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Comparative ride comfort analysis of in-service trams on extreme alignment configurations using smartphone-based sensing

In this paper, a cost-effective method for monitoring and evaluating the tramway passenger comfort and ride quality are presented using motion sensor data of smartphone fitted to in-service vehicles. Running vehicles experience a broad spectrum of vibrations and oscillations that occur in response to excitation inputs of vehicle-track coupled dynamics. Android mobile platform-based acquisition software is developed (CAFat) for commercial use, and the data from smartphone built-in sensors such as accelerometer and gyroscope are processed by sensor fusion and are coupled with local and global positioning using GNSS data to identify sections with poor ride quality. Results are promising and demonstrate that poor ride quality can be accurately localized on a tramway network. The proposed method enables infrastructure monitoring done by conventional passenger cars and makes the possibility of comparing the ride quality of traditional old-designed and the modular multi-articulated in-service vehicles.