2009 TOP CRASH LOCATIONS REPORT

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22000099TTOOPP CCRRAASSHH LLOOCCAATTIIOONNSS RREEPPOORRTT

AUGUST 2011


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Devil I L PillrlLk. Governornm o ttlY P Murray Lt GovernorJe ffrey B Mullan. Secretmy [,. CEO l J l q l . ~ e . Q [rank DeP ,lQ l' AC [lng Adn llnl Slrator I l g h W a y Division

Dear Reader:Enclosed is MassDOT Highway Division's edition of the 2009 Top Crash LocationsReport, which may be used to evaluate top crash intersection locations and top crashpedestrian and bicycle locations in order to improve the safety of our roadway system.This report, like last year's report, focuses on intersection locations and is based oncrashes entered into the Registry of Motor Vehicles' Crash Data System (CDS). The 2009Report contains the identification of top bicycle-motor vehicle and pedestrian-motorvehicle crash locations. This informat ion is also available by contacting your RegionalPlanning Agency and MassDOT Highway District Traffic Engineer.In an effort to reduce injury and fatal crashes, MassDOT, in cooperation with a variety ofpublic and private safety stakeholders, is in the process of updating the MassachusettsStrategic Highway Safety Plan (SHSP). To view the original SHSP (from 2006), downloada copy of the Plan or to learn more about it, go to the MassD OT Highway Division Traff icEn gineering and Safety w ebs ite. The Safety Plan identifies the State's key safety needsand can be used to guide investment decisions to achieve significant reductions inhighway fatalities and serious injuries on all public roads based upon a data-drivenprocess.This dataset may be used as a screening tool to evaluate locations and make changes toimprove the safety of our roadway system. The 2009 Top Crash Locations Report s oneof the tools for the statewide Highway Safety Improvement Program (HSIP) to identifysafety projects using a data-driven process.Please note that this report is based only on crash records that have been entered intothe statewide crash system and have been geocoded to a specific location. AlthoughMassachusetts General Laws Chapter 90 26 and 29 require drivers and policedepartments to file crash reports that exceed specific thresholds, this is no t always thecase. Furthermore, no t all crashes submitted to the Registry of Motor Vehicles getentered into the crash system. Improving the crash reporting system and the quality ofthe data will help to focus resources where they are most needed.I am convinced that we can make great strides in improving safety on Massachusettsroadways for all users. If you have questions, please contact Neil Boudreau, State TrafficEngineer at (617) 973-821 I.Sincerely,

Frank DePaola, P.E.Administrator

Ten Park Plaza, Suite 4160, Boston, MA 021 16Tel: 617-973-7000, TDD: 617-973-7306Leading the Nation in Transportation Excellence www.mass .gov/ massdot
http:///reader/full/www.mass.govhttp:///reader/full/www.mass.govhttp:///reader/full/www.mass.govhttp:///reader/full/www.mass.govhttp:///reader/full/www.mass.govhttp:///reader/full/www.mass.gov


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TOP HIGH CRASH LOCATIONS REPORT Top 200 Intersection Locations 2007-2009 Top Pedestrian Locations 2002-2009

Top Bicycle Locations 2002-2009

IntroductionMassDOT Highway Division obtains crash data from the MassDOT Registry of MotorVehicles (RMV) Division and uses it for a number of purposes. The primary function is toprovide a foundation for developing safety improvement projects. The Top High CrashLocations Report is one of the tools used in this process. Previously, MassDOT HighwayDivision, with the assistance from Central Transportation Planning Staff (CTPS), produceda Top 1000 Highway Crash Locations Report which included all types of locations(interchanges, intersections and rotaries). Three years ago, MassDOT Highway Divisiondeveloped a new report type where the locations identified were crash clusters atintersections (no grade separated locations and no locations with weaving sections).Beginning two years ago, the report also included the top bicycle and pedestrianclusters. This year, MassDOT Highway Division has also prepared a Top High CrashLocations Report which includes the top 200 high crash intersection locations usingcrash data from 2007-2009 and also includes the weighted (by crash severity) highestfrequency bicycle-motor vehicle and pedestrian-motor vehicle crash locations for 20022009.The RMV obtains crash data from State and local police reports and from motor vehicleoperators (motorists) wh o are involved in crashes. The RMV Crash Records Sectioncollects, enters and maintains crash data records, which are the source of the MassDOTHighway Division crash data.To produce this high crash locations listing, MassDOT Highway Division, with theassistance of Geonetics, has developed an automated procedure fo r processing,standardizing, matching and aggregating the crash data by geographical location usingGeographic Information System (GIS) tools and procedures.Generally, the geocoding rate (the rate at which crashes can be located to a specificgeographical point) for crashes between 2007 and 2009 is near ly 89%. However, thegeocoding rate is no t uniform for all crashes or for all types of crash locations. Somecrashes may be more difficult to geocode because of multiple intersections between thesame roadway names within a community, mis-entry of location information on thecrash repor t form or a host of other reasons.


