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For intelligent vehicles, a robust perception system relies on training datasets with a large variety of scenes. The architecture of federated learning allows for efficient collaborative model iteration while ensuring privacy and security by leveraging data from multiple parties. However, the local data from different participants is often not independent and identically distributed, significantly affecting the training effectiveness of autonomous driving perception models in the context of federated learning. Unlike the well-studied issues of label distribution discrepancies in previous work, we focus on the challenges posed by scene heterogeneity in the context of federated learning for intelligent vehicles and the inadequacy of a single scene for training multi-task perception models. In this paper, we propose a federated learning-based perception model training system.

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.

The technology of active sound generation (ASG) for automobiles is one of the most effective methods to flexibly achieve the sound design that meets the expectations of different user groups, and the active sound synthesis algorithms are crucial for the implementation of ASG. In this paper, the Kaiser window function-based the harmonic synthesis algorithm of automobile sound is proposed to achieve the extraction of the order sounds of target automobile. And, the suitable fitting functions are utilized to construct the mathematical model between the engine speed information and the amplitude of the different order sound. Then, a random phase correction algorithm is proposed to ensure the coherence of the synthesized sounds. Finally, the analysis of simulation results verifies that the established method of the extraction and synthesis of order sound can meet the requirements of target sound quality.

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 recent years, research on car-like robots has received more attention due to the rapid development of artificial intelligence from diverse disciplines. As essential parts, path planning and lateral path tracking control are the basis for car-like robots to complete automation tasks. Based on the two-degree-of-freedom vehicle dynamic model, this study profoundly analyzes the car-like robots’ path planning and lateral path tracking control. Three objectives: path length, path smoothness, and path safety, are defined and used to construct a multi-objective path planning model. By introducing an adaptive factor, redefining the selection of reference points, and using the cubic spline interpolation for path determination, an improved NGSA-III is proposed, which is mostly adapted in solving the multi-objective path planning problem.

In the Formula Student Electric China (FSEC), the body structure is generally divided into two types, truss steel tube body and carbon fiber load-bearing body (monocoque). The monocoque is loved by Formula Student teams around the world because it has a higher stiffness and lighter weight than the truss steel tube body. With the widespread application of monocoque, it also brings more problems. Due to the use of the monocoque, the connection between each component and the body was changed from the welding of the original truss steel pipe frame to a bolted connection. However, the bolted connection will provide a large preload force to the monocoque, resulting in the monocoque easily crushed in the local, so it is necessary to pre-bury an enhanced part in the monocoque to ensure the connection strength, that is, the embedded part. At present, aluminum plug-ins after topological hollow processing are being used.

Overloading of trucks can easily cause damage to roads, bridges and other transportation facilities, and accelerate the fatigue loss of the vehicles themselves, and accidents are prone to occur under overload conditions. In recent years, various countries have formulated a series of management methods and governance measures for truck overloading. However, the detection method for overload behavior is not efficient and accurate enough. At present, the method of dynamic load identification is not perfect. No matter whether it is the dynamic weight measurement method of reconstructing the road surface or the non-contact dynamic weight measurement method, little attention is paid to the difference of different vehicles. Especially for different vehicles, there should be different load limits, and the current devices are not smart enough.

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.

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.

In order to solve the problems of insufficient accuracy for theoretical models and data-driven models for objective drivability evaluation requiring a large amount of data, an objective drivability evaluation method based on a hierarchical mixture model is proposed. First, a novel method of constructing a drivability evaluation system is developed, which combined by work breakdown structure (WBS) and analytic hierarchy process (AHP). Then, downshift condition is taken as a case study, and the subdivision condition is identified based on the hybrid mixture model. What's more, the drivability evaluation indexes of downshift condition are analyzed to establish the evaluation system of drivability.

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.

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.

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.

Due to the increase of mining production and rising labor costs, manufacturers of construction and mining equipment are engaged in developing large tonnage mining truck with good dynamic performance and high transport efficiency. This paper focuses on the improvement of the dynamic performance of a 52t off-highway dump truck. According to the characteristics of its operating cycle, electric auxiliary drive system is installed in the front axle aiming at improving the utilization rate of ground adhesion. The new all-wheel drive hybrid electric system makes it possible for dump truck transports at a higher velocity. Both the conventional dump truck model and the new all-wheel drive hybrid truck model are built based on the AVL-Cruise platform. Meanwhile, under the premise of enough dynamic performance, fuel consumption can be minimized by collaborative optimization in Isight.

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.

Butanol, which is a renewable biofuel, has been regarded as a promising alternative fuel for internal combustion engines. When blended with diesel and applied to pilot ignited natural gas engines, butanol has the capability to achieve lower emissions without sacrifice on thermal efficiency. However, high blend ratio of butanol is limited by its longer ignition delay caused by the higher latent heat and higher octane number, which restricts the improvement of emission characteristics. In this paper, the potential of increasing butanol blend ratio by adding hot exhaust gas recirculation (EGR) is investigated. 3D CFD model based on a detailed kinetic mechanism was built and validated by experimental results of natural gas engine ignited by diesel/butanol blends. The effects of hot EGR is then revealed by the simulation results of the combustion process, heat release traces and also the emissions under different diesel/butanol blend ratios.

With the development of the Internet for vehicles, the Car-sharing has been developed rapidly in recent years. This paper focuses on the network programming and distribution for Car-sharing, which helps to clarify the characteristics and basic law of Car-sharing network development, as well as the main approaches to construct it. Firstly, by analyzing the effect factors and expanding ways of Car-sharing network, characteristics of the development of Car-sharing industry and its network, as well as main Car-sharing users and services, the influence factors of Car-sharing demand and the main demand points in a city are summarized. Secondly, in order to better evaluate the network programming and distribution for Car-sharing, this paper proposes an optimization decision method of the car-sharing network planning by evaluating the possible alternatives in a same scale. The assessment index of Car-sharing network planning is constructed.