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SECTION V--DESCRIPTION OF STRATEGIES Information on Agencies or Organizations Currently Implementing This Strategy Many states have implemented electronic toll collection for all toll roads and have developed systems which will permit motorcycles to use these toll roads (e.g., http://www. bayareafastrak.org). Some states even provide special reduced tolls for all riders that use the electronic toll collection system (http://www.e-zpassny.com). Websites Department of Transportation--Intelligent Transportation Systems website http://www.its.dot.gov/ Intelligent Transportation Society of America website http:/ /www.itsa.org/ WP.29 World Forum for Harmonization of Vehicle Regulations--International Harmonized Research Activities--Intelligent Transport Systems Working Group http://www.unece.org/trans/main/wp29/wp29wgs/wp29gen/infpape_125.html National Agenda for Motorcycle Safety--position statement on deployment of ITS http://www.nhtsa.dot.gov/people/injury/pedbimot/motorcycle/00-NHT-212-motorcycle/ environmental59-60.html American Motorcyclist Association--comments on need to include motorcycles in the development and deployment of ITS http://www.ama-cycle.org Objective 11.1 H--Improve Motorcycle Safety Research, Data, and Analysis Strategy 11.1 H1--Develop and Implement Standardized Data Gathering and Reporting for Motorcycle Crashes (N/A) General Description Motorcycles are often overlooked during crash data gathering efforts. The frequency of motorcycle crashes is considerably lower than the frequency of automobile crashes; therefore, motorcycle crash data analysis is often limited to the evaluation of rider compliance with legislated safety measures (e.g., helmets, licensing). It is acknowledged that the collection, data coding, data entry and analysis of crash data requires the assistance of many different groups (e.g., law enforcement, data entry specialists, data analysts, etc.) and the scope of the crash data collection effort is often affected by budget considerations. However, many states are recognizing the benefits of using existing crash data as a tool for monitoring highway safety and for the development of safety countermeasures. Until another comprehensive motorcycle crash causation study is conducted, this data can serve as a useful tool to better understand motorcycle crash causation. Exhibit V-65 presents a number of sources that are available for obtaining information on motorcycle crashes. Numerous other resources for motorcycle data exist at the National Center for Statistical Analysis (NCSA--http://www.nhtsa.dot.gov/people/NCSA/) and V-109

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SECTION V--DESCRIPTION OF STRATEGIES EXHIBIT V-65 Sources of Motorcycle Crash Data Data Source Data Type Website Fatal Analysis Reporting National Fatality http://www-fars.nhtsa.dot.gov/ System (FARS) Data National Automotive Crash Data from http://www- Sampling System Selected Police nass.nhtsa.dot.gov/BIN/NASSCASELIST.EXE/SETFILTER (NASS)21 Crash Reports Web-based Injury National Fatal http://www.cdc.gov/ncipc/wisqars/ Statistics and Query and Non-fatal System (WISQARS) Injury Data the Governor's Highway Safety Association (GHSA--http://www.statehighwaysafety.org). Additional reports are presented in the Key References section. Most states rely on national fatality data which may or may not be indicative of the motor- cycle crash patterns in their particular state. Appendixes 1 and 2 illustrate the distribution of single- and multiple-vehicle fatal motorcycle crashes for each state. The data show that each state is unique and, in many cases, state trends in motorcycle crashes are different from the national trends. For this reason, each state must develop its own solution to reducing the frequency and severity of motorcycle fatalities. For an additional discussion of approaches to data analysis, see the Model Implementation Process in this guide, especially the discussion and examples provided under Step 1. This strategy involves the introduction to and the development of state-level data gathering and reporting of motorcycle crashes. Most states collect sufficient data to determine the number of motorcycle crashes within a state; however, standardized data gathering, data linkages and the addition of motorcycle-related elements to the state crash reporting form could significantly increase understanding of motorcycle crashes and their causes. This strategy strongly supports the efforts of NHTSA in the development of the Model Minimum Uniform Crash Criteria (MMUCC at: http://www.mmucc.us/default.aspx? home=yes). The MMUCC includes 113 data elements, many of which can be used independently for analysis and many of which can be linked to other data sources such as hospital records, license records, etc. Appendix 3 shows the results of an analysis of 51 different traffic crash data reports in terms of whether or not the crash data form included a selected group of motorcycle related variables. The overall results of this analysis are presented in Exhibit V-66. Once the data listed in the table are being regularly collected by states, and a consistent crash data reporting system has been established, data linkages can be initiated in order to further understand motorcycle crash causation. The CODES project is an illustration of how crash data records can be linked to hospital records in order to find detailed information regarding different types of motorcycle crashes and their associated medical outcome (http://www. 21 Motorcycles are include in this database only when they are involved in a collision with another vehicle and that vehicle qualifies as NASS case. V-110

