Research On Key Technologies For V2V Multi-Hop Broadcast In VANETs

Today, intelligent transportation system is a key project in transportation. Its part of data transmission fully displays VANETs application importance. In many applications of VANETs, safety application draws much attention from research community, government and vehicle manufactures in recent years, in particular, the safe message distribution becomes a hot topic. For traffic safety on road, the protocol for efficient distribution of safety message meets high requirements. Vehicles move quickly in VANETs, network topology changes frequently, the traffic density variability and diversity of wireless channel quality make safety message broadcast facing huge challenge. Accurate prediction of link duration can significantly enhance the effectiveness of message transmission.While there is little research on such topic currently. We study broadcast protocol of safe message in urban VAENTs and link duration prediction in urban and highway scenarios. The solutions to the problems, basic research methods and results are as follows:Firstly, we focus on existing multi-hop broadcast protocols for safe message dissemination in VANETs at home and abroad. These protocols to transmit message along the road cause long transmission delay, and maintaining neighbor lists to identify road intersections cause high network overhead. Aiming at solving these problems and the urban environment that the wireless signal can directly reach, we propose AGBP(Area-Grouping Based Broadcast in Urban VANETs) protocol, including two parts of the vehicle region grouping and message distribution. Aiming at the regional grouping of vehicles, we propose equilateral triangle model and regular hexagon model structure grouping method; For message distribution, we design the mathematical formula of computing waiting delay for forwarding a message according to the distance between nodes and the vertex of an equilateral triangle or regular hexagon. All nodes control message forwarding according to the waiting delay parameter from this formula. The message is forwarded when the waiting delay is equal to zero. The node which first forwards a message is defined as the relay node in this group. Other nodes receiving the message cancel forwarding messages. This allows discarding the same message from other nodes. This protocol distributes a message along different road and direction per hop at the same time.Compared with exiting protocols, simulation results indicate that this protocol has high coverage, low forwarding node ratio, low link duration and network overhead.Secondly, in the light of large and dense building blocks radio signal in urban scenarios, to improve the efficiency and reliability of message distribution at the road intersections and reduce the message dissemination delay, we propose PMBW(Position based Multi-hop Broadcast for Warning Protocol in urban VANETs) in this disseration.The protocol uses different message forwarding mechanism at the intersection and on the straight road respectively. We propose that the identification method of road intersection, the mechanism of relay nodes selection and the relay node directly forward message without waiting time at the intersection. On the straight road, we propose a mathematical formular to compute waiting delay for forwarding message, when waiting delay becomes zero, the node forwards message, The first forwarding node is defined a relay node. Other nodes receiving message cancel forwarding message, and nodes discard same message from other nodes. We propose that this protocol forwards message in both direction along a straight road to reduce delay. The experiment results show that this protocol outperforms the existing broadcast protocols in terms of message coverage, forwarding node rate, link delay and network overhead in a variety of traffic flow density environment.Thirdly, vehicle nodes move quickly and network topology changes frequently in VANETs, so it causes link between two nodes to disconnect frequently. To dynamically predict how long the link connects between a neighbor and broadcast node in the future, we thoroughly analyze multiple microscopic factors including vehicles postion, move direction and vehicle speed, etc, these affect the link duration, aiming at vehicles moving straight on the road, considering an urban scenario with a traffic light and a highway scenario without a traffic light, we propose DPLD(Dynamically Predict Link Duration) model. We propose that relative velocity follow normal distribution and shows an estimation method for distribution parameters. This model uses the relative velocity distribution parameters as factors to automatically adapting speed change. Considering vehicles move in the same direction and opposite direction, we propose a relative distance computing method according to direction of movement. For traffic lights impacting on link duration, we design a probability model for continuous vehicles facing traffic lights combination, and analyze the specific prediction method of the link duration for each traffic light combination in detail and possible prediction errors. Aiming at extraction of simulation data and handling exception of vehicle speed, we propose that sliding windows to save speed data and Exponential Moving Average method. This ensures to accurate data in a short time. Therefore, it can reduce prediction errors due to experiments means. Simulation results shows that this model has high accuracy of link duration prediction in urban and highway scenarios with traffic flow density change.Fourthly, considering the impact of the vehicle turning on the link duration, we thoroughly study and propose ELDP(Extended Link Duration Prediction) model. We analyze the change range of the turning of the vehicle on the road, we use velocity vector method to analyze this. We propose relative velocity value follow normal distribution and show estimation method of parameters. We effictively use turning angle of vehicle as a factor in parameters estimation. Our model can automatically adjust to adapt speed change by using distribution parameters as foctors. We also use turning angle of vehicle as one factor to compute distance that one vehicle moves at relative speed. So turning angle of vehicle indirectly becomes a factor in the model by involving calculation of all parameters in the model, therfore this model can effectively addresses the turning of vehicle impact on link duration prediction proplem. When we analyze impact of traffic lights on link duration, we use probabilty analyztion method in fourth chapter, but all parameters are computed according to analsis in this chapter. We propose that EMA method and sliding window to save data according this chaper idea to enhance prediction accuration. Simulation results show that ELDP prediction has high accuracy by comparison between prediction duration and real link duration. This is enough for safe message distribution.