Montgomery County Bicycling Crash Data Analysis
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1 Montgomery County Bicycling Crash Data Analysis Montgomery County Police Department Department of Transportation 8/7/2012
2 Principles Require Data-Driven Performance Promote Strategic Governance Increase Government Transparency Foster a Culture of Accountability Bicycle Crash Analysis 2
3 Meeting Goal Meeting Goal: Review bicycle crash information of other jurisdictions including those with bike sharing programs to assess if Montgomery County should expect an increase in occurrences when establishing a bike share program Review overall bicycle crash data in the County to inform the development of a bicycle safety strategy How we measure success: Identify high incident areas for targeted monitoring. Identify recommendations to improve bicycle safety and reduce risks of accidents. Bicycle Crash Analysis 3
4 Meeting Agenda Bicycle Crash Statistics for the State of Maryland Montgomery County Bicycle Crash Data High Incident Areas Identification of crash variables Bike Sharing Program Comparisons Implementation of Montgomery County s Bike Share Program Summary of Recommendations Wrap-Up and Follow-Up Items Bicycle Crash Analysis 4
5 Data Caveats Bicycle Crash Data County crash data is from incidents reported to the police. These incidents are usually more serious crashes involving car and bicyclist. Often there are crashes not reported, leading to a apparently lower volume of incidents Does not include pedestrian and bicycle incidences Incidences not on a roadway are not usually reported, or captured by Park Police Bicycle Usage in Montgomery County Montgomery County s last count for bicycle usage was in FY2009. Methodologies can vary between physical automated counters and using volunteers. Analysis of bicycle crash data will not meet all standards of statistical rigor due to small sample sizes, but comparison over time will yield meaningful results Bicycle Crash Analysis 5
6 Maryland Pedalcyclist Fatalities by County for 2010 Pedalcyclist Fatalities Pedalcyclist Fatalities per 100,000 (National Comparison) Compared to National rates, Montgomery County is in the lower third tier of pedalcyclist fatalities Source: National Highway Traffic Safety Administration Bicycle Crash Analysis 6
7 Maryland Pedalcyclist Fatalities by County Total Baltimore Worcester Carroll Montgomery Prince Georges Anne Arundel Calvert Harford Howard Queen Anne St. Mary Charles Frederick Talbot Wicomico * Jurisdictions with zero reported fatalities are omitted Source: National Highway Traffic Safety Administration Bicycle Crash Analysis 7
8 State of Maryland Data on Total Bicycle Crashes (1 of 2) Jurisdiction Avg Total 2010 Population 2010 Rate (per 100,000) Worcester , Talbot , Baltimore City , , Wicomico , Dorchester , Washington , Somerset , Cecil , Anne Arundel , Baltimore County , Source: State of Maryland; Population data from US Census Bureau Bicycle Crash Analysis 8
9 State of Maryland Data on Total Bicycle Crashes (2 of 2) Jurisdiction Avg Total 2010 Population 2010 Rate (per 100,000) Montgomery , Howard ,085 9 Harford ,826 9 Prince George's ,420 9 Queen Anne's ,798 8 Charles ,551 8 St. Mary's ,151 8 Allegany ,087 5 Frederick ,385 5 Calvert ,737 5 Carroll ,134 3 Kent ,197 0 Caroline ,066 0 Garrett ,097 0 Source: State of Maryland; Population data from US Census Bureau Bicycle Crash Analysis 9
10 Police Analysis of 2011 Montgomery County Bike Crash Data: Time of Day / Day of Week Most bicycle collisions occur afternoon to early evening on weekdays, with the greatest cluster seen on Tuesdays around 6 PM In 2011, 76.7% of bicycle collisions occurred during daylight hours Source: Montgomery County Police Department, 2011 Bicycle Collisions Bicycle Crash Analysis 10
