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At present, many electric vehicles are often equipped with only a single-stage final drive. Although the single-stage speed ratio can meet the general driving requirements of electric vehicles, if the requirements of the maximum speed and the requirements for starting acceleration or climbing are met at the same time, the power demand of the drive motor is relatively large, and the efficient area of the drive motor may be far away from the operating area corresponding to daily driving. If the two-speed automatic transmission is adopted, the vehicle can meet the requirements of maximum speed, starting acceleration and climbing at the same time, reduce the power demand of the driving motor, and improve the economy under certain power performance. This is especially important for medium and large vehicles.

The closed cabin temperature is anticipated to be cooled down when it is a bit hot inside the driving car. The traditional air-condition lowers the cabin temperature by frequently switching the status of the compressor, which increases the engine’s parasitic power and shortens the compressor’s service-life. The semiconductor auxiliary cooling system with the properties of no moving parts, high control precision and quick response has the potential to assist the on-board air-condition in modulating the cabin temperature with relative small ranges. Little temperature differences between the cabin and the outside environment means that the system energy consumption to ensure the occupant comfort is relatively low and the inefficiency could be made up by the renewable energy source.

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.

Typical vehicle speed deceleration occurs at the freeway exit due to the driving direction change. Well conducting the driver to control the velocity could enhance the vehicle maneuverability and give drivers more response time when running into potential dangerous conditions. The freeway exit speed limit sign (ESLS) is an effect way to remind the driver to slow down the vehicle. The ESLS visibility is significant to guarantee the driving safety. This research focuses on the color variable ESLS system, which is placed at the same location with the traditional speed limit sign. With this system, the driver could receive the updated speed limit recommendation in advance and without distraction produced by eyes contract change over the dashboard and the front sight. First, the mathematical model of the drivetrain and the engine brake is built for typical motor vehicles. The vehicle braking characteristics with various initial speeds in the deceleration area are studied.

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.

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.

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.

The drivers' hysteretic perception to surrounding environment will affect vehicular fuel economy, especially for the heavy-duty vehicles driving under complex conditions and long distance in mountainous areas. Unreasonable acceleration or deceleration on the slope will increase the fuel consumption. Improving the performance of the engine and the transmission system has limited energy saving potential, and most fuel-efficient driving assistant systems don't consider the road conditions. The main purpose of this research is to introduce an economic driving scheme with consideration of the prestored slope information in which the vehicle speed in mountainous slopes is reasonably planned to guide the driver's behavior for reduction of the fuel consumption. Economic driving optimization algorithm with low space dimension and fast computation speed is established to plan accurate and real-time economic driving scheme.

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.

Using friction brakes for long time can increase easily its temperature and lower vehicle brake performance in the downhill process. The drivers' hysteretic perception to future driving condition could mislead them to stop untimely the engine brake, and some other auxiliary braking devices are designed to increase the brake power for reduction of the friction brake torque. The decompression engine brake has complex structure and high cost, and the application of eddy current retarder or hydraulic retarder on the commercial vehicles is mainly limited to their cost and mass. In this paper, an innovative brake guidance system for commercial vehicles with coordinated friction brakes and engine brake is introduced to guide the drivers to minimize the use of the friction brakes on the downhill with consideration of future driving conditions, which is aimed at releasing the engine brake potential fully and controlling the friction brake temperature in safe range.

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 development of the vehicle quantity and the transportation system accompanies the rise of traffic accidents. Statistics shows that nearly 35-45% traffic accidents are due to drivers’ fatigue. If the driver’s fatigue status could be judged in advance and reminded accurately, the driving safety could be further improved. In this research, the blink frequency and eyes movement information are monitored and the statistical method was used to assess the status of the driving fatigue. The main tasks include locating the edge of the human eyes, obtaining the distance between the upper and lower eyelids for calculating the frequency of the driver's blink. The velocity and position of eyes movement are calculated by detecting the pupils’ movement. The normal eyes movement model is established and the corresponding database is updated constantly by monitoring the driver blink frequency and eyes movement during a certain period of time.

