In order to improve the real-time and accuracy of parking slot detection in automatic parking, this paper proposed a lightweight parking-slot detection algorithm based on collaborative attention and graph neural network. Firstly, This algorithm used a lightweight network structure and the improved MobileNetV3 as the feature extraction network, obtained the location information and feature information of the parking-slot marker points through depthwise separable convolution, combined them to obtain the fused features of the marker points, then constructed a graph network structure to enhance the internal relationship of the parking-slot marker points, and combined the cooperative attention mechanism to integrate multiple attention. Finally, the algorithm was tested on the public parking-slot dataset PS2.0. The results indicate that the detection accuracy is better than the current mainstream algorithm, the average reasoning speed of each frame of image can reach 10.1 ms, with good accuracy and real-time performance.

To make autonomous lane change for intelligent vehicles in the situations with no lane or unclear lane, this paper proposed a lane change trajectory planning method based on virtual lane lines. Firstly, a virtual lane was constructed to divide the road into lanes parallel to the vehicle orientation, the best lane was determined according to the minimum heading angle of collision-free lane change. Secondly, the lane change end state was determined according to the average vehicle speed of the current lane and the target lane. The lane change trajectory was generated using the quintic polynomial combined with vehicle kinematics and dynamics. The path planning algorithm proposed was added to the intelligent planning decision-making module of the intelligent vehicle for simulation and hardware-in-loop test. The results show that the method realizes the function of autonomous lane changing in the situations without lane and improve the safety and driving efficiency of the vehicle in complex traffic environment.

To promote the application of core technologies in the autonomous operation system of intelligent and connected vehicles, this article analyzed the development trends, technical architectures and key technologies of future automotive operation systems from the perspectives of vehicle electronic and electrical architectures. At the same time, based on the application needs of vehicle manufacturers, the paper proposed implementation suggestions to accelerate the production and installation of domestic operation systems and ecological construction, in order to help accelerate the industrialization and development of autonomous operation systems for intelligent and connected vehicles.

For the problem of communication delay caused by the interference of the communication channel in the process of vehicle-road cooperative V2X communication, this paper proposed a V2X delay attack protection technology based on game theory. With the signal-to-noise ratio as the measurement index of communication quality, this paper firstly studied the function relationship between the transmission power of the attacking node and the signal-to-noise ratio to obtain the function relationship between the transmission power of the legitimate node and the attacking node, then this functional relationship was brought into the relationship between transmission power of legitimate node and the signal-to-noise ratio. This function also considered the probability of signal transmission, the probability of being detected and the transmission interference of other nodes to obtain the target function. Finally, the proposed protection technology is verified by simulation and test. The results show that by adjusting the transmission power of the nodes, it can effectively resist the attacker’s interference on the V2X communication channel and reduce the communication delay.

For the problem that intelligent vehicles lack the driver’s subjective driving operation cognition and the risk cognition of traffic participants, this paper proposed a trajectory planning algorithm based on improved Driver Risk Field (DRF). Firstly, the coordinate transformation from Cartesian coordinate system to Frenet coordinate system was carried out for the position of the vehicle, which visually represented the position information between the vehicle and the road; Secondly, a driver risk field model integrating vehicle stability risk was constructed to perceive the risk of traffic participants from the driver’s perspective; Finally, considering the comfort needs of drivers and passengers, obstacle avoidance operations were performed on the perceived risk potential energy high points based on quintic and quartic polynomial trajectories. The simulation and hardware-in-the-loop test results show that the planned trajectory meets both the obstacle avoidance function and the acceleration constraints, ensuring the safety and comfort of driving.

In order to improve the environmental perceive ability and better predict the behaviors of dynamic vehicle targets, a YOLOX model, as the front-end detector, combined with the optimized DeepSort method was proposed to develop the research of dynamic vehicle Multi-Object Tracking. In the process of features matching for dynamic vehicles, the change information of vehicles in the degree of light and shade was extracted to improve the object matching accuracy by adding Haarlike features. Furthermore, based on the application of DeepSort RE-identification network, the improved ResNet13 model was adopted as the backbone network for feature extraction, and SENet was introduced to adjust the feature weight of different channel dimensions. The results show that, compared to the conventional DeepSort method, by using the real on-road video data, the Multi-Object Tracking Accuracy (MOTA) and IDF1 indicator of the proposed algorithm increased by 1.4 percentage points and 7.7 percentage points respectively.

To study the lubrication characteristics of oil-cooled electric drive system, this article analyzed the splash lubrication characteristics of an oil cooled electric drive system and the phenomenon of poor low-speed lubrication under extreme attitudes, analyzed the forced lubrication and suction phenomenon of oil pump. The results show that the main characteristics of splash lubrication are poor lubrication at low flow rates and good lubrication at high flow rates; As the inclination angle increases, the flow rate shows a downward trend in uphill condition, while the flow rate in downhill conditions is just the opposite; The left tilt of 20° shows no lubrication effect and oil suction port is empty, while the right tilt of 20° shows poor oil stirring effect at low speed, while splash lubrication oil amount at left and right tilt is just the opposite. Forced lubrication can comprehensively consider the flow demand and proportion of the motor and reducer in the electric drive. The risk of empty suction of oil pumps will lead to forced lubrication failure. The solution of empty suction shall also consider the reduction of efficiency.

To clarify the discharge breakdown characteristics of drive motor bearing (discharge voltage, discharge current, discharge energy, discharge current density, etc.) and its influencing factor, thus reduce electrical erosion damage, a common mode equivalent circuit with concentrated parameters of a drive motor was established to extract shaft voltage. This paper determined the threshold voltage under the minimum oil film thickness according to the theory of elastic flow lubrication, analyzed the discharge breakdown characteristics of the bearing in combination with the discharge breakdown model, and clarified the variation law of the discharge breakdown characteristics under different rotational speed, temperature and force. The results show that as the rotational speed decreases and the temperature and radial force increase, the discharge breakdown characteristics related characteristics gradually decrease, meanwhile the effect of speed and temperature on the breakdown characteristics of the bearing is significantly higher than that of radial force.

In order to realize identity authentication and key distribution in Internet of Vehicle (IOV) scenario, this paper proposed an enhanced identity authentication scheme for the IOVs based on extended quantum key distribution. The features of this scheme are: (1) Quantum key mobile distribution was completed through quantum security module and preset quantum key in wireless communication, online negotiation of quantum key was completed through Quantum Key Distribution (QKD) equipment in wired communication, to achieve extended quantum key distribution; (2) Basic identity authentication based on post-quantum cryptography encryption and signature algorithms was conducted, and enhanced authentication through preset quantum keys. Finally, through security analysis and performance testing, it is confirmed that this scheme has sufficient security and low computational overhead. The total computational overhead is 1.689 ms, and the performance improvement is 60.43%~70.72%.

In this research, a lightweight authentication scheme was designed based on the quantum communication architecture of the Internet of Vehicle (IoV) cloud network. The authentication process consists of 2 stages: registration and authentication, and 2 rounds of authentication between the vehicle and the IoV cloud platform to ensure the security of the scheme. Test results show that this scheme has computational overhead of only 0.179 ms, and communication overhead of 417 B, which is lower than other 4 schemes, had has high efficiency while ensuring security, therefore it has high applicability for most IoV equipment with low computational amount and low communication volume.