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The number of crashes contained within the RMV crash system has changeddramatically due to a shif t in data entry. General the crash system is comprised of crashreports from police and operators (drivers). The number of operator reports enteredinto the statewide crash system has declined dramatically. The table below illustrates thechange in data entry at the RMV.

Reporting Entity 2005 2006 2007 2008 2009Operator 40,098 40,533 34,348 26,715 9,303Local police 102,698 94,602 95,400 93,649 92,819Other 353 201 153 198 123State police 14,935 14,524 14,608 15,822 15,519TOTAL 158,084 149,860 144,509 136,384 117,764

Furthermore, the repor ting levels of some communities have changed dramaticallybetween the old reporting format (pre-2002) and the new format and as communitiesmove from submitting on paper to submitting electronically (details on reporting level bycommunity are available upon request). Obviously, these report ing changes significantlyimpact the results of the Top High Crash Locations Report.Due to the many difficulties in obtaining precise, useable crash location data and manyissues involved in variations in crash reporting rates by some urisdictions, this reportshould be used as a general purpose screening tool rather than as a precise listing ofcrash frequencies by individual locations. Furthermore, because of the spatial nature ofthe crash clusters, it is imperative to view the crash clusters spatially and no tjust rely onthe tabular naming convention to understand the crash cluster locations.Methodology - Intersection LocationsThe intersection crash cluster analysis method, developed by Geonetics for MassDOT, is acomprehensive method designed to locate crash clusters. At the heart of the method isa 25 meter (82 ft.) fixed search distance around each crash. In basic terms, this radiuscontrols how far the application will search for adjacent crashes. Using a 25 meterradius, the analysis method found nearby crashes and merged their areas together, thuscreat ing clusters. If two distinct clusters are found to share a common crash, the twoclusters are merged into a single cluster. This method of search-and-merge results in a setof many distinct clusters of different sizes and shapes The application then stores theseclusters to the GIS output file, along with the count of crashes within the cluster. Theclusters were then ranked by the number of Equivalent Property Damage Only (EPDO)crashes contained within their boundaries. As in previous Top Crash Lists, fatal crashesare weighted by 10, injury crashes are weighted by 5 and property damage only or nonreported is weighted by 1. These are the same weights that were used to generate the


