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Downhill mountain roads are the accident prone sections because of their complexity and variety. Drivers rely more on driving experience and it is very easy to cause traffic accidents due to the negligence or the judgment failure. Traditional active safety systems, such as ABS, having subjecting to the driver's visual feedback, can’t fully guarantee the downhill driving safety in complex terrain environments. To enhance the safety of vehicles in the downhill, this study combines the characteristics of vehicle dynamics and the geographic information. Thus, through which the drivers could obtain the safety speed specified for his/her vehicle in the given downhill terrains and operate in advance to reduce traffic accidents due to driver's judgment failure and avoid the brake overheating and enhance the safety of vehicles in the downhill.

Autonomous driving technology represents a significant direction for future transportation, encompassing four key aspects: perception, planning, decision-making, and control. Among these aspects, vehicle trajectory planning and control are crucial for achieving safe and efficient autonomous driving. This paper introduces a Combined Model Predictive Control algorithm aimed at ensuring collision-free and comfortable driving while adhering to appropriate lane trajectories. Due to the algorithm is divided into two layers, it is also called the Bi-Level Model Predictive Control algorithm (BLMPC). The BLMPC algorithm comprises two layers. The upper-level trajectory planner, to reduce planning time, employs a point mass model that neglects the vehicle's physical dimensions as the planning model. Additionally, obstacle avoidance cost functions are integrated into the planning process.

In the process of truck overload and over-limit detection, it is necessary to detect the characteristics of the vehicle's size, type, and wheel number. In addition, in some vehicle vision-based load recognition systems, the vehicle load can be calculated by detecting the vibration frequency of specific parts of the vehicle or the change in the length of the suspension during the vehicle's forward process. Therefore, it is essential to quickly and accurately identify vehicle features through the camera. This paper proposes a vehicle feature recognition method based on image semantic segmentation and Python, which can identify the length, height, number of wheels and vibration frequency at specific parts of the vehicle based on the vehicle driving video captured by the roadside camera.

The development of intelligent transportation improves road efficiency, reduces automobile energy consumption, and improves driving safety. The core of intelligent transportation is the two-way information interaction between vehicles and the road environment. At present, road environmental information can flow to the vehicle, while the vehicle’s information rarely flows to the outside world. The electronic throttle and electronic braking systems of some vehicles use sensors to get the state of the accelerator and brake pedal, which can be transmitted to the outside environment through technologies such as the Internet of Vehicles. But the Internet of Vehicles technology has not been widely used, and it relies on signal sources, which is a passive way of information acquisition. In this paper, an active identification method is proposed to get the vehicle pedal on-off state as well as the driver’s operation behavior through existing traffic facilities.

Good heat dissipation of Lithium battery can prevent the battery from shortening its life due to rapid aging or thermal runaway. In this paper, an air-cooled structure of 5 series and 3 parallel battery packs is designed, which combines the advantages of series and parallel air ducts and optimizes the heat dissipation effect and the space ratio of air ducts. First, the heat generation model of NCR18650PF lithium battery is established, and the heat generation rate and time under different discharge rates are calculated. Combined with the working conditions of the battery itself, the necessity of battery pack heat dissipation was found.

Glass lifter is a key part of automobile door system. Guide rail is the carrier of glass lifter, and it bears various load cases when glass lifer works. Mass, stiffness and natural frequencies are the factors that influence the performance of glass lifter. In order to design a lighter and reasonable glass lifter, topology optimization methods are studied in this paper. In a rope-wheel glass lifter, design domain is determined by the mechanical structure and working conditions. Firstly, the single target continuum structure topology optimization mathematic models of guide rail are built in this paper, and analysis of multi-stiffness topology optimization are carried out accordingly in which volume fraction is set as 0.4, 0.5 and 0.6. These models are based on SIMP (Solid Isotropic Material with Penalization) theory.

The hydraulic retarder, which is an auxiliary brake device for enhancing traffic safety, has been widely used in kinds of heavy commercial vehicles. When the vehicle equipped with the retarder is traveling in non-braking state, the transmission loss would be caused because of the stirring air between working wheels of the rotor and the stator no matter if the retarder connects in parallel or in series with the transmission [1]. This paper introduces an elaborate hydraulic retarder air-friction reduction system (AFRS) which consists of a vacuum generating module and pneumatic control module. AFRS works to reduce the air friction by decreasing the gas density between working wheels when the retarder is in non-braking state. The pneumatic control model of hydraulic retarder is built first. Then various driving conditions are considered to verify the performance of the AFRS. The stability of the AFRS is analyzed based on the complete driveline model.

