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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.

Vehicle speed is an important factor to driving safety, which is directly related to the stability and braking performance of the vehicle. Besides, the precise measurement of the vehicle speed is the basis of some vehicle active safety systems. Even in the future intelligent transportation, high quality speed information will also play an important role. The commonly used vehicle speed measurement techniques are based on the wheel speed sensors, which are not accurate, especially when the wheels’ slip rate is not equal to zero. Focusing on these issues, image matching technology has been used to measure the vehicle speed in this paper. The image information of the road in the front of the vehicle is collected, and the pixel displacement of the vehicle is calculated by the matching system, thus accurately vehicle speed can be obtained. Compared with conventional speed measure technology, it has the advantages of wide measuring range, and high accuracy.

The brake performance is one of the most important performances in the automotive active safety, and it is the main measure of automotive active safety. Thus, to develop a platform for the braking system is quite significant. Based on the object-oriented technology, the platform for braking system is developed by making use of Visual C++ 6.0 development tool. By using the VC++ development tool and doing secondary development on other softwares, the software possesses powerful features, such as brake plan selection, performance calculation, parametric modeling, finite element analysis and kinematics simulation, etc. An initial brake system can be designed, calculated and analyzed all in one. The living instance shows that the platform has friendly user interfaces, powerful functions and it can improve the precision and efficiency of brake design. The platform has been of great applied value and can also positively promote the design automation of vehicle's braking system.

In summer, when vehicle parks in direct sunlight, the closed cabin temperature would rise sharply, which affects the occupants step-in-car comfort Solar powered vehicle parking ventilation system adopts the solar energy to drive the original ventilator. Thus, the cabin temperature could be dramatically decreased and the riding comfort could be also improved. This research analyzed the modified crew cabin thermal transfer model. Then the performance of the solar powered ventilation system is analyzed and optimized combined with the power supply characteristics of the photovoltaic element. The storage and reuse of the solar power is achieved on condition that the cabin temperature could be steadily controlled. The research shows that, the internal temperature is mainly affected by the solar radiation intensity and the environment temperature.

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.

The development of electrification is widely considered to be the key to the transportation industry. In recent years, the number of electric trucks on the road is increasing year by year, so the safety of electric trucks is of great importance. At present, the batteries of electric trucks are mostly arranged on the two sides of the trucks. The protective devices are only the guardrails fixed on the vehicle body, so the protective effect is poor. In view of this situation, this paper designed a battery protection device for electric truck. When the truck is hit in a side collision, the transverse guardrail first generates plastic deformation and absorbs kinetic energy. At this time, the collision force is transmitted to the energy-absorbing box along the moving direction of the side collision vehicle, and the energy-absorbing box is contracted to produce a buffer effect.

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.

Studies show that driving in foggy environment is a security risk, and when driving in foggy environment, the drivers are easy to accelerate unconsciously. The safety information prompted to the driver is mainly from fog lights, road warning signs and the traffic radio. In order to increase the quality of the safety tips to prevent drivers from unintended acceleration and ensure the security of driving in foggy environment, the study proposes a safety speed assessment method for driving in foggy environment, combining the information of driving environment, vehicle’s speed and the multimedia system. The method uses camera which is installed on the front windshield pillar to collect the image about the environment, and uses the dark channel prior theory to calculate the visibility. And by using the environment visibility, the safety speed can be calculated based on the kinematics theory. And it is appropriate for vehicles which have different braking performance.

As an important input parameter of intelligent vehicle active safety technology, road adhesion coefficient is of great significance in autonomous collision avoidance, emergency braking and collision avoidance, and variable adhesion road motion control. Traditional recognition methods based on vehicle dynamics require large data volume and low solution accuracy. This paper proposes an adhesion coefficient recognition method based on Elman neural network and Kalman filter. By establishing a seven-degree-of-freedom vehicle dynamics model, dynamic parameters such as yaw angular velocity, longitudinal velocity, lateral velocity, and angular velocity of each wheel, which are easy to measure and strongly related to the road adhesion coefficient, are analyzed as the input of the neural network model.

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.

