The trajectory of a vehicle is comprehensively affected by the interactions between the vehicle, the driving behavior, and the road environment. High-risk driving behaviors and accident-prone road sections can be identified based on the relationship between the trajectory and road geometry. Previous related studies mostly focused on the trajectory deviation at a few points on the road, which cannot capture the continuous variation of the trajectory in an entire curve, and seldom considered the trajectory characteristics along curves with large deflection angles. The aim of this study is to investigate the trajectories passenger cars take on two-lane mountain roads and thus to determine the track patterns and its relevant risks.

In this study, to calibrate the acceleration/deceleration rates in operating speed prediction models, driving tests were performed on two-lane mountain highways using passenger cars, and continuous longitudinal acceleration data were collected. The acceleration/deceleration rates of large vehicles such as coaches and heavy trucks were also measured from the roadside. The collected data were used to determine the cumulative frequency profiles and statistical distribution characteristics of the peak acceleration for different types of vehicles. Based on the established correlations, models of acceleration/deceleration versus road geometry features were developed. The key findings of this study are as follows: First, for passenger cars, the deceleration rate is obviously greater than the acceleration rate. Therefore, it would be inappropriate to use the same value for both the rates in speed prediction models. Instead, acceleration and deceleration should be calibrated separately. Second, none of the breakpoints on the acceleration/deceleration cumulative frequency curves appears at the 85th percentile; rather, they appear closer to the 95th percentile. Therefore, the common practice of using the 85th percentile in highway design should probably be reconsidered. Third, for large coaches, the acceleration and deceleration rates are quite similar, whereas for heavy trucks, the deceleration rate is significantly larger than the acceleration rate. The acceleration and deceleration rates of heavy trucks are both lower than those of coaches. Finally, for passenger cars driving around a curve, a negative correlation exists between the acceleration/deceleration rate and curve radius and a positive correlation exists between the acceleration/deceleration rate and deflection angle.

The most significant assumption of conventional analytical methods (e.g., the subdomain technique) is that the stator and rotor iron cores are infinitely permeable. The magnetic saturation is ignored, resulting in an overestimation of the flux density. This paper presents an analytical model of permanent magnet (PM) machines with segmented Halbach arrays (PMMSHA). It considers the finite magnetic permeabilities of the stator teeth and tooth tips (STTT) and can study the tooth saturation effect. The permeability variation in the slots and teeth is solved via Cauchy’s product theorem. Based on magnetic vector potential and the Maxwell-Fourier method, Poisson’s and Laplace’s equations in the stator teeth/slots, tooth tips/slot openings, air gap, and PMs regions are solved. Consequently, the electromagnetic performance, including the magnetic field distribution in all regions, exciting force density, cogging torque, and electromagnetic torque, is calculated. The results of finite element analysis (FEA) show that the analytical model is highly accurate. Furthermore, the influences of the permeability of the STTT and the number of blocks per pole (NBPP) on the performance of the PMMSHA are studied.