According to the resonant pavement crusher's work principle, its front frame mounted with the resonance system must meet the needs of the structural requirements. To satisfy the strength and stiffness requirement and avoid the resonance, the natural frequency of the front frame should be designed away from the crusher's working frequency. In this paper, the author builds a finite element model of the front frame and analyses its modal. According to the modal analysis results, the fourth modal frequency is close to the working frequency of the crusher. So the front frame should be optimized. In the finite element model, the front frame has been divided into a number of components of shell elements. Through optimal Latin hypercube experimental design, the author analyses the different component thickness's relationship of the frequencies of the front frame. The components with higher correlation coefficient have been chosen as the variables of optimization.

The mountain roads are curved and complicated, with undulating terrain and large distance between charging stations. Compared with traditional powered vehicles, in addition to safety issues, pure electric vehicles also need to deal with the driving range issue. At present, the relevant researches on automobile driving in mountainous areas mainly focus on the driving safety of traditional fuel oil vehicles when going uphill and downhill, while there are few researches on the driving planning of pure electric commercial vehicles on curved slope road. This paper presents a speed planning method for pure electric commercial vehicles based on vehicle-road collaboration technology. First, establish the vehicle dynamics model, analyze the vehicle dynamics characteristics when passing the downhill curve, calculate the safe speed range of the vehicle when passing the downhill curve, and establish the safe speed model of the downhill curve.

With the development of economy, the road cleaning faces great challenges because the road area keeps increasing and the road types tend to be diversified. Cleaning vehicle is widely used in road surface cleaning, but it is more and more difficult to meet the demand of road surface cleaning only through using a single road surface cleaning method. If the way of manual adjustment of cleaning parameters is adopted, the driver is required to have rich experience. At present, there is an urgent need for a cleaning vehicle that can autonomously adjust cleaning parameters according to the road surface. This study is based on road recognition technology. After the pavement category is reflected by the visual sensor feedback information and the pavement adhesion coefficient, the parameters of the cleaning vehicle are adjusted by the controller to adapt to different roads.

In this paper, we propose a method of dynamics simulation and analysis based on superelement modeling to increase the efficiency of dynamics simulation for vehicle body structure. Using this method, a certain multi-purpose vehicle (MPV) body structure was divided into several subsystems, and the modal parameters and frequency response functions of which were obtained through superelement condensation, residual structure solution, and superelement data restoration. The study shows that compared to the traditional modeling method, the computational time for vehicle body modal analysis can be reduced by 6.9% without reducing accuracy; for the purpose of structural optimization, the computational time can be reduced by 87.7% for frequency response analyses of optimizations; consistency between simulation and testing can be achieved on peak frequency points and general trends for the vibration frequency responses of interior front row floors under accelerating conditions.

H-Bahn ("hanging railway") refers to the suspended, unmanned urban railway transportation system. Through the reasonable platform layout, H-Bahn can be easily integrated into the existing urban transit system. With the development of urban roads, the associated rail facilities can be conveniently disassembled, moved and expanded. The track beam, circuits, communication equipment, and sound insulation screen are all installed in a box-type track beam so that the system can achieve a high level of integration and intelligence. The carriage of the modern H-banh vehicle is connected with the bogies by two hanging devices. The vehicle is always running in the box-type track beam; therefore there are less possibilities of derailment. Consequently, the key work focuses on the running stability evaluation and curve negotiation performance analysis.

The main objective of platoon control is coordinated motion of autonomous vehicle platooning with small intervehicle spacing while maintaining the same speed and acceleration as the leading vehicle, which can save energy consumption and improve traffic throughput. The conventional platoon control methods are confronted with the problem of manual parameter tuning. In order to addres this isue, a novel bifold platoon control approach leveraging a deep reinforcement learning-based model is proposed, which enables the platoon adapt to the complex traffic environment, and guarantees the safety of platoon. The upper layer controller based on the TD3 tuned PID algorithm outputs the desired acceleration. This integration mitigates the inconvenience of frequent manual parameter tuning asociated with the conventional PID algorithm. The lower layer controller tracks the desired acceleration based on the inverse vehicle dynamics model and feedback control.

