Ant colony optimisation is a classic example of swarm intelligence (SI). The proposed DITS relies on ant colony optimisation. The traffic information is obtained by clustering the vehicles and using cluster-heads to obtain the traffic density within the cluster.
The system establishes a vehicular ad hoc network and uses communication among the vehicles to relay traffic status information. The agents on their own are not intelligent but working together they solve some of the most complex problems known to man. The system relies on the collective intelligence of a group of simple agents cooperating together. In this paper a distributed intelligent traffic system (DITS) operating within the framework of a multi-agent system which does not rely on historical data has been proposed. Intelligent transport systems (ITS) provide attractive methods for reducing congestion, which involves the use of modern electronic information systems to control, manage and regulate traffic flows according to inputs from traffic flow status prediction systems, through dynamic signal timings. The negative effects of congestion include, an increase in fuel consumption as a result of vehicles spending long hours in traffic and an increase in CO 2 emissions as a result of vehicles moving at much lower speeds. Traffic congestion has been a serious problem on roads around the world ever since ancient Roman times when the streets of Rome became so congested that all non-official vehicles were prevented from entering the city. This observation holds for all experiments with different traffic densities and different road network topologies. The results have shown that for various initial distributions of vehicles, the ACO-strategy obtains higher average speeds, smaller average waiting times and number of stopped vehicles than the non-ACO-strategy. Three performance parameters average speed, average waiting time of vehicles and the average number of stopped vehicles are recorded and studied for different traffic densities and road topologies. The proposed distributed intelligent traffic system (DITS) is implemented in NetLogo and experiments are conducted on two variations of the system, one with ACO, the other without ACO to investigate the impact of ACO on the solution to the traffic problem. Moreover, the information is collected and shared among the vehicles in a distributed manner. Traffic information is collected by the vehicles, rather than fixed roadside infrastructure in this system. This paper models the traffic control problem as a multi-agent-multi-purpose system (MAMP) inspired by ant colony optimisation (ACO). Status-prediction and routing services also rely on historical data and as such the accuracy of such predictions cannot be fully relied upon. IET Generation, Transmission & DistributionĬurrent traffic control systems regulate traffic flows only by switching traffic lights according to historical data.IET Electrical Systems in Transportation.IET Cyber-Physical Systems: Theory & Applications.IET Collaborative Intelligent Manufacturing.
CAAI Transactions on Intelligence Technology.
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