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Experimental Verification of the Ultimate Motion Sickness Algorithm & the Motion Sickness Hybrid Control Strategy Via an Autonomous RC-car

2022 4th International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)(2022)

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摘要
Motion sickness (MS) has been identified as the main cause of hindrance in the futuristic Autonomous Vehicles (AV) of level 4 and 5. Our previous works together with the Autodriver algorithm have shown that ergonomic paths and furthermore a hybrid solution based on ergonomic paths and a MS control strategy can reduce MS thresholds by 73.1%. The following study presents an experimental verification of these paths (Ultimate MS Algorithm (UMSA)) and control strategy (MS Hybrid Control Strategy (MSHCS)), using a 1:7 scaled Autonomous RC-car (Traxxas XO-1). It is hypothesised that the UMSA and MSHCS are capable of reducing MS far more than the ordinary transitional curves like; Cloithoids and X-Sin. Results of the experiment agree with the hypothesis indicating that our proposed solutions of UMSA and MSHCS are capable of reducing MS in futuristic AV.
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关键词
Autonomous Vehicles (AV),Motion Sickness (MS),Ultimate Motion Sickness Algorithm (UMSA),Motion Sickness Hybrid Control Strategy (MSHCS),Traxxas XO-1 (RC-Car),LabVIEW,NI MyRIO & Autodriver Algorithm
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