Efficient vehicle routing optimization for autistic users / Abdulrahman Hasan Mohammed Shabalah - Abdulrahman Hasan , Mohammed Shabalah (2020)
In recent years, daily life without a vehicle would be impossible. As an inevitable result, the number of vehicles on the road increases day by day in various large cities around the world. The increased number of vehicles is a big concern because it causes a lot of traffic congestions, especially during peak hours. Besides, there has been a rapid rise of on-demand Ride-Hailing Services (RHSs), such as Grab, Uber, EzCab, and MyCar, etc. This allows passengers with smartphones to place trip requests and assign them to drivers according to requester’s location and drivers' availability. In consequence, efficient routing algorithms are needed for the sake of enhancing the availability of car-resources. Even though there is an emerging number of RHS applications, there is a lack in their algorithms to tackle the issue of the special characteristics for the autistic users’ requirements. Therefore, in this research, a routing algorithm for ride-hailing services has been proposed. The new proposed algorithm is called Autistic-Features Ant Colony (AFAC). This proposed algorithm utilizes the Ant Colony Optimization (ACO) with autistic features to enhance the efficiency and performance of the overall system and the autistic user's satisfaction in ride-hailing services. AFAC considers the road and the autistic features simultaneously to find the optimum route for the autistic user. While the road features play a vital role in finding the optimum route from nearby car-resources to the autistic user, the autistic features help to make a better selection of car-resources in terms of providing autistic users with specialized drivers who can deal with them. Simulation experiments have been conducted using the Unity game engine to analyse the effect of these features on the performance of the overall system. AFAC is designed based on client-server architecture, which includes both the server-side and the client-side parts. The communication between the client and the server is made by requesting the Hypertext Transfer Protocol (HTTP). The Simulation results were obtained by measuring the performance of three algorithms named Ant Colony, A Multiple Parameter control for Ant Colony (MPAC), and the proposed AFAC. The design and analysis of the comparison have been done using MATLAB tool. The experimental results showed that the performance of the proposed AFAC algorithm outperformed the classical Ant Colony and the recent MPAC algorithms.