Abstract
The Internet of Vehicles (IoV) is the extension of the Internet of Things (IoT) technology in the field of transportation systems. Ride-sharing is one of intelligent travel applications in IoV. Ride-sharing is aimed at taking passengers with similar itineraries and time arrangements to travel in the same car according to a certain matching rule. To effectively integrate transport capacity resources and reduce the number of cars on the road, ride-sharing has become a popular and economical way of travel. The matching and optimizing of drivers and passengers are the core contents of a ride-sharing application system. This paper mainly studies the dynamic real-time matching of passengers and drivers in IoV, considering the main factors such as travel cost, car capacity, and utility. The matching problem is formulated in a ride-sharing system as a Role-Based Collaboration (RBC). A new utility method for the matching optimization of ride-sharing is present. In this paper, we establish a model for simulating the assignment of ride-sharing with the help of the Environments-Classes, Agents, Roles, Groups, and Objects (E-CARGO) model. The objective function and formal definitions are proposed. The utility and time of optimal matching are obtained by using the Kuhn-Munkres algorithm on the revenue matrix. The experimental results show that the proposed formal method based on the E-CARGO model and utility theory can be applied in the ride-sharing problem. Numerical experiments show that the matching time cost increases with the increase of the number of drivers and passengers participating in the ride-sharing system. When the number of drivers and passengers is different, one-to-many matching takes the least time, and one-to-one matching takes more time. When the number of drivers and passengers is the same, the time cost of one-to-one matching increases sharply with a certain value (bigger than 800). Compared with other matching methods, the time spent by the one-to-many method is reduced by 30%. The results show that the proposed solution can be applied to the matching and pricing in a ride-sharing system.
Highlights
The Internet of Vehicles (IoV) is a huge and interactive network composed of vehicle locations, speed, routes, and other information
With the development of economy, the number of private cars is increasing in cities. It is convenient for travel with the increase of urban car, it brings a series of problems, such as traffic congestion, excessive consumption of oil resources, and environmental pollution
(1) We propose a new utility method for the ridesharing matching based on the E-CARGO model with utility and seat number constraints
Summary
The Internet of Vehicles (IoV) is a huge and interactive network composed of vehicle locations, speed, routes, and other information. In a ridesharing application system, it matches the passenger sending the ride request with the nearby driver whose car has vacant seats. In case of one driver and many passengers, when the driver’s car still has vacant seats, some passengers with similar paths will be assigned to travel together according to a certain matching strategy. According to the matching strategies and core factors affecting passengers’ choice of travel in a ride-sharing application system, the specific contributions of this paper are shown as follows. When the number of drivers and passengers is different, the utility of one-to-one matching is the least (3) The experiments present that the utility has an impact on the revenue in a ride-sharing system.
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