Abstract: A control method of mixed traffic flow on freeway ramp based on controllable connected and autonomous vehicles (CAVs) is provided. A ramp is divided into a normal driving section, a vehicle platoon formation section and an accelerating and merging section. A vehicle platoon is formed by a leading CAV and human-driven vehicles (HDVs). Time interval [tmin, tmax] for the vehicle platoon to completely reach the merging point S is calculated. CAVs on the main lane and ramp are cooperatively controlled, and a merging gap is reserved for the ramp vehicle platoon. The vehicle platoon is allowed to accelerate and merge into the main lane. By means of the Internet-of-Vehicle (IoV) technology, the traffic situation on the main lane and downstream merging zone can be obtained in advance, and speeds of the CAVs are cooperatively controlled to lead the ramp vehicles to safely merge into the main lane.

Abstract: A model of a system of an intelligent vehicle is trained and optimized using system operation data of the intelligent vehicle in a normal running state. The system operation data of the intelligent vehicle in a running state is collected in real time. Sensor data of the system operation data is de-noised, and feature extraction and screening are performed for a fatal sensor fault to reconstruct the system operation data. The reconstructed system operation data is inputted into the trained model to output system state data of the intelligent vehicle in the running state. The system state data is compared with a set threshold. If the system state data exceeds the set threshold, an actuator corresponding to the system state data is determined to have a fault. In addition, a system for a fault diagnosis of the intelligent vehicle is further provided.

Abstract: A model of a system of an intelligent vehicle is trained and optimized using system operation data of the intelligent vehicle in a normal running state. The system operation data of the intelligent vehicle in a running state is collected in real time. Sensor data of the system operation data is de-noised, and feature extraction and screening are performed for a fatal sensor fault to reconstruct the system operation data. The reconstructed system operation data is inputted into the trained model to output system state data of the intelligent vehicle in the running state. The system state data is compared with a set threshold. If the system state data exceeds the set threshold, an actuator corresponding to the system state data is determined to have a fault. In addition, a system for a fault diagnosis of the intelligent vehicle is further provided.

Abstract: The present invention discloses a target cross-domain detection and understanding method, system and equipment and a storage medium.

Abstract: Disclosed is an LTE-V based Internet of Vehicles communication test system and test method. The test system includes an ENodeB base station, a roadside test unit, user test terminal, LTE-V core network and local server group. Mobile communication technology is applied to the field of Internet of Vehicles communication, and two technical schemes are used, i.e., wide-area centralized cellular communication and short-range distributed direct communication corresponding to the network architectures based on access network-user terminal and ProSe direct communication interface, respectively. Not only the communication transmission support with large broadband in wide coverage can be supported, but also to achieve low latency and highly reliable communication services between vehicle and vehicle, vehicle and base station, base station and base station, to meet the needs of road safety and traffic efficiency applications.

Abstract: Provided herein relates to the performance testing of automated vehicles, and more particularly to a system and a method for testing cooperative driving capability of an automated vehicle. The system includes a target vehicle, a test road and a control center, where the automated vehicle and the target vehicle are located on the test road, and the control center is located beside the test road. A speed sensor and a binocular camera are provided on the automated vehicle. The speed sensor and the binocular camera are connected to the control center through a wireless communication device, respectively. An on-board device is provided on the target vehicle and is connected to the control center through the wireless communication device. The method provided herein is used to determine the responsiveness of automated vehicles according to the speed relationship and distance between the automated vehicle and the target vehicle.

Abstract: The present disclosure discloses a method for Internet of Vehicles (IoV) electronic traffic sign information broadcast with Quality of Service (QoS) guaranteed mechanism based on conflict detection. Compared with the traditional WLAN applied in electronic traffic sign information broadcast, the present disclosure significantly reduces the information broadcast delay, and at the same time provide QoS guaranteed service for the information broadcast. It allows IoV, through distributed algorithm, to achieve the electronic traffic sign information broadcast with self-organization framework, short transmission delay and high efficiency.

Abstract: Disclosed is an LTE-V based Internet of Vehicles communication test system and test method. The test system includes an ENodeB base station, a roadside test unit, user test terminal, LTE-V core network and local server group. Mobile communication technology is applied to the field of Internet of Vehicles communication, and two technical schemes are used, i.e., wide-area centralized cellular communication and short-range distributed direct communication corresponding to the network architectures based on access network-user terminal and ProSe direct communication interface, respectively. Not only the communication transmission support with large broadband in wide coverage can be supported, but also to achieve low latency and highly reliable communication services between vehicle and vehicle, vehicle and base station, base station and base station, to meet the needs of road safety and traffic efficiency applications.

Abstract: The present disclosure discloses a method for Internet of Vehicles (IoV) electronic traffic sign information broadcast with Quality of Service (QoS) guaranteed mechanism based on conflict detection. Compared with the traditional WLAN applied in electronic traffic sign information broadcast, the present disclosure significantly reduces the information broadcast delay, and at the same time provide QoS guaranteed service for the information broadcast. It allows IoV, through distributed algorithm, to achieve the electronic traffic sign information broadcast with self-organization framework, short transmission delay and high efficiency.