Keith Vodden Dr. Douglas Smith - Transports Canada

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APPENDIX A: DETAIL ON CALCULATIONS OF THE ONTARIO MODEL This chapter describes the Ontario model. A. RAW DATA Raw data for the Ontario model comes from ORSAR. Exhibit A-1 presents the data for 2004 data. Exhibit A-1 Raw Data for Ontario Model—Number of Collisions, Fatalities, Injuries and Damaged Vehicles (2004) Collision Severity Fatal Injury PDO TOTAL Collisions 718 49,948 180,882 231,548 Fatalities 799 799 Injuries: Major 245 3,320 3,565 Minor 330 29,589 29,919 Minimal 189 39,338 39,527 Vehicles damaged: Demolished 678 10,023 5,883 16,584 Severe 188 21,021 32,110 53,319 Moderate 147 24,698 99,313 124,158 Light 125 24,486 137,512 162,123 None 45 8,572 19,161 27,778 Unknown 58 5,420 37,511 42,989 This raw data is entered into spreadsheet O1 and forms the core data used in all subsequent adjustments. In future applications, users will enter ORSAR data for other years to replace the 2004 data. Adjustment factors (developed based on the 2004 data) are applied to other year’s data automatically. These adjustments are discussed in the next section. Note that these data do not include collisions that are not reported to police. A motor vehicle collision does not need to be reported if: • No personal injury or fatality occurs. • Damage to vehicles is less than $1,000. TNS Canadian Facts, Social and Policy Research 113
Analysis and Estimation of the Social Cost of Motor Vehicle Collisions in Ontario • No other public or private property is damaged. • No criminal activity (drinking and driving, stolen vehicle, driving under suspension) is suspected. The first condition restricts any under-reporting to PDO collisions. As a result, data in ORSAR on the number of PDO collisions and on vehicles involved in PDO collisions is expected to be under-reported in the ORSAR data. We do not have data that would allow us to estimate the number of PDOs not reported to police and subsequently not included in the ORSAR data. Such unreported cases would have a minimal impact on the social cost estimates as they do not by definition involve human consequences (fatalities or injuries), or use of resources such as hospital/health care, ambulance, police, courts, and most likely fire departments. (In Section D. 8 we present data from the Insurance Bureau of <strong>Canada</strong> which may indicate the number of vehicles and cost of vehicle damage in unreported collisions.) B. ADJUSTMENTS TO THE RAW DATA A number of adjustments are needed to reflect cases of under-reporting and misreporting in the 2004 data. This section presents information on how the model moves from raw data found in ORSAR to adjusted data based on other information. These adjustment factors would be applied automatically if raw data for other years were entered in place of the 2004 ORSAR data. (If updated information used to produce the adjustment factors becomes available the analyst could also replace the information and thereby generate update adjustment factors.) Diagrams are used to illustrate the adjustments built into the model. 1. Unknown damage to vehicles in collision Police reports identify the extent of damage to vehicles involved in collisions. However, for 10% of vehicles involved in the collisions reported in 2004, damage is listed as unknown. By collision severity the percentage of unknown among total vehicles damaged is 5% for fatal, 6% for injury and 11% for PDOs. The higher proportion of vehicles with unknown damage in PDOs is likely due to self-reporting. We have no information that would indicate whether vehicles with unknown damage should be assigned in higher or lower proportion to more sever damage severity categories. As a result, vehicles with unknown damage are assigned based on the known distribution of vehicles by damage severity. The example illustrated below shows the allocation of 10 vehicles with unknown damage to other damage categories based on the proportion of vehicles across other 114 TNS Canadian Facts, Social and Policy Research
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TP 14800F Analysis and Estimation o
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APPENDIX A: DETAIL ON CALCULATIONS
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• Large truck. Collisions involvi
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ABBREVIATIONS CAC Criteria Air Cont
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Analysis and Estimation of the Soci
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III ONTARIO MODEL This chapter desc
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Ontario Model redistribution. Simil
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Ontario Model • Pedestrian Injure
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Ontario Model Based on this analysi
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Ontario Model Step 3 Allocate addit
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Ontario Model damaged based on this
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Ontario Model 1. Number of total an
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Ontario Model 2.99; specialist—1.
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Ontario Model 5. Tow trucks Tow tru
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Ontario Model Exhibit III-5 Core WT
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Ontario Model We combine this value
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Ontario Model 6. Ambulance The Onta
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Ontario Model individuals who self-
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Ontario Model threatening injury, p
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Ontario Model d) Additional Polluti
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Ontario Model VARIABLE DATA LOST TI
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Ontario Model We have no data to gu
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V ONTARIO SUB-MODELS AND THEIR SOCI
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Ontario Sub-Models and Their Social
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Ontario Sub-Models and Their Social
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Appendix B—Making Changes to the
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Appendix C The Value of Human Conse
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APPENDIX D: VALUE OF HUMAN CONSEQUE
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Appendix D—Value of Human Consequ
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APPENDIX E: REFERENCES Audrey, J. a
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Keith Vodden Dr. Douglas Smith - Transports Canada

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