Recreational vehicles have a lot of potential consumers in China, especially the type C recreational vehicle is popular among consumers due to its advantages, prompting an increase in the production and sales volumes. The type C vehicle usually has a higher air drag than the common commercial vehicles due to its unique appearance. It can be reduced by optimizing the structural parameters, thus the energy consumed by the vehicle can be decreased. The external flow field of a recreational vehicle is analyzed by establishing its computational fluid dynamic (CFD) model. The characteristic of the RV’s external flow field is identified based on the simulation result. The approximation models of the vehicle roof parameters and air drag and vehicle volume are established by the response surface method (RSM). The vehicle roof parameters are optimized by multi-objective particle swarm optimization (MO-PSO).

Based on the multi-body system, the work research the injury index of the mathematics models of pedestrian, by simulating the motion of the pedestrian impacted by vehicle using MADYMO. Compared with the article published, verify the dependability of this simulated test. Based on the dependability, Carry on sensitivity analysis to design parameter of the automobile. Research on the pedestrian protection by the vehicle by revising the sensitive design parameter. By simulating the pedestrian impacted by the vehicle which installing the hood raise structure, search on the injury index. Compared with the original injury index, we can find that the hood raise structure be propitious to the pedestrian.

There are a large number of curves and slopes in the mountainous areas. Unreasonable acceleration and deceleration in these areas will increase the burden of the brake system and the fuel consumption of the vehicle. The main purpose of this paper is to introduce a speed planning and promotion system for commercial vehicles in mountainous areas. The wind, slope, curve, engine brake, and rolling resistances are analyzed to establish the thermal model of the brake system. Based on the thermal model, the safe speed of the brake system is acquired. The maximum safe speed on the turning section is generated by the vehicle dynamic model. And the economic speed is calculated according to the fuel consumption model. The planning speed is provided based on these models. This system can guide the driver to handle the vehicle speed more reasonably.

This paper presents a novel application of hydraulic electromagnetic energy-regenerative shock absorber (HESA) into commercial vehicle suspension system and vehicle road performance are simulated by the evaluating indexes (e.g. root-mean-square values of vertical acceleration of sprung mass, dynamic tire-ground contact force, suspension deflection and harvested power; maximum values of pitch angle and roll angle). Firstly, the configuration and working principle of HESA are introduced. Then, the damping characteristics of HESA and the seven-degrees-of-freedom vehicle dynamics were modeled respectively before deriving the dynamic characteristics of a vehicle equipped with HESA. The control current is fixed at 7A to match the similar damping effect of traditional damper on the basis of energy conversion method of nonlinear shock absorber.

The current paper proposes a hydraulic interconnected suspension system (HIS) based on a hydraulic energy-regenerative shock absorber (HESA) comparatively with the passive suspensions. The structure and working principles of the HIS system are introduced in order to investigate the damping performance and energy regeneration characteristics of the proposed system. Then, the dynamic characteristics of the HIS-HESA system have been investigated based on a 4-DOF longitudinal half vehicle model. In the simulation, two different road inputs were used in the dynamic characterization of the HIS-HESA; the warp sinusoidal excitation, and the random road signal. In addition, a comparative analysis was provided for the dynamic responses of the half vehicle model for both the HIS-HESA and the conventional suspension. Furthermore, a parametric analysis of the HIS-HESA has been carried out highlining the key parameters that have a remarkable effect on the HIS-HESA performance.

As an off-road racing car, driving conditions for a Baja racing car are particularly complex. Extreme working conditions such as deep pits and rocky roads have put higher demand on structural strength and frame safety. To solve this problem, extreme working conditions are first studied to check the safety of the steel tube frame of Baja racing cars. Secondly, based on Noise, Vibration, and Harshness (NVH) to explore the frame's characteristics, analyze the frame's six-order mode, make the corresponding optimization, and solve the resonance problem caused by engine excitation and other factors. Finally, the natural frequency of the frame is measured to verify the effectiveness of the NVH characteristic optimization results, and it is found that the experimental results match the theoretical values. The theoretical analysis results are mainly based on ANSYS software's static and modal analysis.

The tank truck has a wide range of application. When the liquid in the tank is not fully loaded, the lateral movement of the liquid in the tank will shift the center of gravity of the tank truck and make the vehicle less safe. It is easy to roll over when the tank truck is turning. This study combines the vehicle dynamic characteristics and geographic information, which gives the driver safe speed and safe braking distance tips before turning, to reduce the traffic accidents caused by driver's misjudgment. The dynamic model of the tank truck is established, through collecting the real-time information of the vehicle, the vehicle load and braking torque are calculated by the relevant dynamic model. The system needs to measure the deviation of the center of gravity in the tank truck movement process, and the deviation of the center of gravity has a great influence on the safety speed.