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Electric power steering systems (EPS) greatly improve fuel performance over conventional hydraulic power steering systems, and therefore being increasingly adopted. However, it is very important to evaluate the mechanical noise and to identify the correct noise source in steering systems, because an EPS has vibration sources such as at the motor gear reducer, manual gears and intermediate joints. In order to identify the noise source, a technique based on time-frequency analysis using the wavelet transform (WT) has been focused on which uses a mother wavelet (MW) that is derived mathematically. The measured signal is adopted as the MW. In this study, applying this method to time-varying signals, a new concept of the Wavelet Instantaneous Correlation Value (WICV) is discussed and is used to identify the noise source.

A Steer-by-wire (SBW) system, which has no mechanical linkage, is expected to support the driver even in critical situations so as to improve collision safety and cockpit design flexibility. We have shown the effectiveness of driver assistance using an active steering control integrated with active braking control.[1] This is a case of normal driving without any vital component failures. The SBW system failure, however, can lead to an unsafe driving situation. A highly redundant design reduces the SBW failures but complicates its design and increases cost, volume and weight. This paper proposes a new fault-tolerant architecture to cope with the SBW failure. This is based on an integrated control by SBW, active braking, and driving torque distribution. A feasibility study is made using a driving simulator experiment during front obstacle avoidance under failed SBW.

We have developed a new active-front-steering system which contributes to the vehicle safety improvement. This system includes two motors and differential gear unit in one body. It makes possible to compensate steer angle and control reactive torque simultaneously. This means driver assistance control without interference on driver. This concept has a potential to omit tuning process on each vehicle, and reduce weight and cost. We have proved the effect of driver assistance control by this system.

In the recent years, the interaction between human driver and Advanced Driver Assistance System (ADAS) has gradually aroused people’s concern. As a result, the concept of personalized ADAS is being put forward. As an important system of ADAS, Lane Keeping Assistance System (LKAS) also attracts great attention. To achieve personalized LKAS, driver lane keeping characteristic (DLKC) indices which could distinguish different driver lane keeping behavior should be researched. However, there are few researches on DLKC indices for personalized LKAS. Although there are many researches on modeling driver steering behavior, these researches are not sufficient to obtain DLKC indices. One reason is that most of researches are for double lane change behavior which is different from driver lane keeping behavior. The other reason is that the researches on driver lane keeping behavior only provide model structure and rarely discuss identification procedure such as how to select suitable data.

Lane Centering Control System (LCCS) is a lateral Advanced Driving Assistance System (ADAS) with low acceptance. One of the main reasons is that the centering trajectory can’t satisfy different drivers, which is more obvious in the curve condition. So LCCS adaptive to different drivers needs to be designed. The trajectory planning module is an important part for LCCS. It generates trajectory according to the road information for the vehicle control module to track. This paper uses road information obtained from the scenario established in Prescan, and the trajectory planning method proposed can generate trajectories for different drivers in the curve condition. To achieve the goal, this paper proposes a trajectory planning method which contains lateral path planning and longitudinal speed planning. Firstly, the overall strategy of “road equidistant segments division” is used to describe the road information.

Steering reaction torque is one of the most important types of information for drivers since it has significant influence on vehicle maneuverability. Even with today's advanced simulation technology, however, it is very difficult to accurately simulate steering feeling. The purpose of this study is to develop a steering Hardware-in-the-Loop (HIL) simulator that can quantitatively evaluate steering systems. This simulator can control the force on the tie rod with simple mechanism. The validity of this HIL simulator has been ascertained by comparing the simulation results with those obtained during actual vehicle testing.The preliminary research concerning the advanced simulators based on the developed HIL simulator is also reported.

Lane Keeping Assistance (LKA) system is a very important part in Advanced Driver Assistance Systems (ADAS). It prevents a vehicle from departing out of the lane by exerting intervention. But an inappropriate performance during LKA intervention makes driver feel uncomfortable. The intervention of LKA can be divided into 3 parts: intervention timing, intervention process and intervention ending. Many researches have studied about the intervention timing and ending, but factors during intervention process also affect driver feelings a lot, such as yaw rate and steering wheel velocity. To increase driver’s acceptance of LKA, objective and subjective tests were designed and conducted to explore important indices which are highly correlated with the driver feelings. Different kinds of LKA controller control intervention process in different ways. Therefore, it’s very important to describe the intervention process uniformly and objectively.

In order to satisfy design requirements of Lane Keeping Assistance System (LKAS), a Driver Steering Override (DSO) strategy is necessary for driver’s interaction with the assistance system. The assistance system can be overridden by the strategy in case of lane change, obstacle avoidance and other emergency situations. However, evaluation and optimization of the DSO strategy for LKAS cannot easily be completed quantitatively considering driver’s acceptability. In this research, firstly subjective and objective evaluation experiment is designed. Secondly, correlations between the subjective and the objective evaluation results are established by using regression analysis. Finally, based on the correlations established previously, the optimal performance of DSO strategy is obtained by setting the desired comprehensive evaluation ratings as the optimized goal.

Sliding intermediate shaft of Electric Power Steering (EPS) system is used for torque transmission from steering wheel or motor and buffering reverse input from tire. Polyamide coating material with good sliding properties is treated in the sliding types of intermediate shaft. Conventionally, sliding types of intermediate shaft with polyamide coating have been used in vehicle interior. On the other hand, extension of applied area to engine room is needed. However, in high temperature conditions, there is concerns about increase of friction coefficient and wear volume of polyamide by deterioration of sliding properties of polyamide. Therefore, improvement of sliding properties of polyamide in high temperature is necessary. In this research, we examined sliding properties of polyamide blended with metal stearate in high-temperature to use polyamide in high temperature compared to conventional environment. As resin material, we used polyamide 610 blended with metal stearates.

Lane Keeping Assistance System (LKAS) is a typical lateral driver assistance system with low acceptance. One of the main reasons is that fixed parameters cannot satisfy individual differences. So LKAS adaptive to driver characteristics needs to be designed. Driver Steering Override (DSO) process is an important process of LKAS. It happens when contradiction between driver’s intention and system behavior occurs. As feeling of overriding will affect the overall experience of using LKAS, the design of DSO characteristics is worthy of attention. This research provided an adaptive design scheme aiming at DSO characteristics for LKAS by building Driver Preference Model (DPM) based on simulator test data from preliminary experiments. The DPM was to represent the relationship between driver characteristics indices and driver preferred system characteristics indices. So that new drivers’ preference can be predicted by DPM based on their own daily driving data with LKAS switched off.