Dangerous driving behavior will cause serious traffic accidents, which will not only threaten life and property but also cause traffic congestion and reduce road capacity. Speed detection is an important detection method to identify whether a driver is driving dangerously. Traditional speed detection methods need additional sensors, which will increase the cost of speed measurement. This paper proposes a vehicle speed estimation algorithm based on the imaginary projection plane (IPP). The IPP will be established according to the height, field angle, and vertical tilt angle of the camera and will be used to establish the mapping relationship between the world coordinates and image coordinates of the vehicle. By combining YOLOv4 and DeepSORT, the vehicle license plate is detected and tracked, and the center point of the vehicle license plate is taken as the feature point of vehicle speed estimation. The vehicle speed is estimated according to the IPP.

The phenomenon of liquid transfer in the liquid tank of the semi-trailer vehicle for transporting dangerous cargo (SVTDC) during braking is analyzed and the relevant mathematical model is established. The braking dynamic model of the SVTDC considering the liquid sloshing in the tank is established, and the model is verified based on the co-simulation method. Based on the typical conditions, the braking deceleration and axle load calculation functions of the model are simulated and analyzed, and the application prospect of the model in the development of driving automation control strategy is discussed.

Driving comfort is one of the most important indexes for automobile comfort. Driving posture comfort is closely related to the drivers' joint angles and joint torques. In present research, a new method is proposed to identify the most comfortable driving posture based on studying the relation between drivers' joint angles and joint torques. In order to truly reflect a driving situation, the accurate human driving model of 50 percent of the size of Chinese male is established according to the human body database of RAMSIS firstly. Biomechanical model based on accurate human driving model is also developed to analyze and obtain dynamic equations of human driving model by employing Kane method. The joint torque-angle curves of drivers' upper and lower limbs during holding wheel or pedal operation can be obtained through dynamic simulation in the MATLAB. Through curve-fitting analysis, the minimum joint torque of a driver' limb and the optimal joint angel can be found.

The active sound generation systems (ASGS) for electric vehicles (EVs) play an important role in improving sound perception and transmission in the car, and can meet the needs of different user groups for driving and riding experiences. The active sound synthesis algorithm is the core part of ASGS. This paper uses an efficient variable-range fast linear interpolation method to design a frequency-shifted and pitch-modified sound synthesis algorithm. By obtaining the operating parameters of EVs, such as vehicle speed, motor speed, pedal opening, etc., the original sound signal is interpolated to varying degrees to change the frequency of the sound signal, and then the amplitude of the sound signal is determined according to different driving states. This simulates an effect similar to the sound of a traditional car engine. Then, a dynamic superposition strategy is proposed based on the Hann window function.

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.

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.

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.

For the thin ice on the road in winter, the traditional road deicing vehicle relies on mechanical and chemical methods for melting ice, which is inclined to damage the pavement and has insidious influence on environment. The thermal deicing vehicle has been adopted in recent years. Although the deicing method is available, the deicing efficiency is unacceptable while the energy consumption is huge. The study adopts the new idea of “bottom-to-top” for melting the intersection area between the road surface and the bottom ice layer by the microwave heating firstly and then cleaning them out using high pres. vapor cutting so as to save the cost of energy and enhance the traffic safety. First of all, the mathematical model of the melting process of the intersection of the pavement and the ice layer was established according to the microwave heating characteristics.

With the rapidly developing automotive industry and stricter environmental protection laws and regulations, lightweight materials, advanced manufacturing processes and structural optimization methods are widely used in body design. Therefore, in order to evaluate and improve the pedestrian protection during a collision, this paper presents an impact simulation modeling and structural optimization method for a sport utility vehicle engine hood made of carbon fiber reinforced plastic (CFRP). Head injury criterion (HIC) was used to evaluate the performance of the hood in this regard. The inner panel and the outer panel of CFRP hood were discretized by shell elements in LS_DYNA. The Mat54-55 card was used to define the mechanical properties of the CFRP hood. In order to reduce the computational costs, just the parts contacted with the hood were modeled. The simulations were done in the prescribed 30 impact points.

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.