Evaluation and Modeling of Passenger Vehicle Celeration Performance Based on Artificial Neural Networks

Abstract:

As the siginificant factors influence passengers comfort, the vehicle celebration performance may easy to cause accidents, such as hard acceleration and deceleration performance. In order to find the relationship between passengers comfort and celebration performance, 35 passengers and three professional drivers were recruited in the field experiment. The passengers’ comfort feelings were analysed by subject questionnaires, the acceleration and deceleration data were received by CAN bus.The Artificial Neural Networks (ANNs) model was elaborated to estimate and predict the passengers comfort level of driver unsafe acceleration behavior situations. Therefore, the subject views of the passengers could be compared to object acceleration data. An ANN is applied to interconnect output data (subjective rating) with input data (objective parameters). Finally, it is found the investigatioin have demonstrated that the objective values are efficiently correlated with the subjective sensation. Thus, the presented approach can be effectively applied to support the drive train development of bus.

• Periodical: Applied Mechanics and Materials (Volumes 744-746)
• Pages: 1938-1942
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.744-746.1938
• Online since: March 2015
• Authors: Yi He*, Duan Feng Chu
• Keywords: Acceleration Behaviors, ANNs, BUS, Field Experiment, Passengers Comfort

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