V2VR: Reliable Hybrid-Network-Oriented V2V Data Transmission and Routing Considering RSUs and Connectivity Probability

TLDR

Vehicular ad hoc networks are widely used in intelligent transportation systems, yet their self‑organizing multi‑hop wireless nature demands efficient and reliable routing, and wired networks offer higher reliability and bandwidth. The study proposes a reliable VANET routing decision scheme that integrates roadside units into both wireless and wired modes using the Manhattan mobility model to optimize data transmission. The scheme analyzes vehicle mobility and connectivity, applies an improved greedy algorithm for wireless communication, incorporates a wired RSU network, and uses a probabilistic model to evaluate connectivity across various transmission ranges. Experiments demonstrate that the proposed method improves real‑time planning and network transmission performance over baseline protocols in terms of packet delivery ratio, delay, and wireless hops.

Abstract

Vehicular ad hoc networks (VANETs) have been widely used in intelligent transportation systems (ITSs) for purposes such as the control of unmanned aerial vehicles (UAVs) and trajectory prediction. However, an efficient and reliable data routing decision scheme is critical for VANETs due to the feature of self-organizing wireless multi-hop communication. Compared with wireless networks, which are unstable and have limited bandwidth, wired networks normally provide longer transmission distances, higher network speeds and greater reliability. To address this problem, this paper proposes a reliable VANET routing decision scheme based on the Manhattan mobility model, which considers the integration of roadside units (RSUs) into wireless and wired modes for data transmission and routing optimization. First, the problems of frequently moving vehicles and network connectivity are analyzed based on road networks and the motion information of vehicle nodes. Second, an improved greedy algorithm for vehicle wireless communication is used for network optimization, and a wired RSU network is also applied. In addition, routing decision analysis is carried out in accordance with the probabilistic model for various transmission ranges by checking the connectivity among vehicles and RSUs. Finally, comprehensive experiments show that our proposed method can support real-time planning and improve network transmission performance compared with other baseline protocol approaches in terms of several metrics, including package delivery ratio, time delay and wireless hops.