The Motorcycle In-Depth Study Jacques Compagne Secretary General of ACEM Vehicle population Vehicle population Time to decide What is commonly available In 99 ACEM confirmed that: Improvements in MC safety are essential for: riders the future of motorcycling the positive contribution that motorcycling brings to society However, the information available was not enough to develop an integrated safety policy and action plan National accident statistics based on police reports cover: The basic parameters of an accident: where, when, what, some how very little/no why The limitations of such data in Europe are because there is: Very little in -depth reconstruction of the accident, Not enough data (variables) on human, vehicle and roadside environment factors, No harmonised method for collecting the data.
The decision HOW? The OECD methodology () To provide the scientific basis for the discussion of MC accidents in Europe: ACEM organised the Motorcycle Accident In- Depth Study ; Created a Consortium of partners, namely: DG TREN of the European Commission, who co-financed the project. Other partners: BMF, CEA, CIECA, FEMA, FIM. The OECD Common Methodology was developed in 99-000 by experts from Europe, Japan and USA The scope of the common methodology involves: multi-disciplinary teams; recommended sample sizes: 00 accidents per area, per year; on-scene, at the time of the accident; in-depth data (000+ variables); includes both accident and injury causation factors; i.e. the interrelationship of human, vehicle and environmental variables; includes exposure data Whoand where? Main figures For data collection: - France: CEESAR (Centre Européen d Etudesde Sécurité et d Analyse des Risques) - Germany: MUH (Medical University of Hanover) - Italy: The University of Pavia - Netherlands: TNO (NederlandsOrganization for applied scientific research) - Spain: REGES (Investigación y reconstrucción de accidentes de tráfico) For statistical analysis: 9 notified cases 9 accident cases 9 exposure cases 000 variables per accident - The University of Pavia (Italy) Vehicle population MAIDS confirmed that: Human factors are the primary accident contributing factor in % of all cases Primary accident contributing factor Human PTW rider. Human OV driver 0. Vehicle 0. Environmental. Other failure. 9 00.0 OV drivers are largely responsible for accident causation They represent 0% of all MAIDS cases and % of the multi-vehicle accidents
Perception failure Comprehension failure Decision failure Reaction failure Perception failure Comprehension failure Decision failure Reaction failure The most frequent primary accident contributing factor: perception failure on the part of the OV driver It represents % of all MAIDS cases % of all the OV drivers failures Number of cases 00 0 00 0 00 0 00 0 00 0 0 0 0 PTWrider OV driver Vehicle operator Perceptionfailure Comprehensionfailure Decision failure Reactionfailure Otherfailure The next most frequent primary accident contributing factor: decision failure from the PTW rider ( % of all the cases) 9 MAIDS identified secondary contributing factors: On the part of PTW rider in % of the cases On the part of the OV driver in 9% of the cases Other accident contributing factors (Note: Multiple responses could be made for each case) PTW rider 900. OV driver 9. PTW technical failure. OV technical failure 0 0. Environmental cause 00. Other. contributing factor. 09 00.0 The most relevant secondary contributing factors are: Traffic - scan errors in: % of cases for PTW riders % of cases for OV drivers Faulty traffic strategies in: % of cases for PTW riders % of cases for OV drivers Loss of concentration reduces the reaction time of the vehicle operator and thus reduces the amount of time available for collision avoidance Attention failure was present and contributed to accident causation in % of cases (PTW riders) and % (OV drivers)
