Comparison of in-depth accident analysis data from three European countries using the Driving Reliability and Error Analysis Method

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Comparison of in-depth accident analysis data from three European countries using the Driving Reliability and Error Analysis Method Markus MATTSSON, Lars LEDEN Nordic Traffic Safety Academy meeting 2015 1

Topics Introduction DREAM method Case study: Single motorcycle crashes outside urban area, no intersection British, French and Finnish data Results Conclusions Advantages and limitations of DREAM Could DREAM be used routinely in the Nordic countries? Nordic Traffic Safety Academy meeting 2015 2

Methodology - DREAM An accident model Nordic Traffic Safety Academy meeting 2015 3

Nordic Traffic Safety Academy meeting 2015 4

Methodology - DREAM A classification scheme Phenotypes: the observable effects Genotypes: the factors that may have contributed to phenotypes Nordic Traffic Safety Academy meeting 2015 5

Linking rules Nordic Traffic Safety Academy meeting 2015 6

Methodology - DREAM A DREAM chart for each rider involved in a crash Genotype : Permanenet obstruction to view (K2) - trees Genotype : Inadequate road design (Q2) Genotype : Inadequate road geometry (L5) - a hill obstructed view to the curve Genotype : Late observation (B2) Genotype : Genotype : Genotype : Inadequate training (N4) Insufficient skills/knowledge (F6) Overestimation of skills (F5) Genotype : Misjudgement of situation (C2) Phenotype: Insufficient force (A5.2) - the rider failed to counter-steer strongly enough Genotype : Inadequate information design (Q1) Genotype : Inadequate transmission from road environment (M2) Nordic Traffic Safety Academy meeting 2015 7

Sometimes all you can say is Genotype : Phenotype: Sudden functional impairment (E6) No action (A 1.3) Nordic Traffic Safety Academy meeting 2015 8

2BESAFE project STATE OF THE ART MACRO ANALYSIS LEVEL National databases issues UK, Greece, Finland, Italy, France Scenario 1 Scenario 2 Scenario 3 Scenario MICRO ANALYSIS LEVEL In-depth databases UK, Finland, France Scenario 1 Scenario 2 Scenario 3 Scenario M 1 M 2 M 3 M 4 M 1 M 2 M 3 M 4 M 1, 2, 3, 4= Model 1, 2, 3, 4 Nordic Traffic Safety Academy meeting 2015 9

UK data collection sites: 25 crashes Nordic Traffic Safety Academy meeting 2015 10

Nordic Traffic Safety Academy meeting 2015 Transportforum, Sweden, 2011 11

French data: MAIDS & RIDER projects, 10 crashes Nordic Traffic Safety Academy meeting 2015 12

Nordic Traffic Safety Academy meeting 2015 13

Finnish data collection: 16 crashes Nordic Traffic Safety Academy meeting 2015 14

Nordic Traffic Safety Academy meeting 2015 15

Commonalities in the three countries Riding fast rather than safely, excitement seeking Overestimation of own skills Nordic Traffic Safety Academy meeting 2015 16

Country-specific factors Finland High engine power Riders compete / show off to one another France Riding in groups as a risk factor! Inadequate information design Poor condition of the roads UK Late observations by the riders Nordic Traffic Safety Academy meeting 2015 17

Differences in practice: Finnish DREAM chart Nordic Traffic Safety Academy meeting 2015 18

Differences in practice: French DREAM chart Nordic Traffic Safety Academy meeting 2015 19

Differences between countries Different ways of using the method Different input data (differences between the in-depth investigation methods) Question arises: which differences are real, which ones arise through different ways of using the method? Nordic Traffic Safety Academy meeting 2015 20

How to use the method? Personal opinion: using only DREAM genotype codes leaves essential information out Good to complement the charts with more descriptive information Nordic Traffic Safety Academy meeting 2015 21

Conclusions: advantages of DREAM Well-suited for identifying sharp-end factors DREAM is a visual method Easy to see things at a glance Good tool for turning incommensurable information commensurable Between countries Within countries Nordic Traffic Safety Academy meeting 2015 22

Conclusions: limitations of DREAM Blunt-end factors & injury risk factors receive less attention Aggregating results tedious & error-prone Automatize DREAM! DREAM is a visual method Add matrix representation: easier storage Factors not adapted to riders Differences in using the method Amenable by better training of users Nordic Traffic Safety Academy meeting 2015 23

