A Hybrid Path Planning Method Based on Articulated Vehicle Model

Due to the unique steering mechanism and driving characteristics of the articulated vehicle,a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle.First,Support Vector Machine(SVM)theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin,and then,several key points are selected from the optimal zero potential curves by using Longest Accessible Path(LAP)method.Next,the Cubic Bezier(CB)curve is adopted to connect the curve that satisfies the curvature constraint of the articulated vehicle between every two key points.Finally,Back and Forth Rapidly-exploring Random Tree with Course Correction(BFRRT-CC)is designed to connect paths that do not meet articulated vehicle curvature requirements.Simulation results show that the proposed hybrid path planning method can search a feasible path with a 90-degree turn,which meets the demand for obstacle avoidance and articulated vehicle back-and-forth movement.

Design and Implementation of PLC-Based Autonomous Construction System of Unmanned Vibratory Roller

The vibratory roller is a piece of vital construction machinery in the field of road construction.The unmanned vibratory roller efficiently utilizes the automated driving technology in the vehicle engineering field,which is innovative for the unmanned road construction.This paper develops and implements the autonomous construction system for the unmanned vibratory roller.Not only does the roller have the function of remote-controlled driving,but it also has the capability of autonomous road construction.The overall system design uses the Programmable Logic Controller(PLC)as the kernel controller.It establishes the communication network through multiple Input/Output(I/O)modules,Recommended Standard 232(RS232)serial port,Controller Area Network(CAN)bus,and wireless networks to control the roller vehicle completely.The locating information is obtained through the Global Navigation Satellite System(GNSS)satellite navigation equipment group to support the process of autonomous construction.According to the experimental results,the autonomous construction system can finally enable the roller to perform driving operations and construction independently,which was a significant step forward in engineering application.

The Roll Stability Analysis of Semi-Trailer Based on the Wheel Force

It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance,and that may cause serious accidents.Although the scholars did lots of research about the roll stability of liquid tank semi-trailer in theory by calculating and simulation,how to make an effective early warning of rollover is still unsolved in practice.The reasons include the complex driving condition and the difficulty of the vehicle parameter obtaining.The feasible method used currently is evaluating the roll stability of a liquid tank semi-trailer by the lateral acceleration or the attitude of the vehicle.Unfortunately,the lateral acceleration is more useful for sideslip rather than rollover,and the attitude is a kind of posterior way,which means it is hard to take measures to cope with the rollover accident when the attitude exceeds the safety threshold.Considering the movement of the vehicle is totally caused by the wheel force,the rollover could also be predicted by the changing of the wheel force.Therefore,in this paper,we developed a method to analyze the roll stability by the vertical wheel force.A thorough experiment environment is established,and the effectiveness of the proposed method is verified in real driving conditions.

Path Planning Based on the Improved RRT^(∗) Algorithm for the Mining Truck

Planning a reasonable driving path for trucks in mining areas is a key point to improve mining efficiency.In this paper,a path planning method based on Rapidly-exploring Random Tree Star(RRT∗)is proposed,and several optimizations are carried out in the algorithm.Firstly,the selection process of growth target points is optimized.Secondly,the process of selecting the parent node is optimized and a Dubins curve is used to constraint it.Then,the expansion process from tree node to random point is optimized by the gravitational repulsion field method and dynamic step method.In the obstacle detection process,Dubins curve constraint is used,and the bidirectional RRT∗algorithm is adopted to speed up the iteration of the algorithm.After that,the obtained paths are smoothed by using the greedy algorithm and cubic B-spline interpolation.In addition,to verify the superiority and correctness of the algorithm,an unmanned mining vehicle kinematic model in the form of frontwheel steering is developed based on the Ackermann steering principle and simulated for CoppeliaSim.In the simulation,the Stanley algorithm is used for path tracking and Reeds-Shepp curve to adjust the final parking attitude of the truck.Finally,the experimental comparison shows that the improved bidirectional RRT∗algorithm performs well in the simulation experiment,and outperforms the common RRT∗algorithm in various aspects.