MWMingyang Wang

Mingyang Wang

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Mingyang Wang has a total of 5 co-authors. Here are the top co-authors by number of shared publications:

  • Wei Wang

    Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan

    3 shared publications
  • Xinbo Chen

    School of Automotive Studies, Tongji University, Shanghai, China

    3 shared publications
  • Baobao Jin

    Institute of Intelligent Vehicles, School of Automotive Studies, Tongji University, No. 4800 Cao’an Highway, Jiading District, Shanghai 201804, China

    2 shared publications
  • Pengyuan Lv

    Institute of Intelligent Vehicles, School of Automotive Studies, Tongji University, No. 4800 Cao’an Highway, Jiading District, Shanghai 201804, China

    2 shared publications
  • Yong Shen

    Institute of Intelligent Vehicles, School of Automotive Studies, Tongji University, No. 4800 Cao’an Highway, Jiading District, Shanghai 201804, China

    2 shared publications

Latest Publications

  • Open Access

    UWB Based Relative Planar Localization with Enhanced Precision for Intelligent Vehicles

    by Mingyang Wang, Xinbo Chen, Pengyuan Lv, Baobao Jin, Wei Wang, Yong Shen

    Along with the rapid development of advanced driving assistance systems for intelligent vehicles, essential functions such as forward collision warning and collaborative cruise control need to detect the relative positions of surrounding vehicles. This paper proposes a relative planar localization system based on the ultra-wideband (UWB) ranging technology. Three UWB modules are installed on the top of each vehicle. Because of the limited space on the vehicle roof compared with the ranging error, the traditional triangulation method leads to significant positioning errors. Therefore, an optimal localization algorithm combining homotopy and the Levenberg–Marquardt method is first proposed to enhance the precision. The triangular side lengths and directed area are introduced as constraints. Secondly, a UWB sensor error self-correction method is presented to further improve the ranging accuracy. Finally, we carry out simulations and experiments to show that the presented algorithm in this paper significantly improves the relative position and orientation precision of both the pure UWB localization system and the fusion system integrated with dead reckoning.


  • Open Access

    Unified Chassis Control of Electric Vehicles Considering Wheel Vertical Vibrations

    by Xinbo Chen, Mingyang Wang, Wei Wang

    In the process of vehicle chassis electrification, different active actuators and systems have been developed and commercialized for improved vehicle dynamic performances. For a vehicle system with actuation redundancy, the integration of individual chassis control systems can provide additional benefits compared to a single ABS/ESC system. This paper describes a Unified Chassis Control (UCC) strategy for enhancing vehicle stability and ride comfort by the coordination of four In-Wheel Drive (IWD), 4-Wheel Independent Steering (4WIS), and Active Suspension Systems (ASS). Desired chassis motion is determined by generalized forces/moment calculated through a high-level sliding mode controller. Based on tire force constraints subject to allocated normal forces, the generalized forces/moment are distributed to the slip and slip angle of each tire by a fixed-point control allocation algorithm. Regarding the uneven road, H∞ robust controllers are proposed based on a modified quarter-car model. Evaluation of the overall system was accomplished by simulation testing with a full-vehicle CarSim model under different scenarios. The conclusion shows that the vertical vibration of the four wheels plays a detrimental role in vehicle stability, and the proposed method can effectively realize the tire force distribution to control the vehicle body attitude and driving stability even in high-demanding scenarios.


  • Open Access

    A Novel V2V Cooperative Collision Warning System Using UWB/DR for Intelligent Vehicles

    by Mingyang Wang, Xinbo Chen, Baobao Jin, Pengyuan Lv, Wei Wang, Yong Shen

    The collision warning system (CWS) plays an essential role in vehicle active safety. However, traditional distance-measuring solutions, e.g., millimeter-wave radars, ultrasonic radars, and lidars, fail to reflect vehicles’ relative attitude and motion trends. In this paper, we proposed a vehicle-to-vehicle (V2V) cooperative collision warning system (CCWS) consisting of an ultra-wideband (UWB) relative positioning/directing module and a dead reckoning (DR) module with wheel-speed sensors. Each vehicle has four UWB modules on the body corners and two wheel-speed sensors on the rear wheels in the presented configuration. An over-constrained localization method is proposed to calculate the relative position and orientation with the UWB data more accurately. Vehicle velocities and yaw rates are measured by wheel-speed sensors. An extended Kalman filter (EKF) is applied based on the relative kinematic model to combine the UWB and DR data. Finally, the time to collision (TTC) is estimated based on the predicted vehicle collision position. Furthermore, through UWB signals, vehicles can simultaneously communicate with each other and share information, e.g., velocity, yaw rate, which brings the potential for enhanced real-time performance. Simulation and experimental results show that the proposed method significantly improves the positioning, directing, and velocity estimating accuracy, and the proposed system can efficiently provide collision warning.