Metropolis

Click to edit the title text format

Click to edit the outline text formatSecond Outline LevelThird Outline LevelFourth Outline LevelFifth Outline LevelSixth Outline LevelSeventh Outline Level

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