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This article discusses a vehicle stability improvement control method that utilizes an electric power steering system (EPS) with blushless motor. The purpose is to improve the vehicle stability by increasing the steering return torque in a region where the alignment torque is saturated due to the driver's excessive steering maneuver on a slippery road. In this study, a factor analysis was performed for the alignment torque on a slippery road and the basic control to improve the vehicle dynamics stability is studied by using a linear m1odel. Next, a new control algorithm was developed based on these studies. Finally, the new control algorithm was verified to be effective through an on-vehicle test. The proposed strategy can be realized only by adding a steering wheel angle sensor signal to a conventional EPS. That can be easily obtained from electronic stability control system.

In this paper, we suggest a novel algorithm to distinguish semi-steady states from various steering patterns and to estimate the stability factor. The algorithm also estimates each stability factor in left and right turns because there could be a case where they differ based on uneven tire wear and so on. The stability factor, which is the turning characteristic of a vehicle, has been treated as constant for most vehicle control systems. However, in fact, it may change in some situations, for example when a vehicle is overloaded. So there is a chance that a driver may be aware of an unusual sensation when vehicle control is designed based on a constant stability factor. We have succeeded in developing an algorithm to estimate the stability factor accurately enough to be able to compensate for it and have confirmed the effectiveness of the algorithm by simulation and vehicle testing as well.

We have developed a driving simulator for Electric Power Steering (EPS), which can be used to evaluate steering maneuverability on low μ roads. The simulator calculates an 11 DOF (degrees of freedom) vehicle motion based on the steering wheel angle, the accelerator pedal position and the brake pedal position which are operated by the driver. A reaction torque corresponding to the alignment torque is applied to the steering shaft using motors. A 3D CG reproducing the view from the cockpit is displayed on a forward screen. The simulator also includes column type EPS, which generates the assist torque. Consequently, the driver feels the steering torque with good reality. The tire model we used is non-linear and it enables us to simulate the vehicle dynamics also on slippery roads. We compared driver behavior in vehicle and simulator tests and found the simulator could evaluate the relationship between steering maneuverability and EPS control strategy even when the road was slippery.

Steady advances in autonomous vehicle development are expected to lead to improved traffic flow in terms of string stability compared with that for human-driven vehicles. Fluctuation in intervehicle distances among a group of vehicles without string stability is amplified as it propagates upstream (rearward), which may cause traffic congestion. Since it will take a few decades for autonomous vehicles to replace all human-driven vehicles, it is important to tackle the problem of traffic congestion in a mixed flow of human-driven and autonomous vehicles. Communication technologies such as fifth-generation mobile communication systems, which are improving rapidly, enable vehicle-to-vehicle communication with a sufficiently small delay. We previously reported a strategy based on vehicle-to-vehicle communication for avoiding traffic congestion by using leader–follower control, which is a distributed autonomous control strategy.