Yu Jian

Bio: Yu Jian is an academic researcher from Tongji University. The author has contributed to research in topics: Intersection & Smart camera. The author has an hindex of 6, co-authored 18 publications receiving 72 citations.

Control apparatus, and traffic light control method and system applied thereby

Abstract: The invention provides a control apparatus, and a traffic light control method and system applied thereby. The method comprises the following steps: under the condition that green light time of an execution phase is greater than minimum green light time and smaller than maximum green light time, when red light time of a certain candidate phase is greater than or equal to preset maximum red light time, the candidate phase whose red light time reaches the maximum red light time becoming a new execution phase; otherwise, calculating green light demand degrees of the execution phase and the candidate phase, and when the green light demand degree of the candidate phase is greater than the green light demand degree of the execution phase, making the corresponding candidate phase be the new execution phase; and when the green light time of the execution phase is greater than the maximum green light time, detecting the number of queuing vehicles of the candidate phase, and making the candidate phase with the greatest queuing vehicle the new execution phase. According to the traffic flow condition of each phase, traffic lights are intelligently controlled, the number of vehicles released at a crossing is further increased, and smooth traffic operation is guaranteed.

Improved traffic signal control method based on Q learning

Abstract: The invention relates to an improved traffic signal control method based on Q learning The method comprises the following steps that 1, initial lookup tables corresponding to all intersections inside a region are obtained under the simulation environment, and the initial lookup tables include environment information states, intersection actions and corresponding Q values; 2, environment information of all traffic intersections is detected continuously through sensors installed on the traffic intersections under the actual traffic environment; 3, a local intersection is selected inside the region, an intersection signal switching algorithm is adopted for judging whether signal switching is needed at the local intersection or not according to the environment information of the traffic intersections and the initial lookup tables, and a function is updated according to the Q values to update the initial lookup tables; 4, another intersection is selected, the third step is executed again, and finally signal control of all the intersections inside the region is completed Compared with the prior art, the method has the advantages of considering the intersection linkage, achieving computation accurately and conveniently and the like

Traffic monitoring video storing method in HDFS based on event intensity

Abstract: The invention discloses a traffic monitoring video storing method in an HDFS based on event intensity. The traffic monitoring video storing method is characterized by comprising the following steps that an intelligent camera obtains traffic monitoring data, detects traffic events and sends traffic video streaming data and event type description information included in the data to a video server; the video server encodes and segments the video data after receiving the video streaming data sent by the camera, a video file is generated, and the file is marked with the event type according to the event description information of the video data; the video data are uploaded to the HDFS; after receiving a data storage request, a Name Node in the HDFS calls a data placement strategy based on the event intensity to select a target data node for the data file to be stored; the file is stored in the target data node selected in the third step. The problem of node load unbalance caused when the HDFS stores mass traffic monitoring videos can be solved, and accordingly, the traffic monitoring data can be efficiently stored.

Tracking system, camera, monitoring method and monitoring system

Abstract: The present invention provides a tracking system, a camera, a monitoring method and a monitoring system. The camera is autonomously joint as the network system of a tracking object to actively track an object and record the information and escape routes of the tracking object at different monitoring scenes and time points; the camera arranges the corresponding route list according to the correlative mechanism and executes the monitoring motion in the monitoring range; when the tracking object is monitored in the monitoring range according to the preset tracking information, or the tracking object is monitored in the monitoring range according to the shot abnormal event, or the tracking object is monitored in the monitoring range according to the received tracking information sent by other cameras, the feature information of the tracking object is obtained; and when the tracking object gets away from the monitoring range, the new tracking information is generated according to the obtained feature information, and the new tracking information is sent to the corresponding other cameras according to the route list. The tracking system, the camera, the monitoring method and the monitoring system can effectively and accurately monitor the tracking object, and the information transmission between cameras are reliable and stable.

Wireless HART standard-based in-vehicle wireless interaction method

Abstract: The invention relates to a Wireless HART standard-based in-vehicle wireless interaction method, and aims to establish a wireless vehicle-mounted network. The vehicle-mounted network comprises a gateway, access points and a plurality of wireless nodes, wherein the gateway accesses to a vehicle control wired network, and is connected to the access points; and the wireless nodes and the access points form the mesh wireless vehicle-mounted network. The method comprises: a network access and networking stage, a communication stage and a network searching stage. Compared with the prior art, in the method provided by the invention, through the network access and networking stage, the automatic fast networking is realized, through the communication stage, safe data transmission is realized based on a redundant path, and through the network searching stage, low power consumption operation is realized; and the wireless vehicle-mounted network can replace a communication cable, and a purpose of reduction of the wiring harness weight is realized by use of various equipment which are connected with a vehicle through a wireless technology.

Metropolitan intelligent surveillance systems for urban areas by harnessing IoT and edge computing paradigms

Abstract: Recent technological advances led to the rapid and uncontrolled proliferation of intelligent surveillance systems (ISSs), serving to supervise urban areas. Driven by pressing public safety and security requirements, modern cities are being transformed into tangled cyber-physical environments, consisting of numerous heterogeneous ISSs under different administrative domains with low or no capabilities for reuse and interaction. This isolated pattern renders itself unsustainable in city-wide scenarios that typically require to aggregate, manage, and process multiple video streams continuously generated by distributed ISS sources. A coordinated approach is therefore required to enable an interoperable ISS for metropolitan areas, facilitating technological sustainability to prevent network bandwidth saturation. To meet these requirements, this paper combines several approaches and technologies, namely the Internet of Things, cloud computing, edge computing and big data, into a common framework to enable a unified approach to implementing an ISS at an urban scale, thus paving the way for the metropolitan intelligent surveillance system (MISS). The proposed solution aims to push data management and processing tasks as close to data sources as possible, thus increasing performance and security levels that are usually critical to surveillance systems. To demonstrate the feasibility and the effectiveness of this approach, the paper presents a case study based on a distributed ISS scenario in a crowded urban area, implemented on clustered edge devices that are able to off-load tasks in a “horizontal” manner in the context of the developed MISS framework. As demonstrated by the initial experiments, the MISS prototype is able to obtain face recognition results 8 times faster compared with the traditional off-loading pattern, where processing tasks are pushed “vertically” to the cloud.

Vehicle Counting Based on Vehicle Detection and Tracking from Aerial Videos.

Abstract: Vehicle counting from an unmanned aerial vehicle (UAV) is becoming a popular research topic in traffic monitoring. Camera mounted on UAV can be regarded as a visual sensor for collecting aerial videos. Compared with traditional sensors, the UAV can be flexibly deployed to the areas that need to be monitored and can provide a larger perspective. In this paper, a novel framework for vehicle counting based on aerial videos is proposed. In our framework, the moving-object detector can handle the following two situations: static background and moving background. For static background, a pixel-level video foreground detector is given to detect vehicles, which can update background model continuously. For moving background, image-registration is employed to estimate the camera motion, which allows the vehicles to be detected in a reference coordinate system. In addition, to overcome the change of scale and shape of vehicle in images, we employ an online-learning tracker which can update the samples used for training. Finally, we design a multi-object management module which can efficiently analyze and validate the status of the tracked vehicles with multi-threading technique. Our method was tested on aerial videos of real highway scenes that contain fixed-background and moving-background. The experimental results show that the proposed method can achieve more than 90% and 85% accuracy of vehicle counting in fixed-background videos and moving-background videos respectively.

Traffic signal self-adaptive control method based on deep reinforcement learning

Abstract: The invention relates to the technical field of traffic control and artificial intelligence and provides a traffic signal self-adaptive control method based on deep reinforcement learning. The method includes the following steps that 1, a traffic signal control agent, a state space S, a motion space A and a return function r are defined; 2, a deep neutral network is pre-trained; 3, the neutral network is trained through a deep reinforcement learning method; 4, traffic signal control is carried out according to the trained deep neutral network. By preprocessing traffic data acquired by magnetic induction, video, an RFID, vehicle internet and the like, low-layer expression of the traffic state containing vehicle position information is obtained; then the traffic state is perceived through a multilayer perceptron of deep learning, and high-layer abstract features of the current traffic state are obtained; on the basis, a proper timing plan is selected according to the high-layer abstract features of the current traffic state through the decision making capacity of reinforcement learning, self-adaptive control of traffic signals is achieved, the vehicle travel time is shortened accordingly, and safe, smooth, orderly and efficient operation of traffic is guaranteed.

SBPG: Secure Better Portable Graphics for Trustworthy Media Communications in the IoT

Abstract: Smart Healthcare is envisioned as the combination of traditional healthcare augmented by smart bio-sensors, wearable devices, and a plethora of on-body sensors that communicate with smart hospitals, smart emergency response systems, and ambulances, through advanced information and communication technologies. The vision of smart healthcare as part of a smart city relies on the framework of the Internet of Things (IoT) as the underlying core technology that enables the design and operation of a city, whereby smart technology, energy grids, transportation, buildings, communication, and information technology, are all interconnected. This paper addresses some of the challenges faced in the IoT infrastructure, specifically secure communication and user authentication in the context of automated analysis of biomedical images and communication of the analysis results and related metadata in a smart healthcare framework. A hardware architecture for a secure digital camera integrated with the secure better portable graphics (SBPG) compression algorithm, suitable for applications in the IoT, is proposed in this paper. The focus of this paper is on patient data protection and authentication. The proposed SBPG architecture offers two layers of protection, concurrent encryption and watermarking, which address all issues related to security, privacy, and digital rights management. The experimental results demonstrate that the new compression technique BPG outperforms JPEG in terms of compression quality and compressed file size while providing increased image quality. High performance requirements of BPG have been met by employing two techniques: 1) insertion of an encrypted signature in the center portion of the image and 2) frequency-domain watermarking using blockwise DCT of size $8\times 8$ pixels. These approaches optimize the proposed architecture by decreasing computational complexity while maintaining strong protection, with concomitant increase of the speed of the watermarking and compression processes. A Simulink® prototype for the proposed architecture has been built and tested. To the best of our knowledge, the hardware architecture for BPG compression with built-in image authentication capability for integration with a secure digital camera is the first one ever proposed .

In-vehicle networking

Abstract: A system and method for securing communication across an in-vehicle bus, includes establishing a connection between a gateway in a vehicle and the in-vehicle bus; generating a session key at the gateway within the vehicle; transmitting a public key certificate and ephemeral key to the gateway and an electronic control unit of the vehicle; generating a shared secret at the gateway and the electronic control unit, respectively; encrypting the session key with the shared secret at the gateway; receiving the encrypted session key through the in-vehicle bus at the electronic control unit; and decrypting the encrypted session key based on the shared secret generated at the electronic control unit.