A new ridesharing model called collaborative activity-based ridesharing is proposed to enhance not only overall matching rates but also the matches between preferred ride partners. By coalescing the merits of two rece...
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A new ridesharing model called collaborative activity-based ridesharing is proposed to enhance not only overall matching rates but also the matches between preferred ride partners. By coalescing the merits of two recently suggested innovative ridesharing models - the social network-based ridesharing and the activity-based ridesharing the new model leverages people's preference to their social networks and the space-time flexibility of daily activities to improve the matching outcome. The capabilities and advantages of the proposed model are justified by a group of agent-based simulations in a realistic study area. The influence of geography on the match outcome is discussed in particular.
ridesharing is an emerging travel mode that reduces the total amount of traffic on the road by combining people's travels together. While present ridesharing algorithms are trip-based, this paper aims to achieve s...
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ISBN:
(纸本)9781450345897
ridesharing is an emerging travel mode that reduces the total amount of traffic on the road by combining people's travels together. While present ridesharing algorithms are trip-based, this paper aims to achieve significantly higher matching chances by a novel, activity-based algorithm. The algorithm expands the potential destination choice set by considering alternative destinations that are within given space-time budgets and would provide a similar activity function as the originals. In order to address the increased combinatorial complexity of trip chains, the paper introduces an efficient space-time filter on the foundations of time geography to search for accessible resources. Globally optimal matching is achieved by binary linear programming. The ridesharing algorithm is tested with a series of realistic scenarios of different population sizes. The encouraging results demonstrate that the matching rate by activity-based ridesharing is significantly increased from the baseline scenario of traditional trip-based ridesharing.
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