In-depth investigations in the Nordic countries Every fatal road accident investigated in Finland, Sweden, Iceland Denmark, Norway? Similar methods, similar data Driver, vehicle, infrastructure Similar objective: Uncover causal factors, prevent similar accidents Nordic Traffic Safety Academy meeting 2015 24

Discussion Is a harmonization of the Nordic methodologies for in-depth studies beneficial? If yes should an appendix based on DREAM be included in the in-depth databases? How does an optimal reporting system look like? Should also severe injury accidents be investigated in-depth? Nordic Traffic Safety Academy meeting 2015 25

Thank you for your attention www.ltu.se/forskning publications www.2besafe.eu Nordic Traffic Safety Academy meeting 2015 26

Swedish method (Djupstudier av dödsolyckor) Routine since 1997 and is regulated in the government s instruction to the Transport administration Detailed investigation into each fatal road accident with the main objective to identify what caused the fatal injuries concerning Nordic Traffic Safety Academy meeting 2015 27

Swedish method What data is collected? Road data based on: Site inspection, Transport administration systems, Police, Rescue services etc. Vehicle data based on: Vehicle inspection, Police, car and vehicle register, manufactures description etc Road user based on: Police report, autopsy report, driving license register etc. Nordic Traffic Safety Academy meeting 2015 28

Methodology Accident data for 9 scenarios Number of in-depth accidents analysed per country Scenario PTW accident configuration Total The United Finland France Kingdom 1 Moped / Passenger car accident Inside urban area No intersection 0 13 2 15 2 Moped / Passenger car accident Inside urban area Intersection 3 36 10 49 3 Single motorcycle accident Outside urban area No intersection 16 10 25 51 4 Single motorcycle accident Inside urban area No intersection 4 26 16 46 5 Single motorcycle accident Inside urban area Intersection 0 19 17 36 6 Motorcycle / Passenger car accident Outside urban area No intersection 7 8 27 42 7 Motorcycle / Passenger car accident Inside urban area No intersection 0 31 10 41 8 Motorcycle / Passenger car accident Inside urban area Intersection 0 40 20 60 9 Motorcycle / Passenger car accident Outside urban area Intersection 3 18 30 51 TOTAL 33 201 157 391 A lack of in-depth accident data for several scenarios Nordic Traffic Safety Academy meeting 2015 29

Methodology - DREAM Driving Reliability and Error Analysis Method To classify and store information about factors contributing to accidents Warner, H., et al., (2008). Manual for DREAM 3.0, Driving Reliability and Error Analysis Method. Deliverable 5.6 of the european project SafetyNet DREAM is an adaptation of CREAM (Cognitive Reliability and Error Analysis Method) Hollnagel, E., (1998). Cognitive Reliability and Error Analysis Method: CREAM. Oxford, UK: Elsevier Science Ltd.. Nordic Traffic Safety Academy meeting 2015 30

Results from Phan et al (2010) Moped / passenger car, inside urban area, no intersection Inattention Late observation Reduced visibility Moped / passenger car, inside urban area, at intersection PTW with a right of way status: expect a certain behaviour from the passenger car driver PTW without a right of way status: late observation, inattention, priority error, reduced visibility Lack of riding experience for the moped users Nordic Traffic Safety Academy meeting 2015 31

Introduction 4 accident analysis models Description of the DriverVehicleEnvironment system Description of the evolution of the DVE system Determination of the Human Functional Failure (HFF) Driving Reliability and Error Analysis Method DREAM Nordic Traffic Safety Academy meeting 2015 32

France BEA Ministry of Transport BEAmer BEAD BEA-TT (2004) INRETS (1985) STRMTG (1979) CEESAR (1996) Ministry of Research Nordic Traffic Safety Academy meeting 2015 33

Finland Team 1 Ministry of Transport Road accident investigation delegation Team 21 Nordic Traffic Safety Academy meeting 2015 34

United Kingdom No routine in-depth investigation of road accidents VSRC (1982) Separately funded projects BASC TRL Nordic Traffic Safety Academy meeting 2015 35

Pros and cons of the different systems Country Pros Cons Finland France UK Comprehensive Breadth of information Cost-effective Depth of information (?): MA of INRETS focuses on specific accident types Depth of information VSRC: well-planned projects producing specific information BASC advanced knowledge of biomechanics Routine Shallowness of information Non-comprehensive Expensive (BEA-TT) Complicated administration Focused on the Paris area Non-comprehensive Narrowness of information Nordic Traffic Safety Academy meeting 2015 36