Intersection Routing Based on Fuzzy Multi-Factor Decision for VANETs

Abstract

Vehicular ad hoc network (VANET) is a special form of mobile ad hoc network (MANET), which plays a key role in the intelligent transportation system (ITS). Though many outstanding geographic routing protocols are designed for VANETs, a majority of them use parameters that only affect routing performance. In this article, we propose an intersection routing based on fuzzy multi-factor decision (IRFMFD), which utilizes several features. The scheme is divided into two parts, namely vehicular decision management and intersection decision management. In the vehicular component, candidate vehicles between two static nodes (SNs) located at two intersections derive potential routing paths considering distance, neighbor quantity, and relative velocity. In the intersection component, the candidate SN was chosen from the current intersection’s 2-hop neighbors which were connected with the current intersection by a route that was decided on in part one. To get the best scheme, we also introduced other factors to estimate the number of hops in each link and link lifetime. The simulation shows that the IRFMFD outperforms on delivery ratio and end-to-end delay compared with AODV (Ad hoc on-demand distance vector), GPSR (Greedy perimeter stateless routing) and GeOpps (Geographical opportunistic routing).

Hierarchical traffic light-aware routing via fuzzy reinforcement learning in software-defined vehicular networks

“…Then it would consider the channel condition, distance to destination, and queueing delay in prioritizing neighbor nodes for selecting the next-hop nodes. Zhou et al [28] proposed a multiple intersection selection routing called MISR, which modeled the intersection selection as an optimization problem. It selected the intersection with minimum delay and highest connectivity by considering traffic light conditions.…”

“… Transmission of CP packets at intersections such as ITAR-FQ [31] requires updating periodically, which increases latency and overhead, especially at high densities or high traffic loads.  Routing decision-making based on the local knowledge or two-hop neighbor's information due to the restricted view of vehicular topology leads to nodes trapped into the local maxima problem resulting in degradation of data routing efficiency [25][26][27][28][29][30][31][32].  Regardless of road constraints and traffic light conditions, routing efficiency would be restricted.…”

“… Regardless of road constraints and traffic light conditions, routing efficiency would be restricted. The traditional routing methods, including TLRC [25], STAR [26], GTLQR [27], and MISR [28], considered the effect of traffic lights during the local selection of intersections. However, traffic light effects in SDN-enabled vehicular networks should be considered while selecting a sequence of intersections in the data routing process.…”

“…The performance evaluation of our HIFS scheme is discussed in this section in various scenarios compared to the different state-of-the-art methods, including real-time evaluation of road conditions using CP packets (e.g., ITAR-FQ [31]), traffic light aware strategy (e.g., MISR [28]), and SDN-enabled routing scheme (e.g., GLS [16]). Details of these methods for selecting intersections and relay nodes are described in Section 2.…”

Optimal Shortest Path Selection Base on Multi-Criteria Decision Making in Vehicular Ad Hoc Network

“…The non-safety-related application can be further subdivided into (Hua et al, 2017). Nearest vacant car park, Convenient store., Shopping mall, Hotel, Hospital, And Petrol station and many more (Cao et al, 2020;R. Hussain et al, 2020).…”