CMC Roadmap. Motorcycles on track to connectivity & Evaluation of the potential of C-ITS for motorcycles on the basis of real accidents

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1 CMC Roadmap Motorcycles on track to connectivity & Evaluation of the potential of C-ITS for motorcycles on the basis of real accidents Christian Massong, BMW Motorrad, Germany Marcus Petzold, VUFO GmbH, Germany 12th International Motorcycle Conference Cologne, Germany 1 October 2018 Page 1

2 Agenda Brief introduction of CMC Motivation: Enhancement of motorcycle safety Working Group: Unification and Interoperability Motorcycle accidents statistics Analyses and evaluation Potential and benefit of C-ITS Exemplified by the application Left Turn Assist CMC Roadmap Page 2

3 Motivation: Enhancement of motorcycle safety Trend of car and motorcycle fatalities 25,000 USA Europe Japan 35,000 3,500 20,000 30,000 3,000 25,000 2,500 15,000 20,000 2,000 10,000 15,000 1,500 10,000 1,000 5,000 5, Source: International Traffic Safety Data and Analysis Group (IRTAD) Page 3

4 CMC s mission: motorcycle safety Make motorcycle riding safer by vehicle-to-vehicle communication Avoid accidents, e.g. where motorcycles are being overlooked We jointly promote, research and develop connectivity for motorcycles netmag ETSI Page 4

5 Introduction of CMC and C-ITS CMC Working Group Unification & Interoperability 6 Task Groups: CMC C-ITS Roadmap Application- / Use Case Description Rider Motivation, Behaviour and Modelling Profiling HMI Guideline for C-ITS on PTW Accidentology CAR2CAR Illustrator Page 5

6 V2V communication example: Animation of LTA Page 6

7 Percentage (related to the year 2000) Fatally injured road users in Germany 100% 90% Source: Statistisches Bundesamt, Wiesbaden, Fachserie 8 / Reihe 7 Year 2000 = 100% 80% 70% 60% 50% 40% 30% Car occupants Pedestrians Cyclists Truck occupants Motorcycle & Moped rider Year 2017 Page 7

8 German accident data GIDAS Investigation area Information Technical Database Dresden Germany Source: Google Maps & GIDAS Hannover Germany Medical Reconstruction traffic accidents with personal damage per year - since Ø single information per accident Page 8

9 Method: Accident scenarios of motorcycles 1. Creation of a dataset 2. Weighting towards the German traffic accident statistics of Scenario classification Driving Accidents: Collision Accidents: Crossing traffic Longitudinal traffic Lane change Left turn Straight Left curve Right curve U-turn Animals Technical defect Others / Unknown Page 9

10 Accident scenarios by type of accident 5,612 5,151 n = accidents 3,538 3,168 2,816 Collision accidents Driving accidents 2,018 1,950 1, ,274 Page 10

11 Top 10 motorcycle accident causation Collision 6,000 accidents 17.9% 5,000 4, % 3,000 2, % n = accidents Accident Causer = Motorcycle Accident Causer = Other 6.2% 5.2% 4.6% 4.4% Driving accidents 11.1 % 10.0% 7.2% 1,000 0 Page 11

12 Top 10 motorcycle accident causation Collision 6,000 accidents 17.9% 5,000 4, % 3,000 2, % n = accidents Accident Causer = Motorcycle Accident Causer = Other 6.2% 5.2% 4.6% 4.4% Driving accidents Driving accidents are mainly 11.1 addressed by independently % operating 10.0% advanced rider assistant 7.2% systems 1,000 (not C-ITS) 0 Page 12

13 Method: Evaluation of the potential of C-ITS Source: CMC document Application- and Use-Case description Conversion into Filter criteria Applying the filter criteria to the dataset Evaluating the potential of 19 C-ITS applications Result Nr. of addressed accidents with distinction regarding causation Page 13

14 Results Top 10 applications 22% Share in addressed motorcycle accidents (n=28.002, Germany, 2016) 14% 9% 6% 4% 2% 2% 2% MAI: Motorcycle Approach Indication MAW: Motorcycle Approach Warning IMA: Intersection Movement Assist FCW: Forward Collision Warning BSW: Blind Spot Warning LCW: Lane Change Warning LTA: Left Turning Assist EEBL: Emergency Electronic Brake Lights AWW: Adverse Weather Warning 1% 1% Application: Accident Causer: MAI / MAW IMA FCW BSW & LCW LTA IMA FCW EEBL BSW & LCW AWW Other Other PTW Other Other PTW Other PTW PTW PTW Page 14

15 Example: Left Turn Assist - result Nr. Most frequent C-ITS relevant accident scenarios of PTW Scenario Accident Causer no. of accidents % Addressed cases with LTA no. of accidents % 1 Crossing traffic Other ,9% 0 0% 2 Longitudinal traffic PTW ,2% 0 0% 3 Lane Change Other ,0% 0 0% 4 Left turn Other ,2% % 5 Longitudinal traffic Other ,2% 0 0% 6 Lane change PTW ,6% 0 0% 7 U-turn Other ,4% 0 0% 13 Left turn PTW 206 0,7% % The LTA could address: accidents, if the accident causer is the Other vehicle. 123 accidents, if the accident causer is the PTW. Efficiency of LTA in the scenario Left turn is over 70%! Page 15

16 Example scenario: Left turn Car disregards the PTW PTW Source: GIDAS accident case from 2017 Page 16

17 Example scenario: Left turn without LTA Page 17

18 Example scenario: Left turn with LTA Page 18

19 Results Top 10 applications 22% Share in addressed motorcycle accidents (n=28.002, Germany, 2016) 14% 9% 6% 4% 2% 2% 2% MAI: Motorcycle Approach Indication MAW: Motorcycle Approach Warning IMA: Intersection Movement Assist FCW: Forward Collision Warning BSW: Blind Spot Warning LCW: Lane Change Warning LTA: Left Turning Assist EEBL: Emergency Electronic Brake Lights AWW: Adverse Weather Warning 1% 1% Application: Accident Causer: MAI / MAW IMA FCW BSW & LCW LTA IMA FCW EEBL BSW & LCW AWW Other Other PTW Other Other PTW Other PTW PTW PTW Page 19

20 safety benefit for motorcycles CMC Roadmap to make the road safer Be Warned of the unexpected Emergency Electronic Brake Lights See and Get Seen by others Motorcycle Approach Indication Intersection Movement Assist Forward Collision Warning Left Turn Assist Intersection Movement Assist Forward Collision Warning Adverse Weather Warning Road Works Warning Do Not Pass Warning Broken Down Vehicle Warning Traffic Light Violation Warning Motorcycle Approach Warning Lane Change Warning / Blind Spot Warning Lane Change Warning / Blind Spot Warning Ride with Less Stress Group Riding Cooperated Driving Green Light Optimized Speed Advisory Lane Merge Assistant Fuelling & Charging Information Transit Signal Priority Connected Automated Cruise Control technical evolution availability & reliability of data ITS phase I ITS phase II ITS phase III Page 20

21 CMC booth Hall 6 indoor Page 21

22 Thank you for your attention Page 22