Search Results

With the development of highway transportation and automobile industry technology, highway truck overload phenomenon occurs frequently, which poses a danger to road safety and personnel life safety. So it is very important to identify the overload phenomenon. Traditionally, static detection is adopted for overload identification, which has low efficiency. Aiming at this phenomenon, a dynamic overload identification method is proposed. Firstly, the coupled road excitation model of vehicle speed and speed bump is established, and then the 4-DOF vehicle model of half car is established. At the same time, considering that the double input vibration of the front and rear wheels will be coupled when vehicle passes through the speed bump, the model is decoupled. Then, the vertical trajectory of the body in the front axle position is obtained by Carsim software simulation.

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.

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.

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.

There are a large number of curves and slopes in the mountainous areas. Unreasonable acceleration and deceleration in these areas will increase the burden of the brake system and the fuel consumption of the vehicle. The main purpose of this paper is to introduce a speed planning and promotion system for commercial vehicles in mountainous areas. The wind, slope, curve, engine brake, and rolling resistances are analyzed to establish the thermal model of the brake system. Based on the thermal model, the safe speed of the brake system is acquired. The maximum safe speed on the turning section is generated by the vehicle dynamic model. And the economic speed is calculated according to the fuel consumption model. The planning speed is provided based on these models. This system can guide the driver to handle the vehicle speed more reasonably.

The high gravity center of the concrete mixer truck reduces the truck’s stability while steering. The rolling stirring tank makes the stability even worse than the regular engineering vehicle due to the dynamic variation of the centroid position. Most of the researches on the rollover stability of concrete mixer trucks focus on the rollover model establishment and dynamic simulation module. The change of concrete centroid is ignored when the safety cornering speed is calculated. This paper proposes a pre-warning method for the cornering speed of concrete mixer trucks based on centroid dynamic simulation. In the method, the mixing tank stirring model and the vehicle driving dynamic model are established on the Fluent and TruckSim simulation platforms, respectively. The theoretical speed threshold obtained by simulation is used as the evaluation index of the warning speed in the curve. Firstly, the dynamic simulation of the stirring tank model is carried out by Fluent.

When driving in mountainous areas, vehicles often encounter downhill conditions. To ensure safe driving, it is necessary to control the speed of vehicles. For internal combustion engine vehicles, auxiliary brake such as engine brake can be used to alleviate the thermal load caused by the continuous braking of the friction brake. For battery electric vehicles (BEVs), regenerative braking can be used as auxiliary braking to improve brake safety. And through regenerative braking, energy can be partly converted into electrical energy and stored in accumulators (such as power batteries and supercapacitors), thus extending the mileage. However, the driver's line of sight in the mountains is limited, resulting in a certain degree of blindness in driving, so it is impossible to fully guarantee the safety and energy saving of downhill driving.

Mountainous area makes up more than half of the whole land area of China, the road of which is full of ups and downs. Heavy commercial vehicles as the main means of transport in mountainous areas, braking torque recession, even brake failure, often happens because of the overheating in long downhill journey, which seriously threatens the safety of the driving. Therefore, this paper presents an intelligent assistance system based on Geographic Information System and vehicle dynamics. The main brake duration and heat generation can be effectively reduced through adjusting the speed at the slope top, applying the engine auxiliary brake in the initial stage and choosing braking strategy appropriately, in order to prolong the downhill driving distance and improve the safety during continuous braking. This paper characterizes and analyses the road gradients and their effects on braking heat generation.

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.

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 continuous braking for the brake drum will cause the brake thermal decay when the heavy truck is driving down the long slope in the mountain areas. It reduces the heavy truck’s braking performance and the braking safety. The engine braking and the hydraulic retarder braking both consume the kinetic energy of the heavy truck and can assist the truck driving in the mountain areas. This research proposes a combined hill descent braking strategy for heavy truck based on the recorded information of the slopes to ensure the braking safety of the heavy truck. The vehicle dynamic model and the brake drum temperature rising model are established to analyze the drum’s temperature variation during the downhill progress of the heavy truck. Then based on the slope information, the combined braking temperature variation is analyzed considering the characteristics of the engine braking, the drum braking and the hydraulic retarder braking.

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.