RESEARCH ARTICLE Predictability of Road Traffic and Congestion in Urban Areas

Mitigating traffic congestion on urban roads, with paramount importance in urban develop-ment and reduction of energy consumption and air pollution, depends on our ability to fore-see road usage and traffic conditions pertaining to the collective behavior of drivers, raising a significant question: to what degree is road traffic predictable in urban areas? Here we rely on the precise records of daily vehicle mobility based on GPS positioning device in-stalled in taxis to uncover the potential daily predictability of urban traffic patterns. Using the mapping from the degree of congestion on roads into a time series of symbols and measur-ing its entropy, we find a relatively high daily predictability of traffic conditions despite the ab-sence of any priori knowledge of drivers ' origins and destinations and quite different travel patterns between weekdays and weekends. Moreover, we find a counterintuitive depen-dence of