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previous Top 1000 High Crash Locations Report using crash data f rom the previouscrash system.The crashes were then named based on the highest functional classification roadwaywithin the cluster, followed by the roadway with the second highest functionalclassification. In instances where there were two roadways with the identicalclassification, the first street name selected was the street with the longest segmentcontained within the cluster. Some cluster naming was modified to insert the name of aprivate way or site drive, rather than leaving it as unnamed. Note that the areaencompassing the crash cluster may cover a larger area than just the intersection.The module to automatically determine whether the location was an intersection, rotary,interchange or other type of facility has not yet been developed. Therefore, a review ofeach location was required to make that determination. Generally, a location wasdetermined to be an "intersection" if the cluster did no t contain roadways with gradeseparation (interchange) nor weaving sections (rotaries or ramps). The clusters werereviewed in descending EPDO order until 200 locations were obtained. A sample of thetop 2 ranked intersection locations is included in this report to illustrate the concept ofthe intersection clustering. The actual crash clusters can be viewed on the interactivemaps at mass.Qov/mhQ/topcrashclusters. Furthermore, a shape file of the top crashintersection locations is available upon request.The above method was used to develop the top 200 intersection crash locations forcrashes occurring during the three year period from 2007 to 2009. As with previouseditions, the crash location analysis has been scored over a three-year period. By usingcrash experience over the three-year period, anomalies in the individual years of datatend to be reduced.Methodology - Pedestrian and Bicycle LocationsSimilar to previous years, the top locations where reported collisions occurred betweenpedestrians and motor vehicles and bicycles and motor vehicles have been identi fied.The crash cluster analysis methodology for both the top pedestrian and the top bicyclecrashes is similar to the top intersection location methodology in that it uses a fixedmeter search distance (for both pedestrian and bicycle crashes it is 100 meters (328 ft.)compared to 25 meters for intersection locations) to merge crash clusters together.Crashes involving collisions between motor vehicles and pedestrians or bicycles wereidentified by using the non-motorist type code within the CDS database (which mayyield,different results from using most harmful event, first harmful event, or sequence ofevents data fields). Furthermore, the methodology uses the Equivalent PropertyDamage Only (EPDO) weighting to rank the clusters. However, because of the relativelysmall number of reported pedestrian and bicycle crashes in the crash data file, theclustering analysis used crashes from the eight year period from 2002-2009, instead of


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the three year analysis for intersection locations. Additionally, due to the largergeographic area encompassed by both the p e d e s t r i ~ n and the bicycle crash clusters, itwas difficult to name them so they were left unnamed bu t can be viewed spatially. Thetop 10 ranked pedestrian crash locations and the top 10 bicycle crash locations areincluded in this report. The actual crash clusters can be viewed on the interactive mapsat mass.gov!mhd/ topcrashclusters.For further information, please contact Neil Boudreau, State Traffic Engineer, TrafficEngineering and Safety Section, MassDOT Highway Division, 10 Park Plaza, Room 7210,Boston, MA 02116, phone (617) 973-8211.

NOTICEIt should be noted that the Top 200 High Crash IntersectionLocations Report was compiled under the authority of United StatesCode Title 23, Section 148, Highway Safety Improvement Program,s p ~ n s o r e d by the Federal Highway Administration. The compilationof such information is, therefore, subject to the limitations of Section148 (g) (4) which states:

"Discovery and admission into evidence of certain reports, surveys,and information - Notwithstanding any otherprovision of law,reports, surveys, schedules, lists, or data compiled or collected for anypurpose directly relating to paragraph (1) or subsection (cJ( 1J(D), orpublished by the Secretary in accordance with paragraph (3), shallnot be subject to discovery or admitted into evidence in a Federal orState court proceeding or considered for other purposes in any actionfor damages arising from any occurrence at a location identified oraddressed in such reports, surveys, schedules, lists, or other data."
http:///reader/full/mass.govhttp:///reader/full/mass.govhttp:///reader/full/mass.govhttp:///reader/full/mass.govhttp:///reader/full/mass.gov


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2007-2009 STATEWIDE TOP 200 INTERSECTION CRASH LIST

