Internet of Things-based Traffic Management System for Maseru, Lesotho.

Abstract

The number of vehicles in Maseru has been steadily increasing, leading to heightened intensity of congestion and traffic occurrences. This is further exacerbated by ineffective solutions that are currently in place as well as the absence of tools that facilitate dispersal of information to motorists. Traffic lights have been put in place to manage flow of traffic but are becoming increasingly inefficient due to their design. The preset timing cycles between green, amber and red disregarding prevailing conditions leads, inter alia, to increased wait times, use of additional fuel and air pollution. In addition, lack of equipment that is able to provide motorists with information about prevailing road conditions further increases the possibility of one being stuck in traffic. To make traffic management more efficient at signaled junctions, the implementation of the Internet of Things (IoT) paradigm is used to create intelligent traffic management systems such as Wireless Sensor Networks (WSN) and fuzzy algorithms to intelligently decide the phases of traffic lights. Road density and vehicles’ speeds are collected from the road infrastructure using cameras and are passed to a fuzzy algorithm to determine how congested a road is. Dependent on these parameters, the algorithm will also determine which roads should be given highest priority while maintaining a degree of fairness, thus optimizing traffic flow. In addition, the ubiquitous provision of road condition information to motorists in various formats such as text and audio is also used. This feature allows for the acquisition of the latest road status, thus making it possible to find alternative routes. The unique feature in this project is the ability to collect road parameters from the road infrastructure itself, using WSN as well as crowd source data from road users using mobile devices. A study conducted in this research revealed a relationship between the number of cars on a road and concentration of Carbon Dioxide (CO2); the results showed that as the number of cars increases, so does the measure of CO2. Questionnaire-based surveys showed that Maseru citizens have noted an increase in congestion which they attributed to the increase in number of vehicles on the road that is not met by the increase or improvement in road infrastructure. The respondents in this survey also noted limited mechanisms that provide them with road conditions and highlighted that such tools may alleviate congestion. The performance of intelligent traffic lights was conducted via simulations compared with fixed cycle traffic lights. From the simulations it was observed that IoT- based traffic management systems reduced the wait times of vehicles at signaled junctions which would also result in reduction of the pollutant CO2. It is envisaged that the future implementation will include the ability to manage a network of junctions and ability to predict abnormal traffic flows.