Research on the deployment model of intelligent highway sensor network under a bilevel programming framework - Hu, Yaoyao; Han, Tong; Wang, Peng; Wang, Liang; Zhang, Luyu; Mou, Zhenhua (Digital Transportation and Safety, 2025)
Theoretical frameworks for the strategic placement of Road Side Units (RSUs) along highways are currently insufficient. In the context of emerging Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication settings, the impact of the growing presence of smart vehicles on the existing deployment strategy has been overlooked. The current paper therefore introduces a framework for optimizing RSU placement that accounts for the influence of V2V and V2I interactions. To optimize the advantages provided by RSU, the enhancement of RSU deployment scope is realized by leveraging the relay and forwarding capabilities inherent in V2V communications, which helps identify the most efficient deployment intervals, thereby reducing costs. After ascertaining how the intelligent vehicle's transmission range affects the time taken for flooding and recognizing the influence of packet length on the sensor network's energy usage, a novel bilevel programming framework has been introduced. The upper layer model minimizes the flooding time by setting the optimal intelligent vehicle transmission radius. In contrast the lower layer model, under the influence of the upper layer model, maximizes the energy efficiency of the sensing network by setting the optimal packet length. In addition, the conventional interlinking of information and traffic flow theories is restructured for RSU placement, innovatively modeling the benefits throughout the information lifecycle. Regarding information transmission loss, a node energy loss model is determined based on the bilevel programming framework. For construction and maintenance costs, a cost model under different cluster lengths is constructed. Employing MATLAB, a study is executed to scrutinize the multifaceted interdependencies among the density of highway traffic, the saturation of intelligent vehicles, and the distribution of roadside RSUs, to establish the most advantageous spacing for RSU installations. This research lays the groundwork for the deployment of sensor networks along highways. In conclusion, the model's accuracy is confirmed by employing the Warshall algorithm and clustering routing methodologies.