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The detection of river boundaries is a crucial branch of the intelligent perception of unmanned surface vehicles (USVs), it can be used to determine the driving areas of USVs, and also to ensure driving safety by limiting the effective drivable areas of USVs in the river areas. Aiming to detect the boundaries of incompletely structured river channels, this study proposes a real‐time detection method for river boundaries based on a Light Detection and Ranging (LiDAR) sensor. The point clouds that are disturbed by the water surface noise are filtered firstly, and then the spatial and geometric features are extracted separately from the point cloud detected above the water surface. To prevent the error detection and missing detection, the boundary point information is predicted and calibrated in real time by Extended Kalman Filter (EKF). A planning track generation algorithm for coastal autonomous cruise without relying on high‐precision maps, and a heading and distance adaptive control method by Proportional‐Integral‐Derivative (PID), and different driving line generation methods for driving along the narrow river and wide river are proposed respectively. The experimental data verification of river boundary detection shows that the algorithm is accurate, real‐time, and robust. [ABSTRACT FROM AUTHOR]

Integrating advantages of automated driving and mass transport, autonomous buses have broad development prospects. The research on the public acceptance of autonomous buses will help to provide a basis for formulating policies and measures, and thus have important theoretical and practical significance. In this paper, an initial theoretical model of acceptance of autonomous buses was established. An on‐line survey was conducted with a total of 401 valid samples collected. The reliability and validity tests of the data showed that the internal consistency of the questionnaire was high, and the reliability and validity all met the requirements. Based on the results of structural equation modelling, the proposed model was validated and all the hypotheses were confirmed. Attitude would positively affect behavioural intention, and trust and perceived usefulness would positively affect attitudes. Moreover, both perceived ease of use and perceived comfort would have positive effects on perceived usefulness as well as on trust. Perceived risk would be negatively associated with trust. Multi‐group analyses were conducted to test the moderating effects of the individual's education and knowledge of autonomous buses, and the two factors showed significant effects. Based on the results, corresponding measures can be taken to increase the acceptance of autonomous buses. [ABSTRACT FROM AUTHOR]

Ears are responsible for the sense of hearing, which is indispensable for a human to understand the environment. It is similar to an intelligent vehicle where acoustical data contains useful and valuable information to comprehend the environment to enable autonomous driving. One important application of acoustical data processing is to localize sound sources. However, due to the complexity of microphone array setup and the unstable localization performance against noises, few research articles tried to localize surrounding vehicles based on on‐board microphone arrays. The main contribution is the first implementation to combine roof‐mounted microphones and high definition maps as vehicle' s ears for online 3D localization of surround vehicles. This article designed a six‐microphones sensor array dedicated to the on‐board application and improved sound source localization algorithms using the observer technique to adapt to dynamic driving scenarios. A map‐based localization enhancement method is also proposed to make the system more robust to noises and model errors. Feasibility tests are conducted with real vehicles in the scenarios of pass‐by and overtaking. Experimental results validate the feasibility of using microphones to localize surrounding vehicles with lane‐level accuracy. [ABSTRACT FROM AUTHOR]

In case of emergency braking in danger, autonomous vehicle usually uses electronic stability control system to maintain the dynamic stability of the vehicle, and by adjusting the steering system, the vehicle can realize autonomous driving. However, when the autonomous vehicle is in emergency braking on the split‐mu road, due to the inconsistent adhesion coefficient on both sides of the road, the inconsistency of tire force will not only damage the dynamic stability, but also make the vehicle deviate from the planned trajectory. Because the path tracking algorithm of autonomous vehicle needs to detect the trajectory error first, it will lead to the time delay of trajectory error correction, and its correction ability will weaken with the decrease of speed, so that the vehicle's trajectory will deviate unilaterally. Thus, the tracking accuracy is reduced and the driving safety is endangered. This paper proposes a dynamic coordinated control strategy based on dynamics and kinematics. In response to the rapid changes in lateral disturbances, a flexible control transfer mechanism based on vehicle status is constructed, realize dynamic coordinated control based on path tracking algorithm and active steering algorithm. While improving the lateral stability, the trajectory error is reduced. [ABSTRACT FROM AUTHOR]