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SECTION V--DESCRIPTION OF STRATEGIES EXHIBIT V-66 Analysis of Motorcycle Data Elements in 51 State Crash Reporting Forms Is the Data Element on the Crash Reporting Form? Percentage of States Data Element Yes No with This Data Element Motorcycle As a Vehicle Type 49 2 96.1 Motorcycle Make 50 1 98.0 Motorcycle Model 33 18 64.7 Vehicle Identification Number (VIN) 40 11 78.4 Motorcycle Engine Size (cc) 3 48 5.9 Motorcycle Class License or Motorcycle 39 12 76.5 Endorsement Motorcycle Helmet Worn at Time of Crash 44 7 86.3 Number of Vehicle Occupants 23 28 45.1 nhtsa.dot.gov/portal/site/nhtsa/menuitem.9fef9613e59b4dd24ec86e10dba046a0/). Other potential projects could include links with motorcycle licensing or rider training programs to better understand the benefits of such programs within a given jurisdiction. Information on Agencies or Organizations Currently Implementing This Strategy Several states have begun to implement data linkages using the CODES system and many states have made efforts to increase the number of motorcycle-related data elements. The state of Wisconsin has linked motorcycle crash information with hospital information in order to determine the impact of helmet use and alcohol consumption on motorcycle crashes in their state. A complete summary of the report may be found at the following link: http://www.chsra.wisc.edu/codes/motorcycle_crash_information.htm. The Maryland Motor Vehicle Division (MVD) has initiated a project to link motorcycle crash information with hospital, state licensing and rider training records to determine crash causation, rider behavior, licensing status and training experience. Further information can be obtained from the Maryland Motorcycle Safety Program at 1-800-638-8236 or e-mail at motorcyclesafety@mdot.state.md.us. The website for Maryland motorcycle safety programs is: http://mva.state.md.us/MVAProg/moto/default.htm. Websites FARS Web Encyclopedia (Query System)--http://www-fars.nhtsa.dot.gov/ NCSA State Data System--Crash Data Report: 19901999, Section 11: Motorcycles http://www-nrd.nhtsa.dot.gov/pdf/nrd-30/NCSA/Rpts/2002/809_301/12motorcycles.pdf NHTSA, Traffic Safety Facts 2003-Motorcycles, DOT HS 809 764 http://www-nrd.nhtsa.dot.gov/pdf/nrd-30/NCSA/PPT/PresMCFatsUpdate.pdf V-111

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SECTION V--DESCRIPTION OF STRATEGIES NHTSA, Safety Belt and Helmet Use in 2002-Overall Results, DOT HS 809 500 http://www-nrd.nhtsa.dot.gov/pdf/nrd-30/NCSA/Rpts/2002/809-500.pdf Bureau of Transportation Statistics--Motorcycle Rider Safety Data http://www.bts.gov/publications/national_transportation_statistics/2003/html/ table_02_22.html NHTSA MMUCC website http://www.nhtsa.dot.gov/people/perform/trafrecords/pages/mmucc/mmucc.htm State Traffic Data Forms website http://www.nhtsa.dot.gov/people/perform/trafrecords/crash2003/Default.htm CODES website http://www.nhtsa.dot.gov/portal/site/nhtsa/menuitem.9fef9613e59b4dd24ec86e10dba046a0/ State of New Jersey--Crash Data Records http://www.state.nj.us/transportation/refdata/accident/rawdata01-02.shtm Please see the Key References section for other agencies that have implemented this strategy. Strategy 11.1 H2--Include Motorcycle Attributes in Vehicle Exposure Data Collection Programs (N/A) General Description The identification of risk factors in traffic crashes requires the use of exposure data. Ideally this data source represents the population-at-risk, i.e., the population of motor- cycle riders that are exposed to the same risks as those within the accident population. This allows for the analysis of over- and under-representation and the identification of specific risk factors. This exposure data is used to compute vehicle miles traveled (VMT) which is then compared with the accident data found in the Fatality Analysis Reporting System (FARS) and the National Automotive Sampling System (NASS) to identify risk factors in traffic crashes. Exhibit V-67 illustrates motorcycle trends--with respect to sales, registrations, fatalities, and vehicle miles traveled--from 1982 to 2002. EXHIBIT V-67 Trends in Motorcycling: New Unit Sales, Registrations, Fatalities, Vehicle Miles Traveled (VMT) and Fatalities per VMT Source: Jim Ouellet, Head Protection Research Laboratory V-112

