The development of advanced riding assistance systems requires the analysis of user reactions in emergency situations. Motorcycle riding simulators are an alternative to ‘on-road’ testing so that virtual environment dangerous scenarios can be investigated without risks for the participants. In this paper, we propose a process for validation of a low-cost motorcycle simulator characterized by, first, an elastic resistance on the steering input and, second, a counter-steering strategy. For this, 16 riders tested the simulator in different manoeuvres, including a cornering manouvre in a non-urban environment, a slalom manoeuvre and a lane-change manoeuvre. Objective evaluations and subjective evaluations showed that the simulator was realistic, in particular for investigating lateral avoidance scenarios. The development of suitable motorcycle simulators will significantly advance the field of motorcycle safety research.
HHRT – motorcycle safety: IMMA’s contribution to the decade of action for road safety 2011–20. Report, IMMA, Geneva, Switzerland, 2010.
2.
HaworthN. Powered two wheelers in a changing world-challenges and opportunities. Accid Analysis Prevention2012; 44(1): 12–18.
3.
BlackmanRAHaworthNL. Comparison of moped, scooter and motorcycle crash risk and crash severity. Accid Analysis Prevention2013; 57: 1–9.
4.
YehECRoanGKYunIH. Development of an anti-lock brake system for motorcycle. Veh System Dynamics1995; 24(4–5): 427–444.
5.
CornoMPanzaniG. Traction control systems design: a systematic approach. modelling, simulation and control of two-wheeled vehicles. Hoboken, New Jersey: John Wiley, 2014, pp. 198–220.
6.
BiralFLotRRotaS. Intersection support system for powered two-wheeled vehicles: threat assessment based on a receding horizon approach. IEEE Trans Intell Transpn Systems2012; 13(2): 805–816.
7.
BiralFBosettiPLotR. Experimental evaluation of a system for assisting motorcyclists to safely ride road bends. Eur Transp Res Rev2014; 6(4): 411–423.
8.
RuscioDCiceriMRBiassoniF. How does a collision warning system shape driver’s brake response time? The influence of expectancy and automation complacency on real-life emergency braking. Accid Analysis Prevention2015; 77: 72–81.
9.
SavinoGGiovanniniFBaldanziniNPieriniM. Training system for optimal braking on a powered two-wheeler. In: DornL (ed) Driver behaviour training, Vol V. Farnham, Surrey: Ashgate, 2012, pp. 101–125.
BartlettWMeyersD. Time and distance required for a motorcycle to turn away from an obstacle. SAE paper 2014-01-0478, 2014.
12.
SavinoGPieriniMBaldanziniN. Decision logic of an active braking system for powered two wheelers. Proc IMechE Part D: J Automobile Engineering2012; 226(8): 1026–1036.
13.
FreemanPRodriguezJWagnerJ. Validation of a fixed-base automotive simulator for run-off-road safety and recovery training. Proc IMechE Part D: J Automobile Engineering2015; 229(5): 574–89.
MillerDSunAJuW. Situation awareness with different levels of automation. In: 2014 IEEE international conference on systems, man and cybernetics, San Diego, California, USA, 5–8 October 2014, pp. 688–693. New York: IEEE.
16.
FisherDLRizzoMCairdJLeeJD. Handbook of driving simulation for engineering, medicine, and psychology. Boca Raton, Florida: CRC Press, 2011.
17.
KellerMHassCSeewaldABertramT. Driving simulator study on an emergency steering assist. In: 2014 IEEE international conference on systems, man and cybernetics, San Diego, California, USA, 5–8 October 2014, pp. 3008–3013. New York: IEEE.
18.
MarkkulaGBenderiusOWolffKWahdeM. Effects of experience and electronic stability control on low friction collision avoidance in a truck driving simulator. Accid Analysis Prevention2013; 50: 1266–1277.
19.
ItohMLemoineM-PPRobacheFMorvanH. An analysis of driver’s avoiding maneuver in a highly emergency situation. SICE J Control, Measmt, System Integration2015; 8(1): 27–33.
20.
SchiebenAGriescheSHesseT. Evaluation of three different interaction designs for an automatic steering intervention. Transpn Research, Part F: Traffic Psychol Behaviour2014; 27: 238–251.
21.
GreenbergJABlommerM. Physical fidelity of driving simulators. In: FisherDLRizzoMCairdJLeeJD (eds) Handbook of driving simulation for engineering, medicine, and psychology. Boca Raton, Florida: CRC Press, 2011, ch 7.
22.
BenedettoSLobjoisRFaureV. A comparison of immersive and interactive motorcycle simulator configurations. Transpn Research, Part F: Traffic Psychol Behaviour2014; 23: 88–100.
23.
CossalterVLotRRotaS. Objective and subjective evaluation of an advanced motorcycle riding simulator. Eur Transp Res Rev2010; 2(4): 223–233.
24.
CossalterVLotRMassaroM. An advanced multibody code for handling and stability analysis of motorcycles. Meccanica2011; 46(5): 943–958.
25.
BMW. Motorcycle riding simulation to assess instrument and operation concepts and informing riding assistance systems. In: 10th international motorcycle conference, Cologne, Germany, 29–30 September 2014, pp. 443–459. Essen: Institut für Zweiradsicherheit.
26.
CossalterV. Motorcycle dynamics. Raleigh, North Carolina: Lulu Press, 2006.
27.
StedmonABrickellEHancoxM. MotorcycleSim: a user-centred approach in developing a simulator for motorcycle ergonomics and rider human factors research. Adv Transpn Stud2012; 27: 31–48.
28.
PopovARowellSMeijaardJ. A review on motorcycle and rider modelling for steering control. Veh System Dynamics2010; 48(6): 775–792.
29.
KooijmanJSchwabA. A review on bicycle and motorcycle rider control with a perspective on handling qualities. Veh System Dynamics2013; 51(11): 1722–1764.
30.
FiltnessAJRudin-BrownCMulvihillCLennéMG. Impairment of simulated motorcycle riding performance under low dose alcohol. Accid Analysis Prevention2013; 50: 608–615.
31.
CossalterVLotRPerettoM. Steady turning of motorcycles. Proc IMechE Part D: J Automobile Engineering2007; 221(11): 1343–1356.
32.
CossalterVLotRMassaroMSartoriR. Development and validation of an advanced motorcycle riding simulator. Proc IMechE Part D: J Automobile Engineering2011; 225(6): 705–720.
GiovanniniFSavinoGPieriniMBaldanziniN. Analysis of the minimum swerving distance for the development of a motorcycle autonomous braking system. Accid Analysis Prevention2013; 59: 170–184.
35.
LenkeitJFHagoskiBKBakkerAI. A study of motorcycle rider braking control behavior. Report DOT HS 811 448, US Department of Transportation, National Highway Traffic Safety Administration, Washington, DC, USA, 2011.
36.
SavinoGRizziMBrownJ. Further development of motorcycle autonomous emergency braking (MAEB), what can in-depth studies tell us? A multinational study. Traffic Injury Prevention2014; 15(Suppl 1): S165–S172.
