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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.

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 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.

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].

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.

Systematic research on dynamic model, simulation analyses, prototype production and bench tests have been carried out in recent years on the most popular energy-harvesting shock absorbers-the mechanical motion rectifier (MMR), and the hydraulic-electromagnetic energy-regenerative shock absorber (HESA). This paper presents a novel application of the HESA into bogie system of railway vehicles. In order to study the differences of suspension performance and energy harvesting property between first suspension system and second suspension system of the application, simulation models are built in AMESim to make comparison studies on the different department suspensions caused by the nonlinear damping behaviors of the HESA. The simulation results show that the system can effectively reduce the impact between wheel and rail tracks, while maintaining good potential to recycle vibratory energy.

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.

This paper presents a novel application of hydraulic electromagnetic energy-regenerative shock absorber (HESA) into commercial vehicle suspension system and vehicle road performance are simulated by the evaluating indexes (e.g. root-mean-square values of vertical acceleration of sprung mass, dynamic tire-ground contact force, suspension deflection and harvested power; maximum values of pitch angle and roll angle). Firstly, the configuration and working principle of HESA are introduced. Then, the damping characteristics of HESA and the seven-degrees-of-freedom vehicle dynamics were modeled respectively before deriving the dynamic characteristics of a vehicle equipped with HESA. The control current is fixed at 7A to match the similar damping effect of traditional damper on the basis of energy conversion method of nonlinear shock absorber.

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.

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.

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.

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.

The anti-roll bar is an important structural component of the automobile, which can effectively prevent the automobile from rolling and improve the safety of the automobile during steering. In the design of the current anti-roll bar, the stiffness is determined by empirical or oversimplified mathematical models, often not reaching the optimal value. In this paper, eight parameters are used to determine the structure of the anti-roll bar. Combining the Deformation Energy theorem and Castigliano’s theorem, a mathematical model of the stiffness is established. The optimal solution and corresponding parameter values of the mathematical model are obtained by nonlinear programming and genetic algorithm. The influence of structural parameters on the anti-roll bar stiffness is analyzed, and the regular pattern of design is obtained. In addition, the finite element method is used to verify the stiffness solution model.

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.

Semi-active suspension has been widely applied in commercial vehicle suspension in order to get good riding comfortableness. Fuzzy logic control (FLC) has been widely applied in the field of kinetic control because control rule of FLC is easy to understand. But the gain of fuzzy rules and adjustment of membership functions usually depend on experts' experiences and repeated experiments, thus the fuzzy rules and membership functions has strong subjectivity, also are easily affected by environment of experiments, so the main problem of fuzzy logic controller design is selection and optimization of fuzzy rules and membership functions. Genetic Algorithms (GA) is the algorithm that searches the optimal solution through simulating natural evolutionary process and is one of the evolution algorithms which have most extensive impact.

Energy has the worldwide concern since the World War. Recently, the energy harvesting technology has got more attraction in different fields and applications. Hence, in a world where energy becomes rare and expensive, even the small quantities are worth to be harvested where it can be exploited in different applications. Vehicle suspension is one of the vibration power dissipation sources in which the undesired vibration is dissipated into heat waste. Accordingly, the principal motivation of this study is exploitation the conflict between the potentially harvested power and vehicle dynamics in automotive suspension system induced by road irregularity. Therefore, in terms of RMS conflict diagrams, the conflict between the potential power and vehicle dynamics are sufficiently and comprehensively defined considering a vehicle speed of 20 m/s.

This paper presented a brief derivation of the energy dissipation by vehicle shock absorbers. Analysis between energy dissipation and damping coefficient, the road displacement power spectral density, the vehicle speed and the tire stiffness was carried out. Then an energy recovery scheme was put forward, and the bench test proved that the energy harvest scheme is feasible. In the end, this paper provided detailed derivation of the characteristics of the hydraulic electromagnetic energy-regenerative shock absorber, which increases its feasibility and practicability.

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.

Commercial vehicle plays an important role during transportation process under the demand of high speed, convenience and efficiency. So improving active safety of commercial vehicle has become a research topic. Due to the fact that braking characteristic is the basic and most closely related to safe driving of vehicle's performances, this paper aims to improve the braking performance by researching into an integrated control method based on the mature ABS products. Firstly, a strategy which gives priority to ABS and differential yaw moment control, complementary with the hydraulic active suspension control is proposed. In comparison with ABS, the combined control of brake system and suspension system is designed not only for preventing wheels lock. But the directional control to avoid roll or spin is more focused on. Then in order to run the novel method correctly, the controlled variables and evaluation criteria are illustrated briefly.