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Generalized multipath planning model for ride-sharing systems

Frontiers of Computer Science 2014年第1期8卷 100-118页

作者： Jamal YOUSAF JuanziLI Lu CHEN Jie TANG Xiaowen DAI Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 China. General Motors China Science Lab Shanghai 201303 China

Ride-sharing systems should combine environ- mental protection （through a reduction of fossil fuel usage）, socialization, and security. Encouraging people to use ride- sharing systems by satisfying their demands for safety, pri- vacy and convenience is challenging. Most previous works on this topic have focused on finding a fixed path between the driver and the riders either based solely on their loca- tions or using social information. The drivers＇ and riders＇ lack of options to change or compute the path according to their own preferences and requirements is problematic. With the advancement of mobile social networking technologies, it is necessary to reconsider the principles and desired character- istics of ride-sharing systems. In this paper, we formalized the ride-sharing problem as a multi source-destination path plan- ning problem. An objective function that models different ob- jectives in a unified framework was developed. Moreover, we provide a similarity model, which can reflect the personal preferences of the rides and utilize social media to obtain the current interests of the riders and drivers. The model also al- lows each driver to generate sub-optimal paths according to his own requirements by suitably adjusting the weights. Two case studies have shown that our system has the potential to find the best possible match and computes the multiple opti- mal paths against different user-defined objective functions.

关键词： ride-sharing path planning dynamic optimiza-tion

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