Rank

Town

RPA

MassDOTDistrict

Street1

Route1

Street2

185 LOWELL NMCOG 4 BROADWAY FLETCHER STREET

185 ABINGTON OCPC 5 BROCKTON AVENUE 123 BEDFORD STREET

185 HOLYOKE PVPC 2 LOWER WESTFIELD ROAD WHITING FARMS ROAD

185 LYNN MAPC 4 CENTRAL AVENUE WASHINGTON STREET

185 BOSTON MAPC 6 BLUE HILL AVENUE 28 MORTON STREET

185 WESTBOROUGH CMRPC 3 BOSTON WORCESTER TURNPIKE 9 LYMAN STREET

193 WEYMOUTH MAPC 6 UNION STREET PLEASANT STREET

193 WATERTOWN MAPC 6 MAIN STREET 20 MOUNT AUBURN STREET

195 RANDOLPH MAPC 6 NORTH MAIN STREET 28 UNION STREET

195 LYNN MAPC 4 WESTERN AVENUE 107 PARK STREET

195 WALTHAM MAPC 4 LEXINGTON STREET TOTTEN POND ROAD

195 BROCKTON OCPC 5 BELMONT STREET 123 BELMONT AVENUE

195 LAWRENCE MVPC 4 ANDOVER STREET PARKER STREET

195 WEYMOUTH MAPC 6 PLEASANT STREET WASHINGTON STREET

195 BROCKTON OCPC 5 NORTH MAIN STREET EAST ASHLAND STREET

195 SOUTHBOROUGH MAPC 3 TURNPIKE ROAD 9 OAK HILL ROAD

195 HOLYOKE PVPC 2 WESTFIELD ROAD 202 HOMESTEAD AVENUE

195 RAYNHAM SRP EDD 5 BROADWAY 138 CARVER STREET

205 MALDEN MAPC 4 EASTERN AVENUE 60 MAPLEWOOD STREET

205 HAVERHILL MVPC 4 MAIN STREET 97 BAILEY BOULEVARD

205 STONEHAM MAPC 4 MAIN STREET 28 NORTH BORDER ROAD

205 TAUNTON SRP EDD 5 COUNTY STREET 140 HART STREET

8/23/2011


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Top Crash Intersections 2007-2009 ......

RANKLOWELL 1VETERANS OF FOREIGN WARS HIGHWAYVARNUM AVENUE

LegendMassDOT Drstl'oct 4RPA NMCOG Crash locations 2007-2009EPDO 281 Loca l RoadsNtrnl>er er


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Top Crash Intersections 2007-2009 -----:

RANKBROCKTON 2PLEASANT STREET ROlJTE 27WEST STREET

LegendMassDOT Drstlie! 5RPA OCPC Crash locations 2007 -2009EPDO 242 Loca l Ro adsNtrnl>er er


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Top Pedestrian Crash Cluster 2002-2009

!, 1,225 2,450 3,675 ARANK

1 Lege"'CHELSEA Pedestrian Q-ash Locations 2002-2009 epA w>PC local RoodsEPDO 518

NumOOr of Falai Pedestr ian C ,a';',," / " 'V Al l Functional Classification Except Local RoaNu mbef of Injury Pedestr ian era sI1"s 95 o Top Pedestrian Crash OusterNu mbef of Non njury Pedestrian e ra"",," 33 Tota l Pedest rian Crashes 129 ( = : ~ ) MUflK:ip


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1,300 2,600

5,200

RANK2

Lege"'FALL RIVER Pedestrian Q-ash Locations 2002-2009RPA 9


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ffI

1,450 2,175

RANK3

Lege"'CAMBRIDGE Pedestrian Q-ash Locations 2002-2009 epA w>PC local RoodsEPDO 284 NumOOr of Falai Pedestr ian C ,a ' ; ' ,," 2 / " 'V Al l Functional Classification Except Local RoaNumbef of Injury Pedestr ian era sI1"s 43 o Top Pedestrian Crash O usterNumbef of Non njury Pedest rian e ra"" ,, " 49 Tota l Pede st ria n Crashe s ( = : ~ ) MUflK:ip


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- CON GRESS A LlEY-.. CON GRESS STREET"f

, ", 1,400 2,100 2,800RANK

4Lege"'WORCESTER Pedestrian Q-ash Locations 2002-2009RPA CMRPC local RoodsEPDO 187

Nu mOOr of Falai Pedestr ian C ,a';',," 0 / " 'V Al l Functional Classification Except Local RoaNu mbef of Injury Pedestr ian era sI1es 36 o Top Pedestrian Crash OusterNu mbef of Non nju ry Pedestr ian era"",," 7Tota l Pedestrian Crashes 43 ( = : ~ ) MUflK:ip


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//

IFeet1,125 1,687_5 2,250

LOWELLRPA NMCOGEPDO 179Nu mOOr of Fal ai Pedestr ian C,a ;' ,," 0Nu mbef of Injury Pede str ian e rasI1"s 32Nu mbef of Non njury Pede st rian e ra"" ,, " 19To ta l Pede st rian Cras he s 51

