VANET Case Study

3. MOBILITY MODELS
VANET can have both dynamic and static nodes. The dynamic nodes are vehicles, cars and motorbikes. On the other hand, the static nodes are the fixed equipment along the roads. Both types of nodes are participating in the routing process that includes route discovery, route maintenance and packet forwarding. The high mobility of movable nodes has an unfavorable impact in the network performance. Therefore, it is highly required to study the mobility models for VANET, and the effect of these models on VANET communication protocols. In the literature, several mobility models are proposed for VANET. To this end, this section presents a taxonomy and description of VANET mobility models. Initially, the factors that influence the mobility pattern in VANETS are summarized at what follows [16 -18]:
• Layout of streets: Vehicles’
Classification of Synthetic Mobility Models [26]
3.1.2 Survey-based Models. In order to model the human behavior in vehicular network, the survey-based models are used. Hence, Gathering data related to behavior, speed, paths and actions of drivers and Pedestrians. Then, these data can be used to develop a realistic model. The UDel mobility model [27] is a survey-based tool that simulates urban networks. However, the human behavior can be different due to region, laws, culture and ethics. Consequently, the surveys should be done repeatedly and in a different regions and times to assure the reality and accuracy of the gathered data.
3.1.3 Trace-based Models. In contrast to develop a mathematical models and then validating them using mobility traces or surveys, a mobility models can be extracted directly from movement traces. Several models have been proposed using this approach such as Cabspotting [4], CrawDaD [28], UMASSDieselNet [29], MIT Reality Mining [30], or USC MobiLib [31]. Additional feature of this approach is the ability to predict mobility patterns not included in the traces using complex mathematical