using Big Data for Unbiased Weekend VMT Estimation in Crash Analysis
Safety planning required identifying high-risk areas, but existing data had a bias towards weekend travel. By utilizing a trial subscription of Streetlight Data, a solution was developed to estimate weekend Vehicle Miles Traveled (VMT) in a way that eliminated bias and allowed for a more accurate analysis of crash data.
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Using Big Data to Estimate Weekend VMT for Crash Analysis JOSEPH FLOOD, DELAWARE VALLEY REGIONAL PLANNING COMMISSION ANDREW SWENSON, INDIANAPOLIS METROPOLITAN PLANNING ORGANIZATION CATHERINE KOSTYN, INDIANAPOLIS METROPOLITAN PLANNING ORGANIZATION
The Problem Safety was a long-range plan goal Wanted to identify projects that addressed dangerous areas Had data Point-Level Fatalities and Serious Injuries (KSI) 1-km Grid of the Region Metric: Identify grid cells with high KSI per VMT
The Problem Said measure had an inherent bias due to the source data KSI data was for all days of the week VMT was for typical weekday Result: Measure was biased towards areas with higher relative weekend travel Example: Grand Park in Westfield Sports complex that opened on fringe of Urbanized Area in 2014 Has many events over the weekend Such events generate a lot of traffic
The Solution Needed way to get weekend VMT Had 1-year trial subscription of Streetlight Data Divided region into 2km grid Got streetlight index for typical weekday and typical weekend day for each grid cell Index is directly proportional to the number of trips Index = Trips Unknown Constant
The Solution Weekend Index Weekday Index =Weekend Daily Trips Unknown Constant Weekday Daily Trips Unknown Constant =Weekend Daily Trips Weekday Daily Trips Weekly VMT = 5 Weekday VMT + 2 Weekend Weekday Ratio Weekday VMT Allowed for calculation of unbiased measure
