# A Reliable Low-Latency Multipath Routing Algorithm for Urban Rail Transit Ad Hoc Networks
## 1 Introduction
Lower latency. The vehicle-ground and vehicle-vehicle communication do not transmit data through basic network facilities but rather transmit data through trackside equipment in multiple hops, thereby reducing network latency. 4. Stronger robustness. The ad hoc network does not need a central node to control and coordinate the operation of the network and has strong invulnerability. When a node or link fails, it will repair itself or replace the path, so the failure will not affect the operation of the overall network. In recent years, ad hoc networks as a new network communication technology have been widely used in the fields of vehicular ad hoc network (VANET), wireless sensor network (WSN), flying ad hoc network (FANET), and satellite communication. Among them, routing protocols are an important part of network communication technology. Traditional routing protocols can be divided into proactive routing and reactive (on-demand) routing based on different routing strategies, and it can be divided into flat routing and hierarchical (clustering) routing according to the network topology. According to the number of paths used, it can be divided into unipath routing and multipath routing [7]. Domestic and foreign researchers have studied routing protocols mainly from the perspectives of energy, network load, link stability, and routing maintenance according to the characteristics of ad hoc networks in different fields. Ref. [8] proposed EDAODV and AODV-I protocols, where EDAODV uses a bi-directional path discovery mechanism to bypass congested nodes; the AODV-I protocol adds congestion handling to Route Request (RREQ) to avoid selecting congested paths and also adds a route repair mechanism to improve the congestion problem. A multipath strategy for the link lifecycle as well as link energy loss prediction, which effectively reduces energy consumption and latency by selecting paths with long link survival and low energy consumption, was provided in [9]. In [10], a heuristic Q-Learning algorithm was proposed for the problem of frequent network topology changes and poor link stability in VANETs, which adaptively adjusts the parameter values through continuous interaction with the external environment to find a good stable path, improving the reliability of packet delivery. In [11], to address the problem that traditional routing repair incurs huge routing overhead in terms of energy and delay, an efficient routing recovery protocol with the endocrine cooperative particle swarm optimization algorithm (ECPSOA) was proposed, which uses multi-swarm evolution equations to improve the rate of convergence and accuracy of the repair algorithm and reduces routing overhead and energy consumption. To overcome the problem of link instability in VANET, a hybrid multipath routing protocol with intelligent decisions is proposed, which can find routes quickly and uses intermediate nodes for failure maintenance, thus reducing the average routing latency and improving reliability [12]. Reference [13] proposes a method based on node residual energy and link stability, which modifies the original AODV routing protocol and adds header information on node residual energy and stability to the RREQ routing request message, enabling the selection of nodes with high stability and sufficient residual energy during the routing discovery process. Reference [14] proposes a new unmanned aerial vehicle-assisted urban VANET (VRU) based on the AI algorithm. This algorithm includes two sub-protocols for routing data and supporting the detection of malicious vehicles: the VRU_Vu protocol for data packet transmission between vehicles with the assistance of drones and the VRU_u protocol for data packet transmission between drones. In summary, there are many studies related to ad hoc network routing protocols combining the characteristics of WSN networks and VANET networks, but few studies of routing algorithms focus on ad hoc networks for urban rail transit.