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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.

With the increasingly serious problems of environmental pollution and energy shortage, electric vehicles have a promising future. As a core component of electric vehicles, the drive motor is developing towards high power density of which remains temperature rise problems, which affects the performance, efficiency and service life of the drive motor. Liquid cooling has high energy consumption and poor reliability. The heat-pipe has excellent heat conduction and temperature uniformity capabilities. Therefore, this paper proposes a heat pipe-based drive motor heat dissipation system to make the heat-pipe act on the inside of the motor to reach a specified range of driving conditions. The drive motor can better dissipate heat through the heat-pipe. Firstly, analysis of the internal heat generation mechanism of the motor, heat transfer characteristics of the heat-pipe and the heat-pipe layout plan was established.

The development of high precision flow divider/combiner valves has received considerable attention by the authors over the past decade. Several different valve designs for division and combination of flow have been designed which display small flow dividing/combining error (1-2%) when compared to conventional designs (2-10%). Recent studies have improved upon the design in order to reduce cost, weight and complexity of the valve. This paper will present the latest of the authors research into the development of a high precision, autoregulated flow divider/combiner valve with an integral shuttle valve. The autoregulator extends the operating range of the integrated flow divider/combiner valve (for errors less than 2 %) to 10-50 lpm compared to 30-50 lpm for the unregulated valve.

On-road testing of driving performance of the urban bus was carried out, and a representative urban bus driving cycle was developed after on-road testing, according to the test results. Then, the vehicle simulation software AVL CRUISE was used to simulate the dynamic behavior of the urban bus. It involves the simulation of complete drive train system and the driver behavior. The model is validated by comparing the results of the simulation to the results of the field test. Then the developed driving cycle is evaluated by fuel consumption resulted from the simulation and engine bench test on fuel economy.

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.

The basic principle of wavelet transform is presented and the method of wavelet theory is used in vibration signal analysis of vehicle in this paper. The vibration signals which generated in the locations such as cab floor, engine, transmission, band spring and frame under the usual work condition are measured by the vibration test system. The vibration signals are decomposed with the principle of wavelet decomposition at level six, and eigenvectors of signal energy are gained. According to the correlation coefficient of eigenvectors of signal energy distribution, two signals correlativity is determined. It could be an effective method that identificate the main vibration source.

In the process of designing the aerodynamic kit for Formula SAE racing cars, there is a lot of repetitive work and low efficiency in optimizing parameters such as wing angle of attack and chord length. Moreover, the optimization of these parameters in past designs heavily relied on design experience and it's difficult to achieve the optimal solution through theoretical calculations. By establishing a parametric model in CAD software and integrating it with CFD software, we can automatically modify model parameters, run a large number of simulations, and analyze the simulation results using statistical methods. After multiple iterations, we achieve fully automatic parameter optimization and obtain higher negative lift. At the same time, the simulation process is optimized, and simulations are run based on GPUs, resulting in a significant increase in simulation speed compared to the original.

With the increase of car ownership and the complex and crowded parking environment, it is difficult for drivers to complete the parking operation quickly and accurately, which may cause traffic accidents such as vehicle collisions and road jams because of poor parking skills. The emergence of an automatic parking system can help drivers park safely and reduce the occurrence of safety accidents. In this paper, the neural network identifier on the control method of an adaptive integral derivative of a neural network is proposed for an automatic parallel parking system with front-wheel steering is studied by using MATLAB/Simulink environment, and the simulation is carried out. Firstly, according to vehicle parameters and obstacle avoidance constraints, the minimum parking space, and parking starting position are calculated. Meanwhile, the path planning of parallel parking spaces is carried out by quintic polynomial.

Deep Deterministic Policy Gradient (DDPG) is one of the Deep Reinforcement Learning algorithms. Because of the well perform in continuous motion control, DDPG algorithm is applied in the field of self-driving. Regarding the problems of the instability of DDPG algorithm during training and low training efficiency and slow convergence rate. An improved DDPG algorithm based on segmented experience replay is presented. On the basis of the DDPG algorithm, the segmented experience replay select the training experience by the importance according to the training progress to improve the training efficiency and stability of the training model. The algorithm was tested in an open source 3D car racing simulator called TORCS. The simulation results demonstrate the training stability is significantly improved compared with the DDPG algorithm and the DQN algorithm, and the average return is about 46% higher than the DDPG algorithm and about 55% higher than the DQN algorithm.

People, vehicles and circumstances are the three key factors, which affect transportation systems. Offering more information to the driver and helping him observe on all sides so that he can make decisions correctly are of great importance for reducing accidents. According to the present traffic regulations, in this paper we focus on the rules and process used during steering and proposed to implement them in a car information central control system based on CAN. A comparison of the brake time between brake by driver and by radars revealed the great interest of using ECUs connected by CAN network.

