The wheel force transducer is an important device in the automotive testing field which can measure the force or torque applied to the wheel. Because existing wheel force transducers are almost commercial products, they are too expensive and technical information about them has not been made public; this slows down the development of the wheel force transducer to a certain extent. Accordingly a three-axis wheel force transducer is presented in this paper which is selfdecoupled without calculating the decoupling matrix in theory. Its elastic body has a spoke structure with eight elastic beams, which means that it is easy to fabricate. This paper first introduces the overall elastic body structure of the proposed wheel force transducer. Then the strain gauge arrangement, the principle of strain measurement, the connection modes of the bridge circuits and the rotation decoupling principle for F x and F z are analysed, and the self-decoupled characteristics are depicted in detail. Finally, to verify the validity of the designed wheel force transducer, three kinds of experiment are carried out. In the static experiments the static performance and the self-decoupled characteristics of the wheel force transducer are verified; in the dynamic tests, a vehicle dynamics test system is adopted to verify the accuracy of the wheel force transducer in the dynamic environment; in road tests, the sensor is installed in the vehicle to verify whether the output of the proposed wheel force transducer can reflect the variation in the force applied to the wheel in practical applications. The results shows the following: first, the maximum non-linearity error, the maximum hysteresis error and the maximum repeatability error of the proposed wheel force transducer are 0.9% of the full scale, 1.1% of the full scale and 0.5% of the full scale respectively; second, the static coupling rate is about 0.08%, which means that the designed wheel force transducer is self-decoupled in theory; third, the proposed wheel force transducer can measure F x , F z and M y effectively in real applications.

While cloud computing has brought paradigm shifts to computing services, researchers and developers have also found some problems inherent to its nature such as bandwidth bottleneck, communication overhead, and location blindness. The concept of fog/edge computing is therefore coined to extend the services from the core in cloud data centers to the edge of the network. In recent years, many systems are proposed to better serve ubiquitous smart devices closer to the user. This article provides a complete and up-to-date review of edge-oriented computing systems by encapsulating relevant proposals on their architecture features, management approaches, and design objectives.

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To overcome the drawbacks of using a traditional proportional-integral-derivative (PID) control method for a robot driver system, such as requiring preliminary offline learning, big overshoot and large speed fluctuation, a new method for speed tracking of a robot driver system based on sliding mode control is proposed in this paper. Firstly, the coordinated control model of multiple manipulators for the robot driver is built, which achieved coordinated control of the throttle mechanical leg, clutch mechanical leg, brake mechanical leg and shift mechanical arm for the robot driver. On the basis of this, a speed tracking sliding mode controller for a vehicle robot driver is designed using the method of multiple sliding surfaces design, and the variable structure control laws of throttle and brake are designed respectively, which realize the speed tracking of the given driving test cycle. Experimental results demonstrate that compared with the PID control method, the proposed method can obviously reduce the overshoot of vehicle speed tracking control and greatly improve the accuracy of vehicle speed tracking. The vehicle speed tracking accuracy stays within a tolerance band of ±2 km/h, which meets the requirements of national vehicle test standards. Furthermore, the action of the speed tracking control in the same driving test cycle using the proposed method is consistent, so that the robot driver has good repeatability. Therefore, it can ensure the effectiveness of the vehicle emission test.

Many intelligent transportation system applications require accurate, reliable, and continuous vehicle positioning. How to achieve such positioning performance in extended GPS-denied environments such as tunnels is the main challenge for land vehicles. This paper proposes a hybrid multi-sensor fusion strategy for vehicle positioning in tunnels. First, the preliminary positioning algorithm is developed. The Radio Frequency Identification (RFID) technology is introduced to achieve preliminary positioning in the tunnel. The received signal strength (RSS) is used as an indicator to calculate the distances between the RFID tags and reader, and then a Least Mean Square (LMS) federated filter is designed to provide the preliminary position information for subsequent global fusion. Further, to improve the positioning performance in the tunnel, an interactive multiple model (IMM)-based global fusion algorithm is developed to fuse the data from preliminary positioning results and low-cost in-vehicle sensors, such as electronic compasses and wheel speed sensors. In the actual implementation of IMM, the strong tracking extended Kalman filter (STEKF) algorithm is designed to replace the conventional extended Kalman filter (EKF) to achieve model individual filtering. Finally, the proposed strategy is evaluated through experiments. The results validate the feasibility and effectiveness of the proposed strategy.

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