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SECTION V--DESCRIPTION OF STRATEGIES Unfortunately, the methods for computing VMT data for motorcycles vary from state to state, so it is difficult to make comparisons, though FHWA is currently reassessing how to improve data and reporting. The most commonly used exposure database is the Nationwide Personal Transportation Survey (NPTS) or National Household Travel Survey (NHTS), which is conducted every 5 or 6 years. The 2001 data comparing motorcycles and cars are presented in Exhibits V-68 and V-69. Detailed tables, with comparisons for other types of vehicles, may be found in Appendix 5. The data presented below clearly show that the travel patterns of motorcycle riders, with respect to rider age, are quite different from other road users, both in the number of annual miles driven as well as the average trip duration. This strongly suggests that special attention needs to be given to the collection of accurate motorcycle rider exposure data. EXHIBIT V-68 Annual Miles Driven versus Age for Males in 2001 Source: NHTSA, 2001 Motorcycle riders 3,000 2,500 Annual Motorcycle MVMT 2,000 1,500 1,000 500 0 Under 20 21 to 30 31 to 40 41 to 50 51 to 60 Over 60 Age Group Car drivers & passengers 180,000 160,000 140,000 Annual Car MVMT 120,000 100,000 80,000 60,000 40,000 20,000 0 Under 20 21 to 30 31 to 40 41 to 50 51 to 60 Over 60 Age Group V-113

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SECTION V--DESCRIPTION OF STRATEGIES EXHIBIT V-69 Average Trip Duration versus Age for Males in 2001 Source: NHTSA, 2001 Motorcycle riders Car drivers & passengers 80 70 60 Trip Time, min 50 40 30 20 10 0 5 20 25 30 35 40 45 50 55 60 65 70 75 79 84 l* r8 Al to to to to to to to to to to to to to to ve 16 21 26 31 36 41 46 51 56 61 66 71 76 80 O Age Group In 1996, the National Roadside Survey was conducted between 10:00 p.m. and 3:00 a.m. on Friday and Saturday nights in order to obtain information about drinking and driving as well as vehicle type, seat belt use and number of occupants. The survey was done in all 48 contiguous states; however, due to logistical problems, no motorcycle riders were surveyed as part of the study. Unfortunately, due to the relatively small number of motorcycles and the cyclical nature of motorcycle riding, it is very difficult to obtain reliable motorcycle exposure data. Less than 2.5 percent of the people surveyed in the 2001 National Household Travel Survey (NHTS) owned a motorcycle. Due to their small size and light weight (relative to other vehicles), motorcycles are also difficult to detect with some roadway data collection devices (e.g., roadway tubes, vehicle length measurement devices, lane monitors, etc.). Many riders own motorcycles and do not ride them on a regular basis; therefore, the use of vehicle registration data and the use of telephonic surveys does not adequately reflect the over-the-road and at-risk population of motorcycle riders. In many cases, these methods tend to over-estimate the actual riding population because, for many people, motorcycle riding is not a daily activity. Previous studies which have tried to draw conclusions without comparison to exposure data have been strongly criticized (Kraus et al., 1988). This strategy supports the enhancement of existing over-the-road user surveys to include motorcycles. Information on Agencies or Organizations Currently Implementing This Strategy NHTSA has explored methods to collect motorcycle rider exposure data. A workshop was held in June 2003 to discuss potential methodologies for motorcycle rider exposure data collection and the summary report of that workshop is available. V-114

