## 5 Conclusions  
In this paper, an integrated speed-planning and friction coefficient estimation (ISPFCE) algorithm is proposed. The friction coefficient is estimated online by means of torque injection. If a decrease in the friction coefficient is detected before a tight bend, the speed can be adjusted to a safe value before an accident could potentially occur. A simulation based on CarSim and Simulink demonstrates the effectiveness of the proposed algorithm. The present paper reveals that a sudden decrease in the friction coefficient is dangerous for vehicles on curved roads, potentially leading to serious traffic accidents. Conventional lane-keeping systems and cruise control systems without friction estimation may fail to handle such a decrease in the friction coefficient properly, particularly on a curved road with a large curvature. One feasible solution is to estimate the friction coefficient online and reduce the speed before such a bend with a low friction coefficient, which is the key purpose of the algorithm proposed in this paper.  
Figure 34: Speed Plan D: (**a**) Controller A + ISPFCE and (**b**) Controller B + ISPFCE.  
Figure 32: Speed Plan B: (**a**) Controller A + ISPFCE and (**b**) Controller B + ISPFCE.  
As discussed above, speed-planning and friction coefficient estimation are critical for ensuring the safety of vehicles. In the proposed ISPFCE algorithm, only speed planning for the host vehicle is considered. In fact, however, it is also useful to estimate the friction coefficients and planned safe speeds for other vehicles. Thus, given a suitable vehicular network, it is also essential to send relevant information to other vehicles that cannot estimate the friction coefficient for planning safe speeds. The question of how to use the information collected by the host vehicle to improve the safety of other nearby vehicles will be investigated in the future. Due to the practical limitations concerning available equipment and experimental sites, only a numerical simulation is reported in this study. Further experimental investigations will also be conducted to improve the performance of the ISPFCE algorithm.  
Conceptualization, C.B.; methodology, C.B.; validation, C.B., T.Z., G.Y. and L.X.; writing, original draft preparation, C.B. and T.Z.; writing, review and editing, T.Z. and L.X.; supervision, G.Y.  
This research was funded by the National Natural Science Foundation of China, Grant Numbers 51575103 and U1664258; the National Key R&D Program in China, Grant Numbers 2016 YFB0100906 and 2016 YFD0700905; the Foundation of State Key Laboratory of Automotive Simulation and Control, Grant Number 20160112; and the Scientific Research Foundation of Graduate School of Southeast University and Southeast University Excellent Doctor Degree Thesis Training Fund, Grant Numbers YBJJ1703 and YBJJ1704.  
The authors wish to express their gratitude to the anonymous reviewers and the Associate Editor for their rigorous comments during the review process.  
The authors declare no conflict of interest.  
The following abbreviations are used in this manuscript:  
integrated speed planning and friction coefficient estimation  
center of gravity