The neglect of the visual obstruction contributed to accident causation in % of cases (PTW riders) and % (OV drivers) In % of cases (PTW) and % (OV), speed difference contributes Speed unusual but no contribution Speed compared to surrounding traffic (PTW) L vehicles L vehicles of L of L. 9.. Speed difference contributed to accident No unusual speed or no other traffic (not applicable). 09 0..0 0.. 0. 0. 0 0.0 0. 9 00.0 00.0 9 00.0 Speed compared to surrounding traffic (OV) Speed unusual but no contribution. Speed difference contributed to accident. No unusual speed or no other traffic (not applicable).. 00.0 Selected results human factors Vehicle population % of riders had no licence even though one was required % were found to have a licence, but for vehicles other than a PTW There were 0 accident cases in which a licence was not required to operate the vehicle involved in the accident. PTW licence qualification Accident data Exposure data.. None, but licence was required Learner's permit only 0. 0. PTW licence 0.0 9. Only licence for OVs other than PTW.. Not required 0. 9.. 0. 9 00.0 9 00.0 The data clearly indicates that riders without licences are over-represented in the accident population Selected results -human factors Selected results -human factors Primary contributing factor Other Vehicle licence ov driver other failure ov driver reaction failure ov driver decision failure ov driver comprehensionfailure ov driver perception failure PTW rider other failure PTW rider dicision failure PTW rider perception failure other 0 0 0 00 0 00 0 00 Number of cases only car licence PTW licence Drivers who only have a car licence are likely to commit a perception failure OV drivers who also have a PTW licence are much less likely to commit a perception failure PTW training by PTW legal category % of L vehicle riders have no type of PTW training % of L vehicle riders have some type of pre-license training None Pre-licence training Additional training Other L vehicles 9 0.0 9 of L.9..0 0.0. 00.0 L vehicles Frequenc y 0 Percen t of L... 0..9 00.0 9 9 9 9 Percen t 0... 0. 0. 00.0
Selected results -human factors Selected results -human factors PTW collision avoidance manoeuvre by PTW training % of the riders without any type of training failed to attempt a collision avoidance manoeuvre % of the riders who had compulsory training also failed to attempt a collision avoidance manoeuvre age 00% 0% 0% 0% 0% 0% 9 None Kind of training Compulsorytraining Experience on any PTW Riders who have less than months experience on any PTW are more likely to be in an accident when compared to the riding population (% of accident cases and % of exposure cases) Number of cases 00 0 00 0 00 0 00 0 00 0 0 Accidents Exposuredata 9 9 9 up to to to to 0 to 9 9 or more Months Riders with a great experience on PTWs(i.e. over 9 months) are under represented ( % of accident cases and % of exposure cases) 9 none Braking Swerve BrakingangSwerve other Selected results human factors Selected results -human factors Neck ( excluding spine).%(n=) Spine.0% (n=) Upper extremities.% (n=0) Pelvis.% (n=) Whole body.% (n=9) Head.% (n=) Thorax.% (n=) Abdomen.% (n=0) Lower extremities.% (n=0) Injury Distribution Lower extremities made up,% of all injuries Upper extremities counted for,% The head for,% Alcohol and Drug Alcohol use by the PTW riders represents % of all cases cases of alcohol use by the OV driver was reported (%) Alcohol/ drug use by PTW rider Accident data Exposure data None 9. 90 9. Alcohol.9. Drug 0. 0. Alcohol+drug 0. 0.. 0. 9 00.0 9 00.0 Note: drug use is defined as the use of illegal, non-prescription drugs (e.g., cocaine). Alcohol/drug use by the OV driver None 9. Alcohol. Drug 0.. 00.0 Accident causation - vehicle Vehicle factors as primary accident contributing factor account for only 0.% of all cases Primary accident contributing factor Human PTW rider. Human OV driver 0. Vehicle 0. Environmental. Other failure. 9 00.0
Accident causation - vehicle Accident causation - vehicle 9% of the accidents PTW have no failure A total of cases of PTW failure contributed to the accident PTW vehicle failure, accident cause related problem Yes. No 9.0 0.9 9 00.0 % of all PTW vehicle failures were related to the tyre or wheel and most often this was reported as a tire blow out or a tyre failure related to brakes problems ( %) Specific cause of PTW vehicle failure, accident cause related problem Tyre or wheel problem. Brake problem. Steering problem 0. Suspension problem 0. Not applicable, no PTW vehicle failure 9.0 0.9 9 00.0 Cumulative percentage distribution of the PTW travelling speed The median travelling speed was found to be 9 km/h The range of travelling speeds was between 0 km/h and km/h age (%) 00,0% 90,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0%,0% PTW travelling speed (all accidents) 0 0 00 0 00 0 Speed (km/h) PTW Impact speed The data shows that % of PTW crashes occurred at speeds below 0 km/h % of impacts were at speeds of 00 km/h or higher PTW impact speed (all accidents) 0 km/h. 0 km/h. 0 km/h. 0 km/h 9. 0 km/h 0. 0 km/h.9 0 km/h 0. 0 km/h.9 0 km/h 0. 90 km/h. 00 km/h or higher 0. 0. 9 00.0 Pre-crash Motion PTW pre-crash motion prior to the precipitating event Travelling in a straight line in % of accidents Negotiating a bend at constant speed (%, of all cases) Performing a passing manoeuvre on the left (%, of all cases) OV pre-crash motion prior to the precipitating event Travelling in a straight line in % of accidents Stopped in traffic at 0 speed (%) Turning left (0%, of all cases)