11 Crashes Police Analysis of 2011 Montgomery County Bike Crash Data: Time of Year 25.0 Summer months have higher occurrences of crashes. This corresponds with reports from other jurisdictions. Bicycle Collisions by Month Bicycle Collisions by Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Average 2011 Source: Montgomery County Police Department, 2011 Bicycle Collisions Bicycle Crash Analysis 11
12 Police Analysis of 2011 Montgomery County Bike Crash Data: Fault At Fault Units Driver % of Total 53.33% 36.75% 42.11% 42.86% 49.64% 44.19% Bicyclist % of Total 45.00% 60.68% 55.79% 56.19% 41.01% 44.19% Both % of Total 1.67% 2.56% 2.11% 0.95% 2.88% 8.53% Not Determined % of Total 0.00% 0.00% 0.00% 0.00% 6.47% 3.10% Total The percentage of incidents in which both the driver and bicyclist are determined to be at fault has increased significantly since Source: Montgomery County Police Department, 2011 Bicycle Collisions Bicycle Crash Analysis 12
13 Police Identification of Montgomery County High Incident Areas Through geospatial analysis of CY2011 data, Police identified 5 bicycle crash hotspots Bicycle Crash Analysis 13
14 2011 Bicycle Crash High Incident Areas Region Streets Reported Incidents Area 1 Germantown Middlebrook Rd Wisteria Dr 5 Area 2 Wheaton-Glenmont Veirs Mill Rd Randolph Rd 4 Area 3 Forest Glen Georgia Ave Forest Glen Rd 6 Area 4 Silver Spring Georgia Ave Fenton St Dartmouth Ave Mayfair Pl 9 Area 5 Bethesda Old Georgetown Rd Woodmont Ave Arlington Rd 8 The five high incident areas identified by Police appear in more densely populated regions of the County, near busy County roads and intersections. Bicycle Crash Analysis 14
15 Police Geospatial Comparison of Bicycle and Pedestrian Collisions 2011 Bicycle Crash Analysis 15
16 Police Geospatial Comparison of Pedestrian Collisions to Bicycle Collision High Incident Areas Bicycle Crash Analysis 16
17 Typical Reported Bicycle Crash Types Bicyclists rides out at stop signal or stop sign. The crash occurred at an intersection (signaled or uncontrolled) at which the bicyclist failed to yield. Motorist drives out at stop sign. The crash occurred at an intersection at which the motorist was facing a stop sign/signal. Source: Bicycle Crash Analysis 17
18 Typical Reported Bicycle Crash Types Motorist left turn, facing bicyclist. The motorist made a left turn while facing the approaching bicyclist. Motorist right turn. The motorist was making a right turn and the bicyclist was riding in either the same or opposing direction Bicyclist left turn in front of traffic. The bicyclist made a left turn in front of traffic traveling in the same direction.. Source: Bicycle Crash Analysis 18
19 Typical Reported Bicycle Crash Types Motorist Drives Out at Midblock The motorist was entering the roadway from a driveway or alley. Motorist Turned or Merged Right into Path of Bicyclist A motorist turns right, striking a bicyclist which was approaching from the opposite direction. The bicyclist is most likely riding the wrong way, against traffic, but could be legally riding on the sidewalk or an adjacent shared-use path. Source: Bicycle Crash Analysis 19
20 High Incident Area #1: Germantown Language in Reports # % Crosswalk 5 100% Sidewalk 1 20% Intersection 1 20% Yield 2 40% Driveway 0 0% Parking Lot 0 0% Turn 3 60% Right 4 80% Left 2 40% Turn + Left or Right 4 80% Crosswalk + Turn 3 60% Sidewalk + Turn 0 0% Intersection+ Turn 1 20% All of the incidents which occurred in Area 1 involved crosswalks, and most involved turning vehicles. Bicycle Crash Analysis 20
21 High Incident Area #2: Wheaton-Glenmont Language in Reports # % Crosswalk 1 25% Sidewalk 1 25% Intersection 1 25% Yield 0 0% Driveway 0 0% Parking Lot 0 0% Turn 2 50% Right 2 50% Left 0 0% Turn + Left or Right 2 50% Crosswalk + Turn 0 0% Sidewalk + Turn 0 0% Intersection+ Turn 1 25% Half incidents in Area 2 involved turning vehicles. All incidents occurred on Veirs Mill Road or Randolph Road. Bicycle Crash Analysis 21
