# Adaptive Multi-Path Routing Protocol in Autonomous Vehicular Networks
## 1 Introduction  
Vehicle-to-vehicle (V2V) communication in autonomous driving is an essential technology to enable driver safety and traffic efficiency [1; 2; 3; 4]. For example, consider the domain of autonomous driving, where precise vehicle localization demands stringent latency requirements [5]. Furthermore, automated navigation systems, which rely on real-time map and traffic information, necessitate minimum throughput for seamless operation [6]. Here, autonomous vehicles can communicate with each other via ad hoc communications, which does not require infrastructure support [7]. However, due to the limited transmission range of wireless interfaces, the vehicles in vehicular networks may need multi-hop transmissions to communicate with each other. In recent years, many routing protocols have been developed to solve the multi-hop routing problem in vehicular ad hoc networks [8; 9; 10; 11; 12; 13]. Conventional routing protocols take the minimum hop count (min-hop) as the metric for routing. In a single-rate physical environment, min-hop corresponds to the minimum number of transmissions, thus achieving throughput increase, small delay, and low power consumption. The recent development of wireless devices such as 802.11 ax/be standards [14; 15] enables high-bandwidth multi-rate capability. In multi-rate physical environments, min-hop routing may cause throughput loss and reliability loss [16]. Figure 1 shows an example of a vehicular ad hoc routing using min-hop as the metric. We can easily see that the min-hop metric normally chooses long distance links. This means that the link's channel quality is poor, and thus it operates at a low data rate. This results in a large amount of medium time to transmit data, which in turn causes the overall network throughput todecrease. Long-distance links may also cause high bit-error rate (BER), in other words, reliability loss due to the path loss. However, using high-data-rate links does not always produce a higher throughput. There is a strict trade-off between the data rate and the transmission range. The long distance range transmissions must operate at a low data rate while high-data-rate transmissions must run on a short distance range. Accordingly, by selecting high-data-rate links, the ad hoc routing protocol must suffer from an increased number of hops. This tradeoff creates a more complex problem in multi-rate-aware routing protocols. Furthermore, the packet size is an important factor in selecting the adequate path in multi-rate environments. Since the IEEE 802.11 medium access control (MAC) protocol [17] always spends a certain amount of medium time on the fixed physical (PHY) and MAC overhead, the effective throughput is lower than the physical data rate. Due to this fact, the data rate does not affect much on the throughput of small data packets compared to the large ones. This shows that the adequate path may differ according to the packet size. In this paper, we propose a high throughput routing scheme called multi-path ad hoc routing protocol for vehicular networks, in short MARV. MARV makes three key contributions. First, MARV searches for high throughput paths using an on-demand routing searching algorithm so that the routing is more effective compared to other multi-rate-aware schemes, which are based on proactive routing [16; 18; 19]. Here, MARV searches for multiple high-throughput paths while limiting the control overhead. Second, MARV searches for multiple paths to maintain both min-hop and high-throughput paths to select the adequate path depending on the flow size. Third, we conduct extensive experiments to show that MARV outperforms the previous methods in terms of throughput, end-to-end delay, and control overhead. The remainder of this paper is organized as follows. We briefly review previous work related to multi-rate-aware MAC and ad hoc routing protocols in Section 2. We discuss the main motivation of this paper in Section 3, and then in Section 4, we present the effectiveness of MARV and describe it in detail.