Pre-crash Motion PTW pre-crash motion after the precipitating event Travelling in a straight line in % of accidents OV pre-crash motion after the precipitating event Travelling in a straight line in % of accidents Turning left % Line of sight to the OV as seen from the PTW rider at the time of the precipitating event.%.% 0.9%.% 0 9 0.% 9 9.%.% 0.% 0.%.% Number of cases % of all cases 0.% 0.%.% 90% of OVs in front of the PTW rider 0.% Line of sight to the PTW as seen by the OV driver.% 9.% 0 9.% 0.0% 0 0.% 0.9%.% Number of cases % of allcases.% Collision avoidance In almost one-third of all cases, the PTW rider did not attempt to perform any collision avoidance manoeuvre Collision avoidance performed by PTW rider No collision avoidance attempted Braking Swerve.9 9.. 9.%.% 9.% 0 0.0 %.0%.9% The majority of PTWs appears in front of the OV Accelerating Use of horn, flashing headlamp Drag feet, jump from PTW Other 9.. 0...9 00.0 Loss of control mode Loss of control mode Loss of control No loss of control Capsize, or fall over Braking slide-out, low side 9 9.. 0. Loss of control Single accidents No loss of control Capsize, or fall over Braking slide-out, low side. 0.. No loss of control reported in % of all cases loss of control was mostly related to braking % of all cases (% of all cases involving loss of control). Braking slide-out, high side Cornering slide out, low side Cornering slide out, high side Ran wide on turn, ran off road, under cornering Lost wheelie Low speed wobble High speed wobble Weave, no pitch Pitch weave, low speed Pitch weave, high speed cornering End-over, endo, reverse wheelie Continuation, no control actions Other.9.9 0..9 0. 0. 0. 0. 0. 0. 0. 0.. 0.9 Running off the roadway was the most frequently reported loss of control mode: cases, % Braking slide-out, high side Cornering slide out, low side Cornering slide out, high side Ran wide on turn, ran off road, under cornering Lost wheelie Low speed wobble High speed wobble Weave, no pitch Pitch weave, low speed Pitch weave, high speed cornering End-over, endo, reverse wheelie Continuation, no control actions Other..0.. 0... 0.. 0..... 9 00.0 00.0
Reason for failed collision avoidance action In % of the PTW cases and in. of the OV cases, there was failed collision avoidance due to inadequate time available to complete the collision avoidance action Reason for failed collision avoidance Decision failure, wrong choice of evasive action Reaction failure, poor execution of evasive action Inadequate time available to complete avoidance action Loss of control in attempting collision avoidance Other Not applicable, no OV or no evasive action taken PTW rider Frequenc y 9 9 9 9....0 0. 9.. 00.0 OV driver Frequenc y 9... 0. 0. 0.. 00.0 Roadway type Pre-crash path The majority of the accidents occurred on minor arterial roadways (%) Roadway type 0% of the roadway alignment was straight ( of 9 cases) Motorway 9. Major arterial 9 0.9 Minor arterial. Non-arterial, sub-arterial. Parking lot, parking area 0. Driveway 0. Round about or traffic circle 0. Overpass 0. Underpass 0. Dedicated bicycle or moped path separated from traffic roadway. Roadway alignment (PTW) Straight 0. Curve/corner 9. Other/unknown 0. 9 00.0 Dedicated bicycle or moped path not separated from traffic roadway 0. Weather Roadway contamination The weather conditions at the time of the accident were most frequently dry (90%) Rain at the time of the accident was noted in % of all cases Weather conditions at time of accident No precipitation 9.9 Rain.9 Ice rain/snow 0. Other 0.. 9 00.0 Dry and free of contamination in % of all accidents Wet in % of all collected cases Ice, snow and mud were in cases Gravel or sand was reported in cases,.% of all cases Oil in cases Roadway contamination Dry 0. Wet.9 Snow 0. Mud 0. Ice 0. Gravel sand. Oil 0. Other.9 0. 9 00.0