Optimization of the steering trapezoid mechanism parameter has great significance for improving vehicular handling performance and steering safety. The mathematical model of the current trapezoid mechanism design is oversimplified; Thus, the value of the optimum parameter is often not achievable. In this paper, a design model for the trapezoidal steering mechanism is proposed taking into consideration the size and kinematic constraints. Based on combining Ackerman's principle and spatial geometric relation, a multi-body dynamics design method is used to derive a nonlinear optimization model of the split steering trapezoid mechanism. In this investigation, a hybrid genetic algorithm is developed to minimize the steering error and the corresponding optimum design parameters. The selected design parameters are the bottom angle and the steering arm length of steering trapezoid mechanisms.

Road traffic accidents resulting from alcohol-impaired driving are increasing globally despite several measures, currently in place, to curb the trend. For this reason, recent research aims at integrating alcohol early-detection systems and driving simulator experiments to identify intoxicated drivers. However, driving simulator experiments on drunk driving have focused mostly on male participants than female drivers whose characteristics have scarcely been explored. Hence in this paper, vehicle dynamic control inputs on steering, braking, and acceleration performance of 75 licensed female drivers with an upshot of alcohol at four different blood alcohol concentration (BAC) levels (0%, 0.03%, 0.05%, and 0.08%) were investigated. The participants completed simulated driving in a fixed-based simulator experiment coupled with real-time ecological scenarios to extract discrete responses.

Heavy commercial vehicle drivers may frequently shift gears when they are running on long and downhill roads in mountainous area. In order to improve driving safety and fuel economy, it is necessary to predict the slope of the road ahead in real time and correct the driver's shift strategy in time. At present, the road slope estimation is mainly based on the real-time estimation of the road slope at the current position of the vehicle based on the vehicle driving information obtained by the sensors, but the road slope of the road section that the vehicle is about to reach has not been predicted. In this paper, based on the road slope information of the road section that the driver has driven through, combined with Geographic Information System (GIS) information and road design standards, the slope of the road section ahead is predicted.

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.

In new energy vehicles, the electric motor, as the main power source, is developing toward high power density. However, its heat generation problem always affects the overall performance of the motor, so an efficient motor cooling system is especially important. In desert or water-scarce areas, liquid cooling cannot meet the needs of new energy vehicle motor cooling. When glycol or other liquid coolants are low or depleted, motor heat dissipation becomes less effective. Heat pipe is a heat dissipation technology with advantages such as fast thermal response and light weight. In this paper, by improving the heat pipe arrangement and reducing the overall mass of the heat dissipation system, a heat pipe optimization design based on a drive motor heat dissipation scheme is proposed, and the overall stability of the motor working under high temperature conditions is improved.

The articulated steering system is widely used in engineering vehicles due to its high mobility and low steering radius. The design parameters have a vital impact on the selection of the steering system assemblies, such as the operation stroke, pressure, and force of the hydraulic cylinders during the steering process, which will affect the system weight. The system energy consumption is also relevant to the geometry parameters. According to the kinetic analysis of the steering system and dynamic analysis of the steering process, the kinetic model of an engineering vehicle steering system is built, and the length and pressure variation of the cylinder is calculated and validated by the field test. The influence of the factors is analyzed based on the established model. To lower the system weight, needed pressure, and force, the multi-objective particle swarm optimization method is initiated to optimize the geometry parameter of the articulated steering system.

The multi-functional mechanical arm equipped on engineering vehicle can achieve different functions by installing different mechanism devices through the interface at the end of the mechanical arm. It can achieve functions like engineering construction and road rescue. Mechanical arm systems often work in complex environments, which requires good reliability and safety of the boom system. When the mechanical boom is working, the pressure of each luffing cylinder is large, and the contact force and acceleration of each boom are complex, which requires a certain degree of verification and optimization before it can be put into production. In this paper, a virtual prototype of a vehicle mounted hydraulic mechanical arm with four booms is established. Through ADAMS, the dynamic analysis of mechanical arm under multiple working conditions is carried out, the movement parameter changes and the pressure changes of each luffing cylinder are analyzed.

Intelligent sweeper vehicle is gradually applied to human life, in which the accuracy of garbage identification and classification can improve cleaning efficiency and save labor cost. Although Deep Learning has made significant progress in computer vision and the application of semantic network segmentation can improve waste identification rate and classification accuracy. Due to the loss of some spatial information during the convolution process, coupled with the lack of specific datasets for garbage identification, the training of the network and the improvement of recognition and classification accuracy are affected. Based on the Unet algorithm, in this paper we adjust the number of input and output channels in the convolutional layer to improve the speed during the feature extraction part. In addition, manually generated datasets are used to greatly improve the robustness of the model.