Glossary of Data Variables for Fatal and accident causation ... - ERSO

More documents

Recommendations

Info

Manual For SafetyNet accident causation system (SNACS) km/h. From this you can say that the speed is more than adequate (given the speed limits), but the stretch of road with an unblocked view of oncoming traffic is too short. The latter part would indicate that the distance available for the overtake is too short, making Distance a suitable genotype. However, a part of normal driver education is to teach the driver not to overtake unless there is a sufficient stretch of road with a free view, and hill crests are particularly inadequate for overtaking. Given this, the phenotype that best describes the situation would be Timing: premature action. The overtaking should have been performed later on at a more appropriate stretch of road. In practice, this does not have to be a very complicated problem, since the linking table is constructed in such a way that phenotypes which are close also have quite similar linking from the genotypes. This means that the choice of phenotype does not have to be perfect, you can still get to the causes you need for the analysis. 6.5.4 Subjective judgement As the above reasoning shows, the SNACS methodology clearly calls for the investigator to reason from a “normative” standpoint, i.e. the investigator has to have an opinion on what would be normal or reasonable behaviour for a drivervehicle system in the situation at hand, because otherwise it will be difficult to classify what the deviation from the norm is. Also, the reasoning shows that the choice of phenotype will be partially based on the investigator’s judgement. In both these regards, a SNACS analysis will very clearly always be “subjective” in some sense of the word. This can be considered both an advantage and a disadvantage. People who consider it a disadvantage will say that for a SNACS analysis we can never be sure that two investigators will perform the analysis in the same way, since subjective judgment is involved. This would be quite devastating for the methodology, were it not for the fact that all methodologies which analyse causes suffer from the same problem. As David Hume elegantly showed in his treatise on human reason, causes typically cannot be observed; they have to be inferred by reasoning. This means subjective judgement will always be involved when analysing causes, no matter whether you are investigating injury causation mechanisms in passive safety or accident contributing factors in active safety. In light of this, we find it preferable to have a methodology which transparently shows that human judgement is involved, instead of burying that fact under protocols designed to look “objective”. As for the problem of different investigators performing different analysis, the best we can do is to clearly write down the reasons we have for making our choices and then discuss these reasons within the larger group of both your own accident investigation team and several different teams meeting for case review. As has been pointed out in the philosophy of science many times; over time a consensus within a larger group or community is as close to the truth as any methodology analysing causes will ever be. Page 128 of 215
Manual For SafetyNet accident causation system (SNACS) 6.5.5 Genotypes Genotypes categorise the reasons for why a certain dysfunctional behaviour occurs. As have been stated above, these reasons or causes generally cannot be observed; instead they have to be deduced from knowledge that the investigator brings with him/her into the analysis, i.e. the investigator has a preunderstanding of which the possible factors behind accidents are. The SNACS genotypes are sorted into different groups. On the top level, these groups correspond to the domain equivalents from the MTO-perspective (Man, Technology, Organisation) of the accident model that is described above. In SNACS, this terminology has been adjusted to the domain. Man is the road user and Technology is represented by the vehicle. Finally, the organisation part has been split into two subgroups; Infrastructure and Organisation. The genotype groups contain factors that contribute to the actual event at the sharp end, as well as factors that have shaped the circumstances around the event, i.e. uncorrected blunt end failures which have resulted in negative latent conditions. The factors that concern the sharp end are mostly related to the road user and the vehicle, whereas the factors that concern the blunt end are related to different organisations or parties responsible for shaping the context of the event. These shapers of context are road designers, vehicle manufacturers, and organisations or persons responsible for maintaining roads/vehicles and educating the drivers to an expected standard. The main groups and their subgroups are shown in the table below: Road user Vehicle Infrastructure Organisation Observation (B) Interpretation (C) Planning (D) Temporary person related functions (E) Permanent person related functions (F) Communication driver ↔ driver (J) Experience/training (L) Temporary HMI problems in driver environment (G) Permanent HMI problems in driver environment (H) Equipment (I) Maintenance - condition of vehicle (K) Vehicle design (O) Communication driver ↔ environment (J) Maintenance - condition of road (K) Design of traffic environment (N) Organisation (M) Figure 6: The main genotype groups for SNACS There are both general and specific genotypes. The difference between the two types is a degree of information. The specific genotypes describe more delimited states than the general ones. If the investigator has sufficient Page 129 of 215
Page 1 and 2:
Deliverable 5.5, Glossary of Data V
Page 3 and 4:
Subjective judgement 128 Genotypes
Page 5 and 6:
Executive Summary SafetyNet work pa
Page 7 and 8:
were evident. A full report of this
Page 9 and 10:
Database Glossary Information under
Page 11 and 12:
Database Glossary Information recor
Page 13 and 14:
Database Glossary Information 2. Da
Page 15 and 16:
Database Glossary Information compl
Page 17 and 18:
Database Glossary Information 3.1 O
Page 19 and 20:
Database Glossary Information 22. B
Page 21 and 22:
Database Glossary Information 43. N
Page 23 and 24:
Database Glossary Information 70. P
Page 25 and 26:
Page 25 of 215
Page 27 and 28:
Work package 5 Database Glossary 4.
Page 29 and 30:
Work package 5 Database Glossary Va
Page 31 and 32:
Page 33 and 34:
Page 35 and 36:
# Variable Value Notes V21 Vehicle
Page 37 and 38:
# Variable Value Notes V28 V29 V30
Page 39 and 40:
Work package 5 Database Glossary Ev
Page 41 and 42:
Work package 5 Database Glossary #
Page 43 and 44:
# Variable Value Notes R54 Speed li
Page 45 and 46:
# Variable Value Notes R57 Local ar
Page 47 and 48:
# Variable Value Notes R62 Pedestri
Page 49 and 50:
# Variable Value Notes R65 Problem
Page 51 and 52:
# Variable Value Notes R70 Weather
Page 53 and 54:
Page 55 and 56:
# Variable Value Notes P85 Seat dir
Page 57 and 58:
Work package 5 Database Glossary #
Page 59 and 60:
# Variable Value Notes P99 Police r
Page 61 and 62:
# Variable Value Notes P106 Partial
Page 63 and 64:
# Variable Value Notes 10 = Thrown
Page 65 and 66:
Work Package 5 Database Glossary -
Page 67 and 68:
Page 69 and 70:
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78: Work Package 5 Database Glossary -
Page 87 and 88: Accident Classification System (GDV
Page 111 and 112: Page 111 of 215
Page 113 and 114: Manual For SafetyNet accident causa
Page 127: Manual For SafetyNet accident causa
Page 153 and 154: Manual for SafetyNet accident causa
Page 179 and 180:
Manual for SafetyNet accident causa
Page 181 and 182:
Page 183 and 184:
Page 185 and 186:
Page 187 and 188:
Page 189 and 190:
Page 191 and 192:
Page 193 and 194:
Page 193 of 215
Page 195 and 196:
TABLE OF CONTENTS Database operatio
Page 197 and 198:
Database operation manual 7.1 Defin
Page 199 and 200:
7.3 General architecture of SafetyN
Page 201 and 202:
Database operation manual Log of ac
Page 203 and 204:
Database operation manual Figure 22
Page 205 and 206:
Page 207 and 208:
Database operation manual Data entr
Page 209 and 210:
Page 211 and 212:
7.9 Activation and assignment of ca
Page 213 and 214:
7.11 Server daemon Upload/Download
Page 215:
7.13 Safetynet accident causation s
show all

Glossary of Data Variables for Fatal and accident causation ... - ERSO

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?