Abstract
A novel method is proposed to establish the stability criterion of B-double based on the clustering algorithm. The patterns recognizing in the lateral stability of B-double is studied. The vehicle model of multi-degree of freedom is established in the TruckSim. The off-line clustering center is obtained by K-means clustering. The TruckSim & Simulink co-simulation platform is built to identify the vehicle driving stability according to the online identification. The method is of data mining, which makes full use of the comparison of offline data and real-time data. The simulation results show that the method can accurately and real-time quantify the lateral driving stability of the B-double considering various factors, which can provide the criterion for intervention timing and degree of control system.
This research was supported by the National Natural Science Foundation of research on vehicle driving stability region based on driving torque and steering angle bifurcation (51475199) and open project of Key Laboratory of Transportation Industry for safe technology in vehicle operation (KFKT2016-01).
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Liu, Hf., Xu, Q., Xu, Hg., Bao, Cz., Wang, Gj., Zhang, Yh. (2019). Study on the Lateral Stability of B-Double Based on Clustering Analysis. In: Wang, W., Bengler, K., Jiang, X. (eds) Green Intelligent Transportation Systems. GITSS 2017. Lecture Notes in Electrical Engineering, vol 503. Springer, Singapore. https://doi.org/10.1007/978-981-13-0302-9_41
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DOI: https://doi.org/10.1007/978-981-13-0302-9_41
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