RANK5

Lege"' Pedestrian Q-ash Locations 2002-2009

local Roo ds/ " 'V Al l Functional Classification Except Loc al Roao Top Pedestrian Crash O uster ( = : ~ ) MUflK:ip


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1,300 1,950 2,600

RANK6

Lege"'SOMERVIL LE ,CA MB RIDG E Pedestrian Q-ash Locations 2002-2009 epA w>PC local RoodsEPDO 175 Nu mOOr of Falai Pedestr ian C ,a';',," 1 / " 'V Al l Functional Classification Except Local RoaNu mbef of Injury Pedestr ian era sI1"s 32 o Top Pedestrian Crash OusterNu mbef of Non nju ry Pedestr ian era"",," 5 Tota l Pedest rian Crashes 38 ( = : ~ ) MUflK:ip


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NORTHAMPTONepA ""'"EPDO 152 Nu mOOr of Falai Pedestr ian C ,a ' ; ' ,, " 1 Nu mbef of Injury Pede str ian e rasI1"s 28 Nu mbef of Non njury Pede st rian e ra"" ,, " 2 To ta l Pedest rian Cras he s 31

1,150 1,725 2,300

RANK7

Lege"' Pedestrian Q- ash Locat ions 2002-2009

local Roods/ " 'V Al l Functional Classification Except Loc al Roao Top Pedestrian Crash O uster( = : ~ ) MUflK: ip


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'" 1,350 2,025 2,700 RANK

8 Lege"'QUINCY Pedestrian Q-ash Locations 2002-2009 epA w>PC local RoodsEPDO 150

Nu mOOr of Falai Pedestr ian C ,a ' ; ' ,," 0 / " 'V Al l Functional Classification Except Loc al RoaNu mbef of Injury Pede str ian e rasI1"s 26 o Top Pedestrian Crash O usterNu mbef of Non njury Pede st rian e ra"" ,, " 20 To ta l Pedest rian Cras he s 46 ( = : ~ ) MUflK:ip


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", 1,400 2,100!

I

IFeet2,800

il "I I ,

RANK9

Lege"'FRAMINGHAM Pedestrian Q-ash Locations 2002-2009epA w>PC local RoodsEPDOl44NumOOr of Falai Pedestr ian C ,a';',," 0 / " 'V Al l Functional Classification Except Local RoaNu mbef of Injury Pedestr ian era sI1"s 28 o Top Pedestrian Crash OusterNu mbef of Non nju ry Pedest rian e ra"",," 4Tota l Pedest rian Crashes 32 ( = : ~ ) MUflK:ip


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! IFeet, A,500 2,250 3,000RANK

10

LYNN Lege"' Pedestrian Q-ash Locations 2002-2009epA w>PC local RoodsEPDOl23Nu mOOr of Falai Pedestr ian C ,a';',," 0 / " 'V Al l Functional Classification Except Local RoaNu mbef of Injury Pedestr ian era sI1"s 23 o Top Pedestrian Crash OusterNu mbef of Non njury Pedest rian e ra"",," 8Tota l Pedest rian Crashes 31 ( = : ~ ) MUflK:ip


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Top Bicycle Crash Cluster 2002-2009

CAMBRIDGEWA w>PC EPDO 276 Nu mOOr of Fatal Bicycle Crashe s 1 Nu mOOr of Injury Bicycle Crashes 47 Number of N o o ~ n i u r y Bicycle Crashes 31 Tota l Bicyde Cr.""", 79

1,425

RANK2

Lege"' Bicycle Crash Locations 2002-2009

local Roods/ " 'V Al l Functional Classification Except Local Roao Top Bicyde Q-ash Cluster( = : ~ ) MUflicip


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Top Bicycle Crash Cluster 2002-2009 , , ~ ~ - ' - - - . ,

, 1,450 2,175RANK

3Lege"'CAMBRIDGE,SO MERVI LLE Bicycle Crash Locations 2002-2009WA w>PC local RoodsPDO 242