22 High Incident Area #3: Forest Glen Language in Reports # % Crosswalk 2 33% Sidewalk 3 50% Intersection 3 50% Yield 0 0% Driveway 2 33% Parking Lot 0 0% Turn 4 67% Right 3 50% Left 1 17% Turn + Left or Right 3 50% Crosswalk + Turn 2 33% Sidewalk + Turn 2 33% Intersection+ Turn 2 33% The incidents in Area 3 occurred on Georgia Avenue or Forest Glen Road. More than half involved turning vehicles, and at least half involved either a crosswalk, sidewalk, or intersection. Bicycle Crash Analysis 22
23 High Incident Area #4: Silver Spring Language in Reports # % Crosswalk 1 11% Sidewalk 5 56% Intersection 1 11% Yield 0 0% Driveway 2 22% Parking Lot 3 33% Turn 7 78% Right 3 33% Left 2 22% Turn + Left or Right 3 33% Crosswalk + Turn 1 11% Sidewalk + Turn 5 56% Intersection+ Turn 1 11% The majority of incidents in Area 4 involved turning vehicles and sidewalks or crosswalks. Bicycle Crash Analysis 23
24 High Incident Area #5: Bethesda Language in Reports # % Crosswalk 5 63% Sidewalk 2 25% Intersection 1 13% Yield 2 25% Driveway 1 13% Parking Lot 0 0% Turn 6 75% Right 4 50% Left 3 38% Turn + Left or Right 5 63% Crosswalk + Turn 4 50% Sidewalk + Turn 2 25% Intersection+ Turn 1 13% The majority of incidents in Area 5 involved turning vehicles and crosswalks or sidewalks. Bicycle Crash Analysis 24
25 Comparison of Crash Variables: Overall vs. High Incident: Location Variables Location Variables All Reported Crashes (400 incidents) High Incident Areas (32 incidents) Crosswalk % 14 44% Sidewalk % 12 38% Intersection 77 19% 7 22% Yield 71 17% 4 13% Driveway 68 17% 5 16% Parking Lot % 3 9% Data from January 1, 2009-June 4, 2012, 400 recorded incidents Crosswalks and sidewalks were the most common variable among all reported crashes; however, the prevalence of crashes involving crosswalks was higher within the high incident areas. Sources: MCPD Police Reports Bicycle Crash Analysis 25
26 Comparison of Crash Variables: Overall vs. High Incident: Turning Variables Turning Variables All Reported Crashes (400 incidents) High Incident Areas (32 incidents) Turn % 22 69% Right 52 13% 16 50% Left 62 15% 8 25% Turn + Left or Right of any Combination % 17 53% Crosswalk + Any Turn 69 61% 10 31% Sidewalk + Any Turn 56 54% 9 28% Intersection+ Any Turn % 6 19% Data from January 1, 2009-June 4, 2012, 400 recorded incidents The combination of the crosswalk/sidewalk/intersection and turn variables was more common in the total pool of incidents than those occurring in the high incident areas. Sources: MCPD Police Reports Bicycle Crash Analysis 26
27 Comparison of Crash Variables: Overall vs. High Incident: Vehicle Movement Variables Turning Variables All Reported Crashes (400 incidents) High Incident Areas (32 incidents) Moving at a Constant Speed % 7 22% Making right-turn 69 16% 8 25% Making left-turn 62 14% 5 16% Walking/Riding w/traffic 89 23% 6 19% Cross/Enter at intersection % 10 31% Data from January 1, 2009-June 4, 2012, 400 recorded incidents Relative to all reported crashes, there was a higher occurrence of the making a right-turn variable among the high incident area crashes. Bicycle Crash Analysis 27
28 Montgomery County Bikeshare Awarded two grants Job Access Reverse Commute Federal FTA Grant administered through MWCOG Quantity: 200 bicycles, 20 stations Locations: Rockville & Shady Grove Metro Stations, Greater Shady Grove TMD including Life Sciences Center, Rockville Town Center, employment centers along MD-355, Campuses of Montgomery College Rockville, the Universities at Shady Grove, Johns Hopkins. Status: Procurement Contract After contract 4-6 months to order/receive equipment Several weeks for installation of full system Maryland DOT Grant [Possibly Federal Congestion Mitigation/Air Quality Funds (CMAQ)] Quantity: 204 bicycles, 29 stations Locations: Silver Spring, Takoma Park, Friendship Heights (Chevy Chase), Bethesda, and the Medical Center area. Status: Post-Award Stage with State After Contract/Procurement 4-6 months to order/receive equipment Several weeks for installation of full system Source: Montgomery County DOT Bicycle Crash Analysis 28
