A wheel force transducer is a vital instrument in the vehicle-testing field which provides a means for determining experimentally the forces and the moments transmitted to a vehicle through the tyre contact patch. However, existing wheel force transducers are almost commercial products. They are expensive and, for business reasons, technical information is not made public. This slows down the development of the wheel force transducer itself to a certain extent. Moreover, research studies on the wheel force transducer mainly focus on utilization of this tool for vehicle simulations, traction control and anti-lock braking evaluation as it provides information on the characteristics, the performance and the limitations of the vehicle. From the perspective of the sensor itself, although improvement in the transducer accuracy and information extraction using signal-processing methods have been successfully developed in the literature, few investigations on the design of the wheel force transducer have been reported yet. Accordingly, a general design and optimization procedure for the wheel force transducer with a practical case study will be of great significance. Since technical difficulties, admittedly, are primarily about the issues of how to design and optimize the transducer, in this paper a new self-decoupled six-axis wheel force transducer for a heavy truck is designed and fabricated. An easy-to-understand design procedure is highlighted mainly including the conceptual design with the aims of a universal-purpose self-decoupled transducer with an eight-spoke structure, an optimization design which depends on the proposed comprehensive performance criteria in the computer-aided procedure, and a collectivity design focus on the mechatronics assembly for a heavy-truck application. Finally, the wheel force transducer is manufactured, calibrated and tested. The results show that the mean errors of the six-axis forces are about 3% of the full scale with 1% non-linearity, 0.5% repeatability and 1% hysteresis for the sensor only, that there are increased mean values of about 2% non-linearity, 1% repeatability and 1.4% for a certain tyre assembly and that the observed dynamic response is about 2.5–3.5 ms. Both the self-decoupled characteristics and the sensor performance are verified to meet the design and optimization, and the transducer with a real-time wheel force output is also confirmed by road tests.

In this paper,an adaptive steering robust nonlinear control methodbased on driver behavior is presented for an unmanned driving robotic vehicle (UDRV),in order to achieve accurate and stable steering control of UDRV.Considering modeling uncertainties and unknown nonlinear external disturbances, a UDRV nonlinear dynamics model is established. A driver behavior model is established including a coordinate transformation model, a driver virtual path planning model, and a driver desired yaw rate model. Basis of this, anadaptive steering robust nonlinear controller for UDRV is presented, consisted of an adaptive robust backstepping controller and a nonlinear disturbance observer (NDO). TheNDO is designed to compensate for modeling uncertainties and unknown nonlinear external disturbances. The adaptive steering robust nonlinear controller for UDRV is designed through backstepping method and NDOcompensation. The stability of controlsystem is proved. Finally, double lanechange experiments are conducted.Comparison analysis results among the proposed control method, other existed control method and human driver demonstrate the effectiveness of the proposed method.

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.

Understanding the wheel–terrain interaction (WTI) is of great importance to improve the traversability of the planetary rovers. In this article, the design and implementation of an instrumented wheel (IW) for characterizing the WTIs are presented. Such an IW is the key technique of the wheel-on-limb detection (WOLD) system that aims for the forward terrain sensing and traversability prediction before the traversal of the rover. In situ measurements of the WTI forces, wheel velocity, and wheel contact angle, as well as the wheel sinkage, can be achieved via such an IW. Experimental calibration is first implemented to guarantee the IW performance. Then, field tests in the representative environments are conducted to verify the measured parameters of WTIs. It has indicated that such a system concept would be potentially applicable in the future long-safe planetary traverses concerning the rover payloads development and functional validation.

A novel approach for online re-calibration of Wheel Force Transducer/Sensor (WFT) is proposed in this paper. It combines the initial angle alignment and shape-from-motion calibration by taking advantage of the wheel rotation characteristics. The gravitational load of the vehicle is only served as loading constraint in the calibration. Both of the two calibration procedures can iteratively update each other to reach the desired accuracy and efficiency without requiring the redundant data collection that performs inconvenient repeated loading cycles. A two-axis wheel force sensor is modelled and calibrated with the Gravity based Method (GM), the Initial-Value based Method (IVM), as well as the Independent Shape-from-motion Method (ISM) for comparison purposes. The tested results demonstrate that the proposed GM provides an accurate, practical, and effective technique for on-line calibrating the WFTs.