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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.

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.

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.

Vacuum cleaning vehicle is the necessary equipment for the Municipal Sanitation Department to keep the road surface clean and the dust subsidence system is the heart unit for the proper function of the cleaning vehicle. The reasonable design of this system could increase the load capacity of the vehicle and be convenient for the garbage collecting and dumping. Meanwhile, the engine power could be relatively reduced and the influence on the environment duo to the dusty air in the outlet could be also effectively improved. In the study, the gravity dedusting principle is used firstly for structure design to reduce the flow rate of dust particles inside the lower part of the dust subsidence system. The ruleless collision loss among dust particles is reduced and thereby the fan power is saved. By means of a reasonable separated chamber design and the use of inertia baffle, the sort management for dust particles is developed and the work stress of the export filter is released observably.

Vehicle exhaust waste-heat recovery with thermoelectric power generators can improve energy efficiency, as well as vehicle fuel economy. In the conventional structure, the hot-end of thermoelectric module is directly connected with the outer wall of the exhaust pipe, while the cold-end is connected with the water pipe’s outer wall of the vehicle engine cooling cycle. However, the variety of vehicle engine operating conditions leads to the instability of the hot-end temperature, which will reduce the generating efficiency of the thermoelectric modules and also shorten its service life. This research is on the basis of constructing a heat transfer oil circulation, and to study the action principles and implementation methods of it.

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.

While the car ownership increasing all over the world, the unutilized thermal energy in automobile exhaust system is gradually being realized and valued by researchers around the world for better driving energy efficiency. For the unexpected urban traffic, the frequent start and stop processes as well as the acceleration and deceleration lead to the temperature fluctuation of the exhaust gas, which means the unstable hot-end temperature of the thermoelectric module generator (TEG). By arranging the heat conduction oil circulation at the hot end, the hot-end temperature’s fluctuation of the TEG can be effectively reduced, at the expense of larger system size and additional energy supply for the circulation. This research improves the TEG hot-end temperature stability by installing solid heat capacity material(SHCM) to the area between the outer wall of the exhaust pipe and the TEG, which has the merits of simple structure, none energy consumption and light weight.

The hydraulic retarder is an auxiliary braking device generally equipped on commercial vehicles. Its oil temperature change influences the brake performance of hydraulic retarder. The Organic Rankine Cycle (ORC) is a good means to recover exhausted heat. Moreover, it can cool oil and stably control oil temperature with the help of heat absorption related with evaporation. Comprehensively considering the heat-producing characteristics of hydraulic retarder and the temperature control demand, the aimed boundary conditions are determined. Also the changing rules about the working medium flow rate are obtained. In this work, the heat-producing properties of hydraulic retarder under different conditions and the oil external circulating performance is firstly analyzed. By researching the system’s adaptation to the limiting conditions, the aimed temperature to control is prescribed.

It’s not easy to start the engine in winter, especially in frigid highlands, because the low temperature increases the fuel’s viscosity, decreasing the lubricating oil flow ability and the storage performance of battery. Current electrical heating method can improve the engine starting performance in low temperature condition, but this method adds an external power to the engine, leading to the engine cannot maintain an efficient energy utilization. A warming device using the solar energy is designed to conserve the energy during the daytime, and directly warm up the engine at the time when the engine turns off for a long time, especially during the night. A solar collector installed on the top of the vehicle is used to convert the solar energy to the thermal energy, which is then transferred to the heat accumulator that contain the phase-change medium which can increase the heat storage performance.

The automobile exhaust energy can be recovered by the thermoelectric module generator(TEG). Owing to the complex urban traffic, the exhaust gas’s temperature fluctuations are resulted, which means the unstable hot-end temperature of the TEG. By installing solid heat capacity material(SHCM) to the area between the outer wall of the exhaust pipe and the TEG, it is possible to appropriately reduce the temperature fluctuation, but there is still a fluctuation of the TEG’s power output. Then by adding voltage filter circuit (VFC) after the TEG, the power output stability can be improved. This research uses SHCM and VFC to improve the stability of the exhaust gas generation. Firstly, the three-dimensional heat transfer model of the exhaust pipe thermoelectric power generation system is established. The heat capacity materials with low thermal resistance and high heat capacity were selected as the research object based on previous research.

The hydraulic retarder is an important auxiliary braking device for the heavy vehicle, which has some characteristics, such as the big brake torque and long duration braking, when the vehicle is traveling in braking state. However, the transmission power loss will be produced when the vehicle is traveling in non-braking state. This transmission power loss is called Air-friction. Firstly, the air flow distribution characteristics of retarder cavity are studied by computational fluid mechanics, and the Air-friction characteristic in different conditions is analyzed. Then, according to the Air-friction characteristics for the condition of different filling density, a set of vacuum air loss reduction system is designed. Meanwhile, the test bench for retarder Air-friction is set up, the test data of the revolution speed, pressure in cavity and air loss resistance is obtained according to the test bench for hydraulic retarder.

The cooling system with two fans is generally driven by electrical motors in the small cars. Compared with the traditional cars, heavy duty trucks have the larger heat dissipation power of cooling system. The motors power consumption of dual fans will be larger and the two electrical motors will occupy a large space in the engine cabin. Hydrostatic drive refers to the cooling fan is driven by hydraulic motor, but it has the low transmission efficiency. According to the engine water temperature value and the actual working status of the hydraulic system, the actual speed of cooling fan can be controlled by the computer, which guarantees the normal working water temperature of the engine. Hydrostatic drive is generally applied to heavy vehicles, engineering machinery and excavators as driving source of cooling fan which contains the advantages of large output power, overload protection, continuous speed regulation and flexible space arrangements.

Head-up Display (HUD) system can avoid drivers’ distraction on dashboard and effectively reduce collisions caused by emergency events, which is gradually being realized by researchers around the world. However, the current HUD only displays information like speed, fuel consumption, other information like acceleration and braking can’t be displayed yet. This research will use the indicator symbol‘s color and position change to remind drivers to brake or accelerate. Drivers can do driving operation timely and accurately. The system has the advantages of safety, intuition and real-time. The vehicle safe speed is calculated according to the road parameters, like adhesion coefficient and slope, and vehicle parameters, such as vehicle mass and centroid. Then, the appropriate braking operations are obtained by combining the vehicle driving state. The braking information is corresponded to the color and position change of the indicator symbol to prompt the drivers by the HUD interface.

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 order to meet the Euro IV HD diesel engine emission standard legislation limits, an efficient SCR system is adopted for PM optimized YC6L350-40 HD diesel engine serving in China. This paper presents tests made on the engine. The engine had base NOx emission of 8.8g/kwh over the ESC and 8.7g/kwh over the ETC. Outfitted with a 24.7 liter 300cpsi SCR catalyst, the engine NOx emission dropped to 3.2g/kwh over the ESC and 3.5g/kwh over the ETC.

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.