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SECTION V--DESCRIPTION OF STRATEGIES Department of Transportation Solicitation DTNH22-01-R-05162, Methodology for Determining Motorcycle Operator Crash Risk and Impairment Department of Transportation Solicitation DTNH22-02-R-05112, Characteristics of Motorcycle Operators Study Websites Federal Highway Administration--National Household Travel Survey http://www.fhwa.dot.gov/policy/ohpi/nhts/index.cfm NTSB Recommendation to improve VMT data http://safety.fhwa.dot.gov/mac/final010808.htm FHWA Motorcycle Traffic Symposium (and ongoing work) http://www.fhwa.dot.gov/motorcycles/2007symposium.cfm Strategy 11.1 H3--Develop a Set of Analysis Tools for Motorcycle Crashes (N/A) General Description In order to fully understand motorcycle crashes and crash causation, existing data must be analyzed and used to develop appropriate countermeasures. Many highway agencies currently have, or at least have access to, sufficient data to identify motorcycle crash patterns and potential countermeasures. Unfortunately, evaluation of existing data often requires the use of advanced statistical software packages which may not be available to staff and require a high level of statistical knowledge to utilize. This strategy builds upon the efforts of Strategy 11.1 A1 and emphasizes the development of common software tools that can be used to evaluate the data collected using the Model Minimum Uniform Crash Criteria (MMUCC). These tools should be intuitive and easy to use and they should be adaptable for different types of data. This strategy is intended to allow highway agencies to use their own crash data, which would be compared to an exposure population, to identify risk factors for motorcycle crashes in their region. Additional analysis could be performed to compare the user data to other larger data sources such as FARS. The following is a partial list of significant motor- cycle crash variables which are currently available in the FARS data and are typically found within state or regional crash data: Time of accident Type of roadway Day of accident Age of rider Alcohol involvement Motorcycle engine size It is expected that the amount of information available at the state level and at the national level will continue to grow as more and more states begin to adopt the MMUCC guidelines and crash contributing factors are reported with greater frequency. V-115

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SECTION V--DESCRIPTION OF STRATEGIES Information on Agencies or Organizations Currently Implementing This Strategy In an effort to consolidate and communicate between different agencies and groups within the state of Iowa, the Department of Transportation Office of Traffic Safety created a website with a set of crash analysis tools that can be used by anyone interested in better under- standing Iowa crash data. This website and the associated tools can be found at the following link: http://www.dot.state.ia.us/crashanalysis/. The University of Alabama has developed the CARE system which allows users to analyze crash and other data. In addition to crash databases and analysis tools, the website for CARE (http://care.cs.ua.edu/) tells about other data collection and analysis initiatives being carried out. The site allows for online analysis of highway crash data from several states. NHTSA has currently developed software tools that will allow users to estimate the economic cost of crashes in their area. This software tool could easily be used to estimate the economic cost of motorcycle crashes within a given jurisdiction. The PC/Window-based software is available free of charge from the following link: http://www.nhtsa.dot.gov/people/ crash/MVS/ Using Minnesota crash data, the Minnesota Motorcycle Safety Center (MMSC) has determined that the majority of motorcycle fatalities and injuries in Minnesota involve collisions with other vehicles. A complete analysis of the crash data records for the state has identified that alcohol and the lack of training and personal protective equipment are the most frequently reported contributing factors. Given this information and awareness, specific public service ad campaigns have been developed to address these issues. http:// www.motorcyclesafety.state.mn.us/pages/ad2.asp http://www.dps.state.mn.us/ots/ crashdata/2003CFacts/CF03-4Motorcycle.pdf Using Utah crash data, researchers attempted to identify the factors associated with animal- vehicle collisions. It was determined that 94 percent of all motorcycle/animal crashes involved an injury to the motorcycle rider. Using the crash data, sections of roadway that reported a high frequency of animal-to-vehicle collisions were identified and specific countermeasures were introduced in an effort to reduce this type of single-vehicle motorcycle crash. The report can be found at the following link: http://www.dot.state.ut.us/main/uconowner. gf?n=200312091625312. Websites CODES documents available from NHTSA regarding statistical analysis of crash data http://www.nhtsa.dot.gov/portal/site/nhtsa/menuitem.9fef9613e59b4dd24ec86e10 dba046a0/ National Center for Statistical Analysis http://www.nhtsa.dot.gov/people/NCSA/ North Carolina crash data query website http://www.hsrc.unc.edu/crash V-116