Nu mOOr of Fata l Bicyc le Crashes 0 / " 'V Al l Functional Classification Except Loc al RoaNumber of Injury Bicyc le Crashes 45Number of N o o ~ n i u r y Bicyc le Crashes 17 o Top Bicyde Q-ash ClusterTota l Bicyce Cr.""" , 62 ( = : ~ ) MUflicip


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IFeet1,000

CAMBRIDGEW A w>PCEPDO 157Nu mOO r of Fata l Bicyc le Crashe s 0Number of Injury Bicyc le Cras hes 28Number of ~ n i u Bicyc le Cras hes 17Tota l Bicyde Cr. """ , 45

RANK4

Lege"' Bicycle Crash Locations 200 2-2009

local Roods/ " 'V Al l Functional Classification Except Loc al Roao Top Bicyde Q-ash Cluste r ( = : ~ ) MUflicip


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"iAGG ST ' i Er 8"1


, 1,200RANK

5Lege"'CAMBRIDGE Bicycle Crash Locations 2002-2009WA w>PC local RoodsPDO 11 0

NumOOr of Fata l Bicyc le Crashe s 0 / " 'V Al l Functional Classification Except Loc al RoaNumber of Injury Bicyc le Crashe s 20Number of N o o ~ n Bicycle Crashes 10 o Top Bicyde Q-ash ClusterTota lBicyde Cr.""", 30 ( = : ~ ) MUflicip


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Top Bicycle Crash C luster 2002-2009

, , , 0 , 1

.....RV(y S r R ~ H , , ,0OOOlEYSTR E ET , A37.5 1,312 .5 1,750

RANK6

Lege"'CAMBRIDGE,ARLINGTON Bicycle Crash Locations 2002-2009 W A w>PC local RoodsPDO 108 Nu mOOr of Fatal Bicycle Crashes 0 / " 'V Al l Functional Classification Except Local RoaNumber of Injury Bicyc le Crashes 20 Nu mOOr of Noo nju ry Bicycle Crashes 8 o Top Bicyde Q-ash Cluster Tota l Bicyde Cra""", 28 ( = : ~ ) MUrlicip


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i i, 1,200

WESTFIELDWA ;w eEPDO 78Nu mOOr of Fatal Bicycle Cras he s 0Number of Injury Bicycle Crashes 15Nu mOOr of Noo nju ry Bicycle Crashes 3Tota l Bicyce C,a""", 18

RANK7


local Roods/ " 'V Al l Functional Classification Except Loc al Roao Top Bicyde Q-ash Cluster ( = : ~ ) MUflicip


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Top Bicycle Crash Cluster 2002-2009 I - - = :

'" 1,300RANK

8Lege"'NORTHAMPTON Bicycle Crash Locations 2002-2009WA ;w e local RoodsPDO 77

NumOOr of Fatal Bicycle Cras hes 0 / " 'V Al l Functional Classification Except Local RoaNumber of Injury Bicycle Crashes 15NumOOr of Noo nju y Bicycle Crashes 2 o Top Bicyde Q-ash ClusterTota l Bicyce C ,a""", 17 ( = : ~ ) MUflicip


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, ;00 1,200""RANK

9 Lege"'CAMBRIDGE Bicycle Crash Locations 2002-2009 WA w>PC local RoodsPDO 67

NumOOr of Fatal Bicycle Crashes 0 / " 'V Al l Functional Classification Except Loc al RoaNumber of Injury Bicyc le Crashe s 12 NumOOr of Noo nju y Bicycle Crashes 7 o Top Bicyde Q-ash Cluster Tota l Bicyce C ,a""", 19 ( = : ~ ) MUflicip


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, '" 1,275 IFeet1,700

CAMBRIDGEWA w>PCEPDO 62Nu mOOr of Fatal Bicycle Cras he s 0Number of Injury Bicyc le Cras he s 10Nu mOOr of Noo nju y Bicyc le Crashes 12

RANK10


local Roods/ " 'V Al l Functional Classification Except Loc al Roao Top Bicyde Q-ash Cluster

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2009 TOP CRASH LOCATIONS REPORT

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