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Accurately predicting the future trajectories of surrounding traffic agents is important for ensuring the safety of autonomous vehicles. To address the scenario of frequent interactions among traffic agents in the highway merging area, this paper proposes a trajectory prediction method based on interactive graph attention mechanism. Our approach integrates an interactive graph model to capture the complex interactions among traffic agents as well as the interactions between these agents and the contextual map of the highway merging area. By leveraging this interactive graph model, we establish an agent-agent interactive graph and an agent-map interactive graph. Moreover, we employ Graph Attention Network (GAT) to extract spatial interactions among trajectories, enhancing our predictions. To capture temporal dependencies within trajectories, we employ a Transformer-based multi-head self-attention mechanism.

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.

According to the requirements of high transmission ratio and high load torque of high-speed electric drive axle planetary gear system, the design and analysis of fine-pitch planetary gear system with small modulus, small pressure angle and high full tooth height of are carried out. In order to improve the bearing capacity of gear and reduce gear meshing noise, the tooth profile modification parameters of gear system are optimized. In this paper, the tooth modification methods are analyzed and the gear train parameters are determined. The influence degree of different tooth modification methods on the transmission performance of the gear train is determined by orthogonal experiment method. The transmission error is reduced, the stress fluctuation is improved, and the gear meshing performance is greatly improved by adopting the appropriate modification scheme, which proves the effectiveness of the tooth modification scheme.

Road traffic congestion sometimes happens at tunnel exit even without high traffic flow. One reason is that the deceleration process is imperceptible when the vehicle is driving to the tunnel exit with gradual upgrade slopes. Nowadays regulations are more concentrated in transport sectors, and control measures are applied to vehicles through the tunnel. This process is careless of vehicles’ specific characteristics and easily distract the driver attention. In this paper, a tunnel climbing acceleration reminder system is introduced. When the speed drop is detected and the analysis show this is due to the driver's unconscious behavior, the system will remind the driver to speed up. Based on the dynamic model and the tunnel properties, the relationship between the throttle opening degrees and the duration with the speed change is studied. Then, the engine braking is considered for the variation of speeds and slopes.

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.

When vehicle traveling on the bumpy road or vehicle acceleration and deceleration, which will cause the body vibration of vehicle, at the same time, a large part of energy would be absorbed by the shock absorber transforms the mechanical energy into heat energy dissipated. In order to recycle the energy of vibration and keep the stability of running car, this paper provides the shock absorber of energy recovery that recycling the energy dissipated from the traditional absorber. The shock absorber includes rod and rodless chamber cavity, the two parts contain oil outlet and oil inlet, which connected to a bridge type loop of hydraulic to make pulsating oil pressure towards one direction, when the shock absorber vibration causes pulsating oil pressure, it drives hydraulic pump operation. Because the output shaft of the hydraulic pump fixedly attached to the input shaft of generator, so the generator produces electricity for recycling energy[1].

Automotive Front Lighting System(AFS) can receive the steering signal and the vehicular speed signal to adjust the position of headlamps automatically. AFS will provide drivers more information of front road to protect drivers safe when driving at night. AFS works when there is a steering signal input. However, drivers often need the front road's information before they turn the steering wheel when vehicles are going to go through a sharp corner, AFS will not work in such a situation. This paper studied how to optimize the working time of AFS based on GIS (Geographic Information System) and GPS(Geographic Information System) to solve the problem. This paper analyzed the process of the vehicle is about to go through a corner. Low beams and high beams were discussed respectively.

With the development of the Internet for vehicles, the Car-sharing has been developed rapidly in recent years. This paper focuses on the network programming and distribution for Car-sharing, which helps to clarify the characteristics and basic law of Car-sharing network development, as well as the main approaches to construct it. Firstly, by analyzing the effect factors and expanding ways of Car-sharing network, characteristics of the development of Car-sharing industry and its network, as well as main Car-sharing users and services, the influence factors of Car-sharing demand and the main demand points in a city are summarized. Secondly, in order to better evaluate the network programming and distribution for Car-sharing, this paper proposes an optimization decision method of the car-sharing network planning by evaluating the possible alternatives in a same scale. The assessment index of Car-sharing network planning is constructed.

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.

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.

