Abstract

Recently, rates of vehicle ownership have risen globally, exacerbating problems including air pollution, lack of parking, and traffic congestion. While many solutions to these problems have been proposed, Carpooling is one of the most effective solutions to this problems Recently, several carpooling platforms have been built on cloud computing systems, with originators posting online list of departure/arrival points and schedules from which participants can search for rides that match their needs. In this paper, an improved carpool system is described in detail and called the improved intelligent carpool system (IICS), which provides car poolers the use of the carpool services via a smart handheld device anywhere and at any time. This IICS Consist the geographical, traffic, and societal information and used to manage requests and find minimum route. We apply advanced genetic-based carpool route and matching algorithm (AGCRMA) for this multiobjective optimization problem called the carpool service problem (CSP).

Authors and Affiliations