Metropolis
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A window into real-time traffic hazards
Frank Bentrem
Insight Data ScienceFall 2016
Collide-O-Scope
Traffic Safety
Vision ZeroReduce traffic injuries
Provide real-time traffic hazard predictions to NYC public safety officials.
201553,176 Injuries232 Fatalities
Collide-O-Scope
Highlight roadways at significant risk for accidents
NYPD may include this information in their patrol officer deployment plan.
Clear Day
Collide-O-Scope
Highlight roadways at significant risk for accidents
NYPD may include this information in their patrol officer deployment plan.
Rainy Day
Getting the Data
Traffic Speed CamerasNYC DOT (18 months)
Read license plate numbers
Localized precipitation forecastdarksky.net
Vehicle collisionsOffice of Public Safety
Brooklyn Bridge
Daily Pattern
Morning Rush
Evening Rush
Sinusoidal Pattern
Building the Model
Generalized Linear RegressionCross Terms (e.g. Precipitation Intensity * Average Crashes)
Coefficients
Real-Time DataTraffic speedsPrecipitation forecastPredicted crashes per hourfor each road segment
BronxBrooklynManhattanStaten IslandQueens
R squared0.390.600.500.210.54
FeaturesTraffic speedsPrecipitation forecastDaily/Weekly patterns
Building the Model
Coefficients
Real-Time DataTraffic speedsPrecipitation forecastPredicted crashes per hourfor each road segment
BronxBrooklynManhattanStaten IslandQueens
R squared0.390.600.500.210.54
FeaturesTraffic speedsPrecipitation forecastDaily/Weekly patterns
Generalized Linear RegressionCross Terms (e.g. Precipitation Intensity * Average Crashes)
Building the Model
Generalized Linear RegressionCross Terms (e.g. Precipitation Intensity * Average Crashes)
Predicted crashes per hourfor each road segment
BronxBrooklynManhattanStaten IslandQueens
R squared0.390.600.500.210.54
FeaturesTraffic speedsPrecipitation forecastDaily/Weekly patterns
Real-Time DataTraffic speedsPrecipitation forecast
Fitted Coefficients
Building the Model
Generalized Linear RegressionCross Terms (e.g. Precipitation Intensity * Average Crashes)
CoefficientsReal-Time DataTraffic speedsPrecipitation forecastBronxBrooklynManhattanStaten IslandQueens
R squared0.390.600.500.210.54
FeaturesTraffic speedsPrecipitation forecastDaily/Weekly patterns
Predicted crashes per hourfor each road segment
Building the Model
Generalized Linear RegressionCross Terms (e.g. Precipitation Intensity * Average Crashes)
CoefficientsReal-Time DataTraffic speedsPrecipitation forecastFeaturesTraffic speedsPrecipitation forecastDaily/Weekly patterns
BronxBrooklynManhattanStaten IslandQueens
R squared0.390.600.500.210.54
Predicted crashes per hourfor each road segment
My Journey
Frank Bentrem
Scientific Computing, Ph.D.Polymer SimulationsAcoustic Remote SensingTeaching PhysicsQuantitative Finance Data Science Fellowship
A window into real-time traffic hazards
Collide-O-Scope
Collide-O-Scope
Future Improvements
Compile collisions by road
Increase data sample (snow)
Study data anomaliesMissing data (May be missing at most relevent times)
Traffic Construction
Data Overview
Individual road segments
Removed holidays
Seperated weekdays from weekends
Hourly traffic profiles show morning/afternoon rush hours
Speed negatively correlated to collisions
Data Overview
Hourly Weather Dark Sky App
darksky.net
Speeds CamerasNYC DOT
data.beta.nyc
Vehicle CollisionsNYC DPS
Predict Traffic Flow using Precipitation Forecast
Reduce traffic accidentsAdvisories
Driver avoidance
Improve delivery scheduling for businesses
Improve travel-time estimates for apps
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