Social Sensing Enhanced Time Ruler for Real-Time Bus Service

Social sensing helps realize the real-time prediction of bus routes by perceiving social events and evaluating their influence on the time when a bus passes through a road section. This paper proposes a social sensing enhanced real-time bus service that integrates sensing ability and social networks to better understand and measure social events that influence vehicle velocity. The establishment of the real-time service revolves around the PT service quality attributions PEAs and the road condition attributions PRCAs. The processes that collect bus relevant events and further categorize them into PEA events or PRCA events were proposed respectively. A method of scoring PEAs for travelers according to social events was discussed. An artificial neural network based prediction model was proposed to estimate the bus arrival time by analyzing PRCA events.

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