Final Activity Report Summary - MYMOSA (Motorcycle and Motorcyclist safety) The general objective of MYMOSA RTN was the improvement of PTW safety and riders' safety leading to a significant reduction of injuries and fatalities of motorcyclists. This objective has been reached by development of simulation tools, predictive models and new protective equipment concepts. WP1 "Accident dynamics" has fulfilled its technical objective to develop a well-validated CAE methodology - and corresponding toolset - to describe the interaction between vehicle-rider & its environment during motorcycle riding (both for the pre-accident and the accident phase). This has been done by focusing on the; Motorcycle Modelling; Rider Modelling; Pre-crash phase dynamics simulation of motorcycle-rider system. The validity of the integrated motorcycle-rider modelling has been proven through realistic driver scenario simulations. The rider characteristics represent a large unknown in the model environment, an experimental test rig has been proposed and developed, which can be used to measure the static & dynamic rider characteristics. The experimental test rig could only be achieved by closely working together. The researchers have - in addition to technical deliverables - set key steps into personal development, through the interaction and organisation of activities, the presentation of their results and the publication of many papers at conferences and in journals. WP2: The WP on integrated safety investigated the relevant topics in order to contribute to the development of an on-board safety system capable to assist the rider in safety critical situations both during normal riding conditions and in pre-crash (i.e. when a crash is unavoidable). The system was developed starting from an in-depth accidentology study based on the MAIDS database, which provided the necessary information on the most relevant accident configurations both in terms of rider actions/manoeuvres, kinematic behaviour and injuries. A system architecture (i.e. necessary sensors, functions and devices) was proposed and its potential benefits were assessed. Lastly the decision logic of the system, which incorporates research results on sensors and human factors, was developed. The proposed safety system is capable to warn the rider or, if a crash was unavoidable, to trigger autonomous actions to reduce the crash severity. WP3: The objectives of this WP are; improvement of the energy absorbing capabilities of safety helmets; proposal for new helmet standards. The research carried out on the improvement of safety helmets produced two prototypes; 1. includes aluminium honeycomb inserts in the polystyrene foam; 2. has an energy absorbing liner made of a plastic material with an optimised structure. The two prototypes achieve a higher level of energy absorption with respect to their commercial counterparts in some impact configurations and they represent promising alternatives. However further investigations are needed for a full assessment of their performances. The possibility of making the standard tests more relevant to real-life accidents was explored and produced interesting ideas that were presented at two IRCOBI conferences and awarded to Mr Ghajari the award for the best paper presented by a young scientist. In a nutshell the main idea generated by the work of Mr Ghajari is to increase the mass of the head-forms used in standard tests to take into account the presence of the human body. WP4 developed new biomechanical knowledge on head and neck, specifically for motorcyclists based on the current knowledge of car occupants and pedestrians. Based on volunteer sled testing simulating motorcycle (pre-crash) braking, it was found that volunteer kinematic behaviour was mainly determined by their trait, being stiff or floppy and that other factors such as pre-warning were of little influence. A methodology was developed for measurement of rider kinematics on an actual motorcycle. Based on an existing multi-body head-neck model, humanlike stabilising and bracing control of the head was implemented and validated against above tests & other available tests from automotive pre-crash research. A FE muscle material model was implemented, 3D muscles.
