Colorado Crash Data Safety Summit June 8, 2016

2015 Colorado Data* 116,388 Total Crashes 30,783 Injuries 543 Fatalities 506.015 100MVMT 88,258 Roadway Center Line Miles

*All 2015 data is preliminary

Historic Fatal and Serious Injury Trend *

* 2015 Data is preliminary

500 490 480 470 460 450 440 430 420 410 400

1.400

Fatalitiy Rate

Safety – Fatalities and Fatality Rate

1.200 1.000 0.800 0.600 0.400

VMT (100M)

Fatality Rate and VMT 1.600

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Fatalities

Why it matters: In order to achieve Colorado’s vision, Towards Zero Deaths, we need to track progress and use data to target safety improvements to maximize improvements to safety.

700

Target (2.5% reduction)

VMT (100 M)

Fatality and VMT

500

600

480

500

460

400

440

300

420 400

200

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Fatality Target (12 reduction) VMT (100 M)

* 2015 Data is preliminary

VMT (100M)

Fatality Rate

CDOT Crash Database • Contains all crashes – statewide • All agencies • PDOs, injuries and fatalities • Extracted from DOR • Coded by CDOT temp staff • Once coded/summarized, data belongs to CDOT

CDOT Crash Database Crash Coding • Geo-locating – verify crash location on non-highway crashes using: • Cross streets • Fixtures, Land marks • Cleansing the data • QA/QC • Directions • Crash type corrections • Normalizing/Uniforming • Spell check • Data consistency: Example: Colorado, Colo, CO • Identifying roadway type • Highway • Local Roads • Private Roads

Colorado Crash Record Timeline Oversight STRAC / NHTSA / FHWA

Crash Occurs Department of Transportation

State Patrol

• Investigation • Writes the report

Department of Revenue Loads and input data into database

• Download DOR Data • QA/QC • Normalize Location Coding • Create Enhanced Data

Engineering

Planning

Safety

Law Enforcement

FARS

• Investigation • Writes the report

Other Stakeholders

Crash Occurs

CDOT Data Analysis and Dissemination

Local Agencies

Legislative Departments Public Requests

Crash Occurs

Public Relations

90th Percentile

90th Percentile

90th Percentile

46 Days

30 Days

56 Days

41 Days - Paper 5 Days - Electronic

State Patrol

132 Days - Coded 90th percentile records coded - 109 days

0 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101 105 109 113 117 121 125 129 133 137 141 145 149 153 157 161 165 169 173 177 181 186 190 194 199 203 207 211

Crashes

Days from crash date to coded date

700

600

500

400

300

200

100

0

Days

0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 97 100 103 106 110 113 116 119 123 126 129 132 136 142 146 149 152 155 158 161 165

Crashes

Days between crash date and DOR load date

900

800

700

600

500

400

300

200

100

0

Days

Programs and People Using Data • Federal Highway Administration • National Highway Traffic Safety Administration • Fatality Analysis Reporting System (FARS) • Highway Safety Improvement Program • FASTER Safety Mitigation Program • Statewide Plan • Strategic Highway Safety Plan • Office of Transportation Safety • Behavioral Programs • Fatality Analysis Reporting System • Legislative Requests • Colorado State Patrol

• Colorado Department of Health and Environment • CDOT Regions • MPO/TPR’s • Public Relations • Media • Researchers • Cities • Counties • Engineers • Planners • Law Enforcement • Public • Attorneys • Marijuana Data Advisory Committee

SPF Example 160

Urban 6-Lane Freeway

140

120

APMPY

100

80

60

40

20

0 20,000

130,000 AADT Corresponds to An Expected Accident Frequency of 60 Accidents Per Mile Per Year 40,000

60,000

80,000

100,000

120,000

AADT

140,000

160,000

180,000

200,000

LOSS

Statewide Analysis

Time of Day

Day of Week

Month of Year

Contributing Factor

Roadway Description

Vision Zero Suite - Output The data from vision zero can be output to Excel. This spreadsheet can be sorted, filtered and searched.

CDOT Data • CDOT can share data with stakeholders • Data sharing = Data driven decision making • Local agencies • Law Enforcement • Planners • Systemic mitigation – Identify locations similar to locations with crashes. • Use curve and crash data to project locations before crash patterns develop.

Law Enforcement – Using Data • • • •

Single crashes are random Crash patterns indicate potential for mitigation Different from Crime Analysis Measure Effectiveness • What works and what does not?

Law Enforcement – Using Data • DUI crash pattern • Identify liquor establishments, educate • Overlay with citation data • Identify where/when enforcement is needed • Improve campaigns • Audience • Location • Dates/Times

Law Enforcement – Using Data • Staffing • Do staffing levels/shifts match needs? • Improve response time • Predict locations for minimal response times • Sunglare • Weekend tourists vs commuting traffic • Focus enforcement activities using trends • Example: Rear end vs Sideswipe • Focus on following too close or improper lane changes

Future Database Connections

CDOT Roadway Data

DOR Legal Document

CSP Citation

Health & Human Services

Weather

DOR Driver / Vehicle

CDOT Crash Data

CDPHE Death Certifica

Maintenance

Operations / INRX Hospital / EMS

Existing connection Future connection

Liquor License

LLE Citation

Judicial Citations

Others

Future of Data • Analyze systemic data errors • Provide Law Enforcement Training • Electronic Form changes • Improve efficiencies at every level • Improve location information • Improve data sharing • Improve crash report, include data needs

Future of Data • Coordination of databases • Citation • Health data • EMS • Maintenance • Roadway • Traffic Operations • Identify Over/under representation projects • Enforcement • Education • After analysis of projects • Data driven deployment of resources

Alisa Babler, PE Data Unit Manager Colorado Department of Transportation TSM&O, Traffic Data Unit [email protected] 303-757-9967