Improve Traffic Management in the Vehicular Ad Hoc Networks by Combining Ant Colony Algorithm and Fuzzy System

Abstract

Abstract-Over the last years, total number of transporter has increased. High traffic leads to serious problems and finding a sensible solution to solve the traffic problem is a significant challenge. Also, the use of the full capacity of existing streets can help to solve this problem and reduce costs. Instead of using static algorithms, we present a new method, ACO algorithm, combine with fuzzy logic which is a fair solution to improve traffic management in the vehicular ad hoc networks. We have called this the Improved Traffic Management in the Vehicular ad hoc networks (ITMV). Proffer method combines the map segmentation and assign to one server, calculate the instantaneous state of the traffic in roads with use fuzzy logic and distribute traffic for reduce traffic as much as possible by less time priority rather than shorter route. This method collects the vehicles and streets information to calculate the instantaneous state of the vehicle density. The proposed method through simulations were compared with some existing methods and in terms of speed, travel time and reduce air pollution improved by an average of 36.5%, 38%, 29% ,Respectively.

Modeling Ant Colony Optimization for Multi-Agent based Intelligent Transportation System

“…Thus, we simulated the ITMS in pragmatic style with a micro traffic, open source traffic simulation model (SUMO), and solved the challenges related to modeling and simulation for ITMS. Article in [6] also present a similar approach to solve the traffic management problem. However, they used fuzzy logic and ACO on one attribute (# of vehicles on a road segment) only to detect congestion amount of a particular road segment.…”

“…In addition, counting # of vehicles in a segment is easy to find in simulation environment but difficult in real scenarios. Because the process requires instantaneous congestion detection method, which is not discussed in [6]. We also did a comparative study with other methods and implemented a low-cost but flexible ITMS method in [20][21] [22].…”

“…In addition, a central server approach (for data uploading, processing, and sending results back to the server) was proposed in [6] and all our previous works [11] [30]. However, central server approach will create great pressure on the network for large number of sensors or IoT devices and massive data processing situations.…”

Solving Traffic Routing System using VANet Strategy Combined with a Distributed Swarm Intelligence Optimization

“…The proposed mobile application is easy to use and helps the driver to be informed by the state of the route periodically (at each minute). Khodadadi et al (2016) presents a new method that combines the fuzzy logic with the ACO algorithm to improve traffic control in the VANET network. The proposed method prepares a map segmentation and dynamically calculates the state of traffic at each intersection based on the fuzzy logic combined with distributed traffic, as it aims to reduce the traffic as much as possible (calculating by duration rather than the shortest routes).…”