Lane Utilization Ratio (LUR), affected by lane selection behavior directly, represents the traffic distribution on different lanes of road section for a single direction. The research on LUR, especially under Penetration Conditions of Connected and Automated Vehicles (PCCAV), is not comprehensive enough. Considering the difficulty in the conduction of real vehicle experiment and data collection under PPCAV, the lane selection model based on phase-field coupling and set pair logic, which considers the full-information of lanes, was used to carry out microscopic traffic simulation. From the analysis of microsimulation results, the basic relationships between Penetration of Connected and Automated Vehicles (PCAV), traffic volume, and Lane-Changing Times, also that between PCAV, traffic volume, and LUR in the basic section of the urban expressway were studied. Moreover, the influence of driving propensity on the effect of PCAVs was also studied. The research results could enrich the traffic flow theory and provide the theoretical basis for traffic management and control.

Ship object detection is the core part of the maritime intelligent ship safety assistance technology, which plays a crucial role in ship safety. The object detection algorithm based on the convolutional neural network has greatly improved the accuracy and speed of object detection, which YOLO algorithm stands out among the object detection algorithms with more excellent robustness, detection accuracy, and real-time performance. Based on the YOLO v4 algorithm, this study uses the k-means algorithm to improve clustering at the input side of image data and introduces relevant berth data in the self-organized dataset to achieve detection of ships and berths for the lack of detection of berths in the existing ship detection algorithm. The experimental results show that the mAP and F1-score of the improved YOLO v4 are increased by 2.79% and 0.80%, respectively. The improved YOLO v4 algorithm effectively improves the accuracy of ship object detection, and the in-port berth also achieves better detection results and improves the ship environment perception, which is important in assisting berthing and unberthing.