Abstract
Carpooling consists of sharing individual vehicle space among people with comparable trajectories. Although there are some software initiatives to help carpooling practice, none of them really implements features similarly to searching for people with similar trajectories and profile. In this study, we propose an innovative approach to generate clusters of users that share similar trajectories and profile for carpooling purposes based on Optics, K-means algorithm and ensemble learning. First, we provide a proper definition of fundamental elements of the carpooling context in order to contribute to a standardization of the concerning nomenclatures. Next, we perform four different experiments for the purpose of showing the feasibility of the approach. We also contribute to the construction of a real dataset (donated to UCI), properly depicted, used in two of these experiments. Results with Davies-Boulding index indicate that the generated clusters are feasible to the design of a carpooling recommendation system. Time performance evaluation of the approach has been also performed for both dynamic program analyses via software profiling method and time complexity analysis according to Big O notation.
Highlights
Traffic jams are a serious concern in metropolitan areas (He et al, 2012)
Carpooling is a typical solution used by some nations to avoid the problems generated by the increase traffic condition
This paper aims to extend the work of (Cruz et al, 2015) along three axes: (i) Propose (semi-formal definition of the elements of the carpooling context, towards a standardized nomenclature, (ii) Add users’ profiles to the clustering approach and (iii)
Summary
Traffic jams are a serious concern in metropolitan areas (He et al, 2012). Economic losses, health issues and environmental damages are some of the known consequences (Resende and Sousa, 2009; Currie and Walker, 2010; Levy et al, 2010; Hart et al, 2009). In Beijing, China, the government has adopted these solutions to solve the problem of the one worst traffic in the world. It is a solution, the traffic is still critical in peak hours. Carpooling (share individual vehicle space among people with similar destinations) is a typical solution used by some nations to avoid the problems generated by the increase traffic condition. This solution is strongly related to some cultural aspects (Gowri, 2008; Matos et al, 2014). There are plenty of vehicles with just the driver inside (Ghoseiri et al, 2011)
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