Road surface Traffic control The road surface was considered to be optimal in % of all cases In % of the cases, road surface was not optimal Roadway condition Asphalt, optimal condition.0 Asphalt, not optimal condition. Other than asphalt, optimal condition 0. Other than asphalt, non optimal condition. 0. PTW riders violated traffic controls in % of cases in which a traffic control was present Traffic control violated by PTW rider No Yes if traffic control was present or if traffic control was violated Not applicable, no traffic control present 9 9..9.. 00.0 OV drivers violated traffic controls in % of cases where a traffic control was present Traffic controls violated by OV operator 9 00.0 No 99. Yes 0.0 0. Not applicable, not traffic control present 9. 00.0 Accident causation - environmental factors represent a significant part of the primary contributing factors with near % of all cases Primary accident contributing factor Human PTW rider. Human OV driver 0. Vehicle 0. Environmental. Other failure. 9 00.0 Accident causation - environmental factors Accident causation Roadway design MAIDS identified secondary contributing factors: On the part of PTW rider in % of the cases On the part of the OV driver in 9% of the cases From the road environment in % of the cases Other accident contributing factors (Note: Multiple responses could be made for each case) PTW rider 900. OV driver 9. PTW technical failure. OV technical failure 0 0. Environmental cause 00. Other. Un known contributing factor. 09 00.0 Roadway design defects were present in cases In cases, it was the precipitating event of the accident In cases it was the primary contributing factor of the accident In the 9 remaining cases, the roadway design defect was a contributing factor to the accident. Roadway design defect (PTW) Roadway design defect present but not a contributing factor.9 Roadway design defect was the precipitating event 0. Roadway design defect was the primary contributing factor 0. Roadway design defect was a contributing factor 9. Not applicable, no OV, or no roadway design defect present 9. 9 00.0 9
Accident causation Traffic hazard Accident causation Roadway maintenance A total of cases were reported to involve a traffic hazard As the precipitating event for 0 cases As primary contributing factor cases Or as secondary contributing factor cases Traffic hazard, including construction and maintenance operations (PTW) Temporary obstruction present but not a contributing factor. Temporary obstruction was the precipitating event 0. Temporary obstruction was the primary contributing factor 0. Temporary obstruction was a contributing factor.0 Not applicable, no OV, or no temporary traffic obstruction 9. 0. 9 00.0 reported cases of roadway maintenance defects Maintenance defects were the precipitating event in cases There were the primary contributing factor in 9 cases (% of the cases) And secondary contributing factor cases Roadway maintenance defect (PTW) Roadway maintenance defect present but not a contributing factor. Roadway maintenance defect was the precipitating event 0.9 Roadway maintenance defect was the primary contributing factor 9. Roadway maintenance defect was a contributing factor 0. Not applicable, no OV, or no roadway maintenance defect.0 0. 9 00.0 Accident causation Weather Selected results - environmental factors The data presented indicates that weather made no contribution to accident causation in 9.% of MAIDS cases In cases the weather was reported as being a primary contributing factor for the PTW (%) The weather was also reported to contribute to accident causation in cases (%) Weather-related problem (PTW) Weather made no contribution to accident 9. Weather related problem was the precipitating event 0. Weather related problem was the primary contributing factor.0 Weather related problem was a contributing factor. 9 00.0 Crash barriers 0 PTW rider injuries were associated with barrier contact (.%) (,%) were minor or moderate (0%) were to the head and were severe or higher Number of cases Minor Moderate Serious Severe Critical Maximum MAIS (%) were to the lower extremities and the majority of these injuries were minor and moderate There were serious lower extremity injuries due to roadside barrier contact 0 0 0 Head Neck Upper extremities Abdomen Pelvis Spine Lower extremities Wholebody Thank you 0