As motor assembly of Battery Electric Vehicle (BEV) replaces engine system of Internal Combustion Engine (ICE) vehicle, interior structure-borne noise induced by road random excitation becomes more prominent under middle and high speed. The research is focused on central driving type BEV. In order to improve interior noise in middle and low frequency range, dynamic load of BEV body must be identified. Consequently the structural noise induced by road excitation is conducted. The limitations of common identification method for dynamic body load are analyzed. The applied several identification methods are proposed for deterministic dynamic load such as engine or motor. Random dynamic load generated by road excitation is different from deterministic dynamic load. The deterministic load identification method cannot be applied to the random load directly. An identification method of dynamic body load for BEV is presented based on power spectrum decomposition.

Recent research has shown that butanol, instead of ethanol, has the potential of introducing a more suitable blend in diesel engines. This is because butanol has properties similar to current transportation fuels in comparison to ethanol. However, the main downside is the high cost of the butanol production process. Acetone-butanol-ethanol (ABE) is an intermediate product of the fermentation process of butanol production. By eliminating the separation and purification processes, using ABE directly in diesel blends has the potential of greatly decreasing the overall cost for fuel production. This could lead to a vast commercial use of ABE-diesel blends on the market. Much research has been done in the past five years concerning spray and combustion processes of both neat ABE and ABE-diesel mixtures. Additionally, different compositions of ABE mixtures had been characterized with a similar experimental approach.

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.

Squeal noise in vehicle disc brakes is perceived by comsumers as both annoying and warranty cost. The mechanism is considered a mode coupling phenomenon also referred to as coalescence. In this paper, the system eigenvalues have been computed using a technique based on the • nite element method in order to obtain the dynamical properties of the disc brake assembly. The simulated squeal results were compared with the brake noise test that was in accordance with SAE J2521 standard and showed good correlation for some squeal frequencies which indicated that the research on disc brake squeal using complex mode could predict squeal propensity of the disc brake. Among the methods that have been used to control squeal noise, increasing the system damping has been shown to be very effective. The most commonly used method to increase system damping consists of attaching multi-layer laminates on the back of the brake pads.

For fracture cracks that occurred in the tight coupling exhaust manifold durability test of a four-cylinder gasoline engine with EGR channel, causes and solutions for fracture failure were found with the help of CFD and FEA numerical simulations. Wall temperature and heat transfer coefficient of the exhaust manifold inside wall were first accurately obtained through the thermal-fluid coupling analysis, then thermal modal and thermoplastic analysis were acquired by using the finite element method, on account of the bolt pretightening force and the contact relationship between flange face and cylinder head. Results showed that the first-order natural frequency did not meet the design requirements, which was the main reason of fatigue fracture. However, when the first-order natural frequency was rising, the delta equivalent plastic strain was increasing quickly as well.

Discretionary lane changing is commonly seen in highway driving. Intelligent vehicles are expected to change lanes discretionarily for better driving experience and higher traffic efficiency. This study proposed to optimize the decision-making and trajectory-planning process so that intelligent vehicles made lane changes not only with driving safety taken into account, but also with the goal to improve driving comfort as well as to meet the driver’ s expectation. The mechanism of how various factors contribute to the driver’s intention to change lanes was studied by carrying out a series of driving simulation experiments, and a Lane-Changing Intention Generation (LCIG) model based on Bi-directional Long Short-Term Memory (Bi-LSTM) was proposed.

Before the new car rolls from the line, due to assembly errors, inaccurate four-wheel positioning, etc., the vehicle will run off on a flat road, which will affect the driving comfort and safety. At present, most automobile manufacturers choose to perform the deviation test in the process of vehicle rolls from the line. Compared with other detection methods, the online deviation test system is developed with high precision of laser ranging, fast response and good reliability, which can realize fast and high-precision detection of vehicle deviation. In this paper, test system software is developed based on the LABVIEW, a variety of communication methods to build the communication system, using information check and queue task processing to control, to meet the test needs. Firstly, the calculation model of the deviation of the test system is established.

This paper presents a Driver-In-the-Loop (DIL) bench test system for development of ESC controller. The real-time platform is built-up based on NI/PXI system and the real steering/throttle/braking actuator. In addition, the CarSim provides the vehicle model and the animator for virtual driving environment. A hierarchical ESC controller is proposed in MATLAB/Simulink then download into PXI. In the upper motion controller, the sliding mode theory is adopted and the logic threshold algorithm is used in the lower slip controller. Finally, ESC test is implemented under typical conditions by DIL and Model-In-the-Loop (MIL). The results show that, DIL could make up the shortage of driver model which can’t accurately simulate the emergency response of real driver. Therefore, DIL test could verify the ESC controller more accurately and effectively with considering the human-vehicle-road environment.

Compared with urban areas, the road surface in mountainous areas generally has a larger slope, larger curvature and narrower width, and the vehicle may roll over and other dangers on such a road. In the case of limited driver information, if the two cars on the mountain road approach fast, it is very likely to occur road blockage or even collision. Multi-vehicle cooperative control technology can integrate the driving data of nearby vehicles, expand the perception range of vehicles, assist driving through multi-objective optimization algorithm, and improve the driving safety and traffic system reliability. Most existing studies on cooperative control of multiple vehicles is mainly focused on urban areas with stable environment, while ignoring complex conditions in mountainous areas and the influence of driver status. In this study, a digital twin based multi-vehicle cooperative warning system was proposed to improve the safety of multiple vehicles on mountain roads.

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.