Nowadays, off-highway vehicles enjoyed a significant status in the national defense and civil construction. There is no doubt that the working conditions of off-highways are quite different from the conventional passenger cars, hence, their suspensions are particularly designed. Since the hydro-pneumatic suspension technology is maturely applied in engineering machinery, this paper presents a concept for a novel energy-harvesting device, which is applied in off-highway vehicles based on hydro-pneumatic suspension, namely, electro-hydraulic energy-harvesting suspension (EHEHS). The EHEHS took the fundamental of mechanism-electronic-hydraulic system, which consisted the following elements: a cylinder, 2 check valves, a hydro-pneumatic spring, a hydraulic motor, a DC motor, a processing circuit and a battery. In the EHEHS system, the cylinder is used to transmit the vibration energy into hydraulic energy, which is stored in hydro-pneumatic spring.

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.

Mountain road winding and bumpy, traffic accidents caused by speeding frequently happened, mainly concentrated on curves. The present curve warning system research are based on Charge-coupled Device, but the existing obstacles, weather , driving at night and road conditions directly affect the accuracy and applicability. The research is of predictability to identify the curves based on the geographic information and can told the driver road information and safety speed ahead of the road according to the commercial vehicle characteristic of load, and the characteristics of the mass center to reduce the incidence of accidents. In this paper, the main research contents include: to estimate forward bend curvature through the node classification method based on the digital map.

Path tracking is one of the critical technologies in the autonomous vehicle. Its performance may be seriously affected by disturbance resulting from unpredictable environment like changes in road friction coefficient and parameter uncertainty such as cornering stiffness and mass caused by errors of measurement. Besides, since the vehicle system consisting of many systems is an extremely complex nonlinear system, it is almost impossible for us to establish a precise model of a vehicle especially when it is moving. These inevitable factors influence the control accuracy and even threaten the stability and safety of the vehicle system. This paper proposed a promising solution to this problem, robust MPC (Model Predictive Control) combined with the optimal preview controller for path tracking problems of an autonomous vehicle. The state space model in tracking error variables of a passenger vehicle used for path tracking application is established.

Signage recognition is one of the hot topics in recent years. It has important applications in intelligent traffic and autonomous driving of smart cars. This paper designs a road marking recognition method combining OPSA point set distance and wavelet transform. The method consists of three main phases: 1) image denoising, restoration, 2) feature extraction, and 3) image recognition. First, a Gaussian-smoothing filter used to attenuate or remove irrelevant information in the image, enhance related information in the image, and achieve image denoising. In the feature extraction stage, the feature extraction and recognition method based on wavelet transform adopted to overcome the deficiency of the traditional Fourier feature extraction method, ensure that high frequency information is not lost, and low frequency information is not lost. Finally, the OSPA point set used to identify distance markers.

The technology of active sound generation (ASG) for automobiles is one of the most effective methods to flexibly achieve the sound design that meets the expectations of different user groups, and the active sound synthesis algorithms are crucial for the implementation of ASG. In this paper, the Kaiser window function-based the harmonic synthesis algorithm of automobile sound is proposed to achieve the extraction of the order sounds of target automobile. And, the suitable fitting functions are utilized to construct the mathematical model between the engine speed information and the amplitude of the different order sound. Then, a random phase correction algorithm is proposed to ensure the coherence of the synthesized sounds. Finally, the analysis of simulation results verifies that the established method of the extraction and synthesis of order sound can meet the requirements of target sound quality.

The sweeping vehicle has made a great contribution to the cleaning of urban roads. The traditional electric sweeping vehicle uses the main and auxiliary motors to drive the driving system and the operating system respectively. However, because the sweeper is in a low-speed working condition for a long time, and the drive motor must meet the demand for high power, there exist problems of low motor utilization and high cost. Aiming at this phenomenon, a dual-motor power coupling system based on planetary gears is proposed. First, analyze the driving mode of the dual-motor coupling power system according to the actual working scheme of the sweeper, and match the parameters of the motor based on this. Second, on the premise of meeting the power requirements, analyze and divide the working range of each drive mode based on the principle of minimum energy consumption, and then obtain the best drive mode switching control and speed and torque distribution strategy.

The ride performance and stability of the vehicle will decrease while the vehicle passing a deceleration bump with relatively high speed. If the speed is too low, the road efficiency and ride comfort will be affected. It is essential to identify the proper speed taking into account all the factors. In this paper, the dynamic model of the vehicle passing through the deceleration bump is established. Three kinds of indicators vibration weighted acceleration RMS, maximum vertical vibration acceleration and wheel load impact coefficient, are used to comprehensively evaluate the ride comfort and safety. The highway model, vehicle model, and common trapezoidal cross-sections bump models are set up in Carsim. Parameters such as vertical acceleration and tire force at different vehicle speeds are obtained. Then use the spline interpolation method to fit the data, and comprehensively consider the three indicators to get the best speed.