29 Bikesharing Program Benchmark Comparison conducted a nation-wide analysis of analysis of bike sharing programs The size and maturity of bikesharing programs varies greatly amongst jurisdictions Many jurisdictions conducted analysis of cycling volume to determine crash rates Capital Bikeshare station in Arlington, VA In addition to the creation of bikesharing initiatives, some jurisdictions also pursued a Bicycle Friendly America Rating conducted by the League of American Bicyclists According to data pertaining specifically to bikesharing incidents, jurisdictions reported that these initiatives are not a large driver of cycling crashes or fatalities. Bicycle Crash Analysis 29
30 Bike Sharing Program Benchmark Data Reported Bicycle-Vehicle Crash Data by Jurisdiction Location Denver, CO N/A N/A N/A N/A Minneapolis, MN N/A San Antonio, TX N/A N/A N/A Madison, WI N/A Boulder, CO N/A N/A N/A Arlington, VA Washington, DC N/A Montgomery County (Police Data) Washing Council of Governments *(Accidents with Injuries) N/A Although Capital Bikeshare reports only 30 accidents related to the initiative since its start in September 2010, crashes were higher in 2010 for both Washington DC (24%) and Arlington VA (33%) than 2009 N/A: No Public Report available. Sources: Respective jurisdictions reports. *Metro Washington COG Report: Bicycle Crash Analysis 30
31 Bike Sharing Program Benchmark Data Denver, CO B-cycle Location Minneapolis/St. Paul, MN Nice Ride Arlington, VA Capital Bikeshare Washington, DC Capital Bikeshare Miami Beach, FL DecoBike San Antonio, TX B-Cycle Madison, WI B-Cycle Boulder, CO, B-cycle Boston, MA New Balance Hubway Broward County, FL B-Cycle Jurisdiction Pop. Size (Metro Area) Start Date* System Bike Size (Jan 2012)* Reported Accidents ** Fatalities ** Total Trips (Jul 2012)* 600, , Apr , , , Jun , , , , Sep 1,200 (System Wide) ,200,000 87, , Mar ,000,000 1,327, , Mar , , , May N/R 97, , May , , , Jul N/R 1,748, , Dec ,200 ** Self-reported by jurisdiction * Sources: Mineta Transportation Institute, Public Bikesharing in North America: Early Operator and User Understanding Bicycle Crash Analysis 31
32 Bike Sharing Program Benchmark Data Location Denver, CO B-cycle Minneapolis, MN Nice Ride Arlington Capital Bikeshare Washington, DC Capital Bikeshare Miami Beach, FL DecoBike San Antonio, TX B-Cycle Madison, WI B-Cycle Boulder, CO, B-cycle Boston, MA New Balance Hubway Broward County, FL B-Cycle Jurisdiction Size Have Counters for Volume of Cyclists Data Bicycle Friendly America Rating (By League of American Bicyclists) 600,158 Stationary Counters Silver 667,646 Stationary Automatic Counters/Volunteers Gold 207,627 Stationary Automatic Silver 601,723 None N/A 87,779 No Response N/A 1,327,407 None Bronze 233,209 Stationary Automatic Counters Gold 97,385 Stationary Automatic Counters Platinum 617,594 Annual Counts in Sept/Oct Silver 1,748,066 None N/A Some locations have counters but are often unable to do annual analysis on the data collected. Sources: Local jurisdictions phone interviews; Mineta Transportation Institute, Public Bikesharing in North America: Early Operator and User Understanding Bicycle Crash Analysis 32
