# A Routing Algorithm Based on Real-Time Information Traffic in Sparse Environment for VANETs
## 1 Introduction  
Over the past few decades, due to the fast development of the social economy and wireless communication technology, the existing road infrastructure and equipment have been unable to meet the safety and entertainment requirements of vehicles. As the next generation of the transportation system, intelligent transportation system (ITS) undertakes the task of improving road congestion, reducing traffic accidents and providing entertainment services. Vehicular Ad Hoc Networks (VANETs) are the keystone for enhancing roads users' safety and comfort [1; 2; 3; 4; 5]. The concept of VANETs comes from the mobile ad hoc network (MANETs), VANETs combines wireless communication with the vehicle driving scenarios to enable the mutual communication between vehicle nodes [6; 7; 8; 9]. Although there are many similarities between MANETs and VANETs, the specific characteristics of the vehicle motion model make VANETs have more problems and challenges [10; 11]. For instance, the high mobility of vehicles makes frequent changes in the topology of network in VANETs, resulting indifficulties in routing table maintenance and poor node connectivity. The vehicle can only drive in one direction and may meet traffic jams or emergency accidents, these conditions will cause the communication status between vehicle nodes to be extremely complicated. For decades, many researchers have made their own contributions in the design of routing protocol for VANETs and proposed different routing algorithms [12; 13; 14; 15; 16; 17]. Some of them are classified as topology-based, cluster-based, position-based, broadcast-based, and infrastructure-based. By comparison, location-based routing represents a promising scheme in vehicular environments as it supports geographical position information of each vehicle to offer routing. When a source node starts to send packets to the destination node, the route path has not been determined because the relay node is calculated from the location information of itself, neighbors, and the destination. Nodes neither maintains the routing table nor establishes the global path between source and destination. This routing scheme can better adapt to frequent topology changes. However, these location-based routing protocols have certain limitations. The connectivity of the nodes is not taken into account in the routing algorithm, which is magnified in sparse scenarios. To overcome this problem, many new routing algorithms have been proposed. Some of them use Road Side Units (RSU) to make statistics on the road conditions, such as traffic volume, road connectivity, etc. Although RSUs can be used to solve such problems and facilitate communication among vehicles, the deployment of these units entails a high cost. Another solution is to use maps to obtain road and intersection information. There are already some commercial maps available, such as Google, Ali, and Tencent. However, commercial maps cannot provide excellent real-time performance. In some places, the network connection of these maps will be disconnected, and sometimes the latest map information may not be updated for various reasons. The other protocols that consume network resources and obtain information on vehicular density generate additional overhead. On the other hand, in the transmission process of the current node and relay node, packet loss often occurs due to node mobility and channel loss. For example, the receiver may leave the wireless communication transmission range of the sender before receiving the packets totally. Therefore, appropriate routing should consider both packet loss and node connectivity in the decision-making process. In this paper, we propose a relay selection algorithm exploiting hello message exchanged between vehicles, and combining several parameters in order to improve the packet loss rate and end-to-end delay performance in sparse scenarios. A new network parameter named effective information traffic is proposed in this paper which is used to assist routing decisions for reducing routing redundancy.