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The retarder is an important auxiliary braking device of heavy vehicles. However, the stirring air in the working wheels of the idle retarder would cause the transmission loss when the vehicle is traveling in non-braking state [1]. For certain driving conditions, the air-friction characteristics in the working wheels of the idle retarder are analyzed first. Then the relationship between the air density and the torque produced by stirring air is studied. The thermal characteristics of the retarder in the idle condition are also concerned according to the energy flow and heat transfer. Meanwhile, the increased transmission loss caused by the rising temperature of the stirring air and its inference on the transmission stability are also studied. Finally, the optimal range of air vacuum degrees in the working wheel of the idle retarder is determined and the evaluations for the air-friction and the heat transfer characteristics are given for the vacuum degrees.

With the rapid development of the logistics and transportation industry, heavy-duty trucks play an increasingly important role in social life. However, due to the characteristics of large cargo loads, high center of mass and relatively narrow wheelbase, the driving stability of heavy trucks are poor, and it is easy to cause rollover accidents under high-speed driving conditions, large angle steering and emergency obstacle avoidance. To improve the roll stability of heavy trucks, it is necessary to design an active anti-rollover control system, through the analysis of the yaw rate and the load transfer rate of the vehicle, driving states can be estimated during the driving process. Under the intervention of the control system, the lateral transfer rate of heavy trucks can be reduced to correct the driving posture of the vehicle body and reduce the possibility of rollover accidents.

Path planning system, which is one of driver assistance systems, can calculate the driving paths and estimate the driving time through the road information provided by information source. Traditional path planning systems calculate the driving paths through Dijsktra's algorithm or A* algorithm but only consider the road information from electronic maps. It is not safe enough for operating vehicles because of the insufficient information of vehicle performance as well as the driver's willingness. This study is based on the Dijsktra's algorithm, which comprehensively considered vehicular active safety constraints such as road information, vehicle performance and the driver's willingness to optimize the Dijsktra's algorithm. Then the path planning system can calculate the optimal driving paths that would satisfy the safety requirement of the vehicle. This study used LabVIEW as a visual host computer and MATLAB to calculate dynamic property of the vehicle.

The heavy-duty vehicles have large transportation capacity. Gross mass and center of gravity position of the heavy-duty vehicles vary with the cargo mass and the driving condition, which affect driving safety and handling stability. Gross mass and center of gravity position of the vehicles are usually measured on fixed test platform, and the vehicles are stationary or pass the platform slowly in the measurement process. Most dynamic weighing system could not measure the center of gravity position of the vehicles. On-board mass and center of gravity of motor vehicles measurement system mainly based on the tire pressure information could measure gross mass and center of gravity position accurately in the driving process. The measurement errors of the sensors are effectively decreased by filtering collected sensor data. The relationship between the tire pressure and the tire load is built when the vehicle is stationary.

The mountainous roads are rugged and complex, so that the driver can not make accurate judgments on dangerous road conditions. In addition, most heavy vehicles have characteristics of large weight and high center of gravity. The two factors above have caused most of the car accidents in mountain areas. A research shows that 90% of car accidents can be avoided if drivers can respond within 2-3 seconds before the accidents happen. This paper proposes a speed warning scheme for heavy-duty vehicle over the horizon in mountainous area, which can give the drivers enough time to respond to the danger. In the early warning aspect, this system combines the front road information, the vehicle characteristics and real-time information obtained from the vehicle, calculates and forecasts the danger that may happen over the horizon ahead of time, and prompts the driver to control the vehicle speed.

In the intelligent speed planning system, real-time estimation of road slope is the key to calculate slope resistance and realize the vehicles’ active safety control. However, if the road slope is measured by the sensor while the commercial vehicle is driving, the vibration of the vehicle body will affect its measurement accuracy. Therefore, the relevant algorithm is used to estimate the real-time slope of the road when the commercial vehicle is driving. At present, many domestic and foreign scholars have analyzed and tested the estimation of road slope by the least square method or Kalman filter algorithm. Although the two methods both can achieve the estimation, the real-time performance and accuracy still need to be improved. In this paper, for traditional fuel commercial vehicle, the Kalman filter algorithm based on the kinematics and the extended Kalman filter algorithm based on the longitudinal dynamics are respectively used to estimate the road slope.

When dump trucks unload dusty materials, dust particles with a diameter of 1 to 75 microns slide out of the dump body and float into the air. Dust particles naturally settle down spending a few hours, which causes air pollution. People who work in this environment daily suffer serious physical harm. To study the movement of dust particles during the unloading process, a scaled-down model is used to simulate the process of dump truck unloading gravel, and a high frame rate camera is used to record the movement trajectory of dust particles during the unloading process. In this paper, by observing the movement process of unloading dust particles by dump trucks, based on the principle of dynamics, a mathematical model describing the unloading of dust particles in the dump body and a mathematical model of the diffusion of dust particles in the air are established. Take the small gravel sampled at the construction site as an example of the experiment.

The sweeper vehicle plays a very key role in maintaining the urban environment. If the sweeper vehicle can accurately and efficiently identify and classify the ground garbage in the working process, it can greatly improve the working efficiency of the sweeper vehicle and reduce the consumption of manpower. Although the deep learning algorithm based on DUC and PSPNet has high accuracy, the recognition speed is low. ENet is a lightweight network, which greatly improves efficiency, but significantly sacrifices accuracy. This paper presents an improved real-time detection lightweight network based on PSPNet, which takes into account the operation speed and accuracy. The network takes PSPNet as the backbone network, and increases the stride in the convolution process, to reduce the size of the feature map and reduce the amount of calculation.

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.

With the continuous increasing requirements of commercial vehicle weight and speed on highway transportation, conventional friction brake is difficult to meet the braking performance. To ensure the driving safety of the vehicle in the hilly region, the eddy current retarder (ECR) has been widely used due to its fast response, lower prices and convenient installation. ECR brakes the vehicle through the electromagnetic force generated by the current, and converted vehicle mechanical energy into heat through magnetic field. Air cooling structure is often used in the traditional ECR and cooling performance is limited, which causes low braking torque, thermal recession, and low reliability and so on. The water jacket has been equipped outside the eddy current region in this study, and the electric ECR is cooled through the water circulating in the circuit, which prolongs its working time.

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.

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.

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.