33 Overview of Strategies for Mitigating Bicycle Crashes Road markings for a bike lane and sharrows currently used in the County. Two bike-friendly signs currently used in the County Safety education graphic from Nice Ride MN website Strategy Shared Roadway: On-Road Bike Facilities: Intersection Treatments: Maintenance: Traffic Calming: Trails/Shared- Use Paths: Markings, Signs, Signals: Education and Enforcement: Support Facilities and Programs: Description The goal of an appropriately designed roadway should be to safely and efficiently accommodate all modes of travel, from bicyclists to pedestrians to motorists. Various kinds of on-road facilities, such as bike lanes, paved shoulders, and wide curb lanes, make bicyclists more comfortable. Nearly half of all bicycle-motor vehicle crashes occur at intersections or other junctions. Maintenance of all kinds of bicycle facilities must be planned for and done routinely. Traffic calming is a way to design streets, using physical measures, to encourage people to drive more slowly. Bike paths or shared-use trails are complementary to the road network and serve recreational, child, and even commuter bicyclists. Traffic engineers have an arsenal of pavement markings, signs, and signals that can be used to inform, regulate, and warn both motorists and bicyclists. Education and enforcement are key strategies in increasing bicyclist and motorist awareness and behavior. The simple promotion of bicycling is a way to increase the amount of riding in a community. Bicycle Crash Analysis 33
34 DOT Engineering Highlights and Recommendations: Project Selection Criteria Prioritization of Projects If the improvement is part of master plan If project fills in or completes major gap along countywide bikeway If there is large demand for project If project is correcting an unsafe condition If project promotes alternative modes of transportation to car If project is cost-effective If project connects major destinations If project requires only signage improvements Avenues for Public Opinion Montgomery County Bicycle Action Group (MCBAG) Transportation Management District (TMD) Advisory Committees Annual Commuter Survey Surveys include opportunity for comments Pedestrian Bicycle & Traffic Safety Advisory Committee Communications via public box, response to e-newsletter articles, & inperson events; feedback on bike maps, other bike information Source: Montgomery County DOT, Council Hearing in Fall of 2011; Commuter Services Section, Div. of Transit Services. Bicycle Crash Analysis 34
35 DOT Engineering Highlights and Recommendations: Bikeways Creation Ways to achieve Bikeways in Montgomery County Large CIP Projects Stand Alone CIP Projects Have completed Facility Planning Private Developer Requirements and as part of the other Government projects Annual Road Maintenance Annual Bikeways Program Typical Types of Bikeways: 1) Marked Bike Lanes 2) Signed Shared Roadways 3) Shared Use Paths Source: Montgomery County DOT Bicycle Crash Analysis 35
36 Recommendations Enforcement campaign should target both drivers and cyclists During a successful enforcement campaign in Boston, police issued 220 tickets to cyclists and 279 tickets to drivers, and distributed more than 700 helmets. Crash variables should be used to create targeted mitigation strategies Bicycle safety campaign should have a strong education component Boston Bikes conducted a major outreach campaign to cyclists and drivers. Boston Public School interns took to the streets to flier 10,000 bicycles with safety information, and the City mailed fliers to every registered driver in Boston via excise tax mailings, totaling nearly 500,000. In partnership with MassBike, the City also offered live bike safety education classes several times per month at multiple locations throughout the summer. Bikeshare bikes should display safety tips and warnings both on the bicycle and via program documentation Continual monitoring of crash variables in both high incident areas and throughout the County Bicycle Crash Analysis 36
37 Wrap-Up and Follow-Up Items Bicycle Crash Analysis 37
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