Sensor network for traffic surveillance
Authors: Yangshong Xu
Venue:  (2007)

Nowadays, with the rapid development of economics and societies, transportation is playing a very important role in the balanced running of social and economic systems. However, urban traffic problems such as traffic accidents and traffic congestions are becoming more and more serious in almost all large cities in the world. This thesis is focused on a traffic surveillance system which collects and transmits real-time traffic information in a large city, which is one of the most important steps in solving the transportation problems above. Considering the drawbacks of current traffic surveillance system, a brand-new system with a distributed architecture is proposed based on the concept of sensor networks. Then, an intelligent sensor node using an embedded ARM chip and MCU is developed and software system is built up accordingly, including Linux operating system, hardware drivers, and so on. Finally, a simulation program proves the validity of the system. As an example, the thesis proposes a real-time route guidance system to show how it supports other transportation services, which can then automatically guide vehicles by voice. It illustrates the system architecture and describes the establishment of each part. The concept of agent network is introduced to build up the system. Furthermore, a dynamic route algorithm is presented in brief. A communication system integrating the existing infrastructure is discussed and simulation results are provided to testify the applicability of the proposed wireless data communication system. In addition, two important techniques required to build the new surveillance system are discussed in this thesis. (1) the sensors to collect traffic information; (2) the communication network to transmit information among all sensors and vehicles. In order to detect and track the moving objects, this thesis presents a creative background updating method, which can works effectively even for some complex circumstances. The image processing results show that this method can realize the segmentation of the moving objects. Due to the simple model and fast calculation speed, the method can satisfy the requirements of detecting and tracking traffic objects in real time and at a high speed. Additionally, the thesis designs a new kind of object detection and tracking algorithm based on the attributive combination of contour and color in order to deal with the occlusion problem to some extent. Some experiments have testified to the robustness and practicability of the proposed system. For the communication network, the main challenging problems are the large scale of the network, the movement of vehicles that may cause the levity of the network structure, and the large demands on communication capacity. In order to solve these problems, the performance optimization technique is accredited as one of the most important techniques for such a large scale wireless sensor network. This thesis focuses on the research in the following aspects. First, the optimal combination of the duty cycle, one of the most important parameters, is introduced to optimize the system performance. A duty cycle optimization model is put forward based on calculating n-times reachable matrix. Now that the parameter optimization model can be boiled down to a NP-hard problem, an improved genetic algorithm is introduced to solve the problem. The computational procedure and efficiency are discussed, and simulation study based on a practical road network is given to illustrate the validity of the proposed method. Second, the topological structure optimization problem is formulated as a graph problem, while fulfilling random node-to-node communication demands. A new optimization method, called un-detour optimization, is proposed to optimize the topological structure based on the improved genetic algorithm. In addition, the approach is evaluated quantitatively by simulating community wireless sensor networks. The comparison results demonstrate that some significant performance advantages can be achieved by this approach. Finally, the thesis sums up the contributions achieved and proposes some future works.