Bike Week Crash Analysis

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Bike Week Crash Analysis David Salzer Patrick Santoso University of New Hampshire 7/15/2014 1

What is Bike Week? Official name is Laconia Motorcycle Week First or second week of June 2013 attendance: 330,000 Peak attendance in 2004: 430,000 Laconia population: 20,000 Brings $100 million to NH 2

Started in 1916, Added to Gypsy Tour 1917 3 Photo Courtesy of Charlie St. Clair's and Jennifer Anderson's book, Laconia Motorcycle Week, Arcadia publishing, 2008

Changed to a Weeklong Event in 1935 4 Photo Courtesy of http://www.weirsbeach.com/largejpgs/bikeweekguidecovers.html

Riot of 1965 5 Photo Courtesy of http://sillyverse.com/2013/01/11/summer-vacations-on-winnisquam/

Today: Family Friendly Event 6 Photo Courtesy of http://sillyverse.com/2013/01/11/summer-vacations-on-winnisquam/

Orientation to New Hampshire Population (2013): 1,323,459 Population is concentrated in the lower portion of the state which is considered Boston Metro State is predominantly rural Laconia is located in the Lakes Region on the banks of Lake Winnipesaukee (69 mi 2 ) Concord Manchester Portsmouth Nashua 7

Orientation to Laconia 8

Issue to be Solved State and local police want to reduce the number of motorcycle crashes through enforcement Where and when should police be stationed to see maximum reduction in crashes? Part of Driving Towards Zero Note: NH does not have a helmet law for riders over 18 years old 9

Proposed Solution Analyze historical motorcycle crash data (2002-2011) sourced from local and state police to determine enforcement locations Temporal analysis Correct non-georeferenced data points using NH Mosaic Parcel Map Identify focus areas of high accident density (kernel density analysis) Hub and spoke analysis 10

Step 1-Temporal Analysis of MC Crashes Average Crashes by Month All Crashes by Year and Time of Day Bike Week Crashes by Day and Time (3 Year Avg- 10, 11, 12) 11

Average MC Crashes By Month 200.0 180.0 160.0 140.0 120.0 100.0 80.0 10 YRAVG 3 YRAVG 60.0 40.0 20.0 0.0 0 2 4 6 8 10 12 12

All MC Crashes by Time and Year High Period PEAK 13

Bike Week MC Crashes by Day & Time PEAK High Period High Period PEAK 14

Bike Week MC Accidents By Day 60 50 40 30 20 Total MC Accidents Poly. (Total MC Accidents) 10 0 Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday 15

3 Year Top 15 Towns For MC Crashes by Month 16

Step 2-Analyze Crashes Spatially Geolocate Centroid Crashes Kernel Density Analysis Hub and Spoke Analysis 17

Crash Point Data Data is captured by local and state Police Standardized and compiled by NHDOT Available data: 2002-2011 Data Captured Location, data and time Vehicles involved, property damaged Influencing factors (speed, alcohol, etc.) Injuries, fatalities Make of vehicle 18

Geolocating Applicable Crashes 19

Kernel Density Analysis In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable. Kernel density estimation is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. 1,2 1.Rosenblatt, M. (1956). "Remarks on Some Nonparametric Estimates of a Density Function". The Annals of Mathematical Statistics 27 (3): 832. doi:10.1214/aoms/1177728190. 2.Parzen, E. (1962). "On Estimation of a Probability Density Function and Mode". The Annals of Mathematical Statistics 33 (3): 1065. doi:10.1214/aoms/1177704472. JSTOR 2237880. Bike Week (2002-2011) 20

What Does it Mean? Density of crashes represented in a heat map Indicate areas where crashes most often happen Can be inferred that crashes will most likely happen in these areas again ArcMap function exists in: Spatial Analyst Tools>Density 21

All MC Crashes (2002-2011) 22

Bike Week (2009, 2010, 2011) Bike Week (2002-2011) 23

Bike Week (2002-2011) 24

Hub and Spoke Analysis Route 3 Route 25 Winona Rd Route 11 Route 104 Route 106 Route 3 25

What Was the Impact in 2013? Substantial Reduction in June 2013 Crashes Reduction in Bike Week 2013 Crashes Reduction in Bike Week 2013 High Period Crashes 26

Average MC Crashes By Month 220 200 180 160 140 120 100 80 10 Yr Average 3 Yr Average 2013 60 40 20 0 0 January February 2 March April 4 May June 6 July August 8 September October 10 November December 12 10 YR AVG 1.6 1.5 13.0 63.8 95.0 193.4 143.4 124.5 98.8 50.8 17.3 1.8 3 YR ABG 1.3 1.3 18.0 73.7 101.0 162.3 136.7 124.3 94.0 45.3 16.7 2.7 2013 0.0 0.0 15.0 59.0 91.0 149.0 96.0 126.0 68.0 30.0 9.0 1.0 27

Bike Week 2013 MC Crashes by Day & Time Total Crashes 09, 10, 11 AVG: 77 2013: 51 crashes 33% reduction All days except Sunday lower in 2013 High Period (Wed-Sat) 09, 10, 11 AVG: 52 2013: 37 29% reduction All days lower in 2013 Bike Week 2013 Time/Day Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday Totals 12:00 AM 0 0 0 0 0 0 1 1 2 1:00 AM 0 0 0 0 0 0 0 0 0 2:00 AM 0 0 0 0 0 0 0 0 0 3:00 AM 0 0 0 0 0 0 0 0 0 4:00 AM 0 0 0 0 0 0 0 0 0 5:00 AM 0 0 0 0 0 0 0 0 0 6:00 AM 0 0 0 0 0 0 0 0 0 7:00 AM 0 0 1 0 0 0 0 0 1 8:00 AM 0 0 0 0 0 0 0 0 0 9:00 AM 0 0 0 0 0 0 0 3 3 10:00 AM 1 0 0 1 0 0 0 1 3 11:00 AM 0 2 0 0 0 1 1 1 5 12:00 PM 1 1 1 0 0 1 1 2 7 1:00 PM 0 1 0 0 1 0 1 2 5 2:00 PM 0 2 0 0 0 0 1 1 4 3:00 PM 1 0 0 0 0 1 0 0 2 4:00 PM 0 0 1 0 0 0 3 2 6 5:00 PM 0 0 0 0 0 0 2 1 3 6:00 PM 0 0 0 0 0 1 1 2 4 7:00 PM 0 1 0 0 1 0 1 0 3 8:00 PM 0 0 0 0 0 0 0 0 0 9:00 PM 0 0 0 0 0 0 0 1 1 10:00 PM 0 0 0 0 0 1 0 1 11:00 PM 0 0 0 0 1 0 0 0 1 Daily Total 3 7 3 1 3 5 12 17 3 year avg 10 3 7 8 11 9 14 18 28

Questions? 29