## 2 Related Works  
VANETs are an indispensable foundation of modern intelligent transportation. The special characteristics of VANETs such as high mobility, frequent network disconnections, frequent topology changes, uncertainty distribution of vehicles, and insufficient power supply differentiate them from MANETs. Thus, traditional MANET routing protocols are not suitable for VANETs, while routing continues to be one of the challenges in VANETs. The Destination-Sequenced Distance-Vector Routing (DSDV) [9] algorithm uses a serial number mechanism to distinguish the new and old degree of routes, only with the highest number of routes at a time, and the optimal route is selected if there are two routing serial numbers (for example, the shortest number). Ad hoc On-demand Distance Vector Routing (AODV) [10] is combined with the advantages of DSDV and support the multicast routing and improve network service quality. Nonetheless, DSDV and AODV have a notable disadvantage: they have no support for single-channel work, which will have a poor performance in a condition where network topology changes are faster. In some studies, OLSR [11] performed better than AODV via using a number of overhead packets to send messages from the source vehicle to the destination vehicle. Dynamic Source Routing (DSR) [12], as an on-demand algorithm, is also not appropriate for VANETs. It employs source routing other than depending on a transitional node routing table. However, its expansibility is largely limited. The multicast with ant colony optimization for VANETs based on MAODV (MAV-AODV) protocol [13] is based on the Multicast Ad hoc On-Demand Distance Vector (MAODV) [14] protocol and principles of the ant colony optimization (ACO). It is intended to improve the multicast structure life cycle and to realize the more efficient packet delivery with minimal transmission and management overheads. The M-AODV+ (an extension of the AODV+ routing protocol for supporting vehicle-to-vehicle communication) [15] routing protocol achieved high reliability in V2V communication; when it is impossible to realize multi-hop or single-hop communication in ad hoc networks, it creates another communication link between vehicles. The MAR-DYMO [16] based on the ACO is applied to unicat routing in MANETs. It exploits the advantage of the DYMO [17] routing to regulate the behavior of ants, and chooses the best path and the most appropriate range of fault prevention. In some works, ant colony systems are applied to multicast routing optimization for wireless ad hoc networks based on mesh structure. For the DCMP, it is constantly looking for shorter routes (based upon the principles, they possess more pheromone) to accommodate these new best routes' mesh-based structures. Others have presented improvements to MAODV, such as considering the node mobility in the failure prediction [18], improving the multicast route's repair, or routing decision in dynamic node fluctuation environment. [PERSON] et al. proposed a routing protocol based on the predictive motion trajectory (movement prediction-based routing, MOPR) [19]. It is used to improve the GPSR [20] protocol, which takes the position, movement direction, and speed of the vehicles into consideration for routing path selection. Most of the previous vehicle communication studies have been limited to one-hop or few-hop communications [21], mainly to communicate with nearby upstream traffic vehicles to avoid collision [22; 23]. Meanwhile, it is also very crucial to send data from a vehicle to a destination severeal miles away through multi-hop relay with multiple intermediate vehicles. Therefore, a multi-hop routing protocol is needed in a large vehicular network. VADD [8] and MDDV (mobility-centric data dissemination algorithm for vehicular networks) [24] are two multi-hop routing protocol in VANETs. In VADD and MDDV, road act as a link where data delivery depends upon the density of vehicles off the road. Therefore, data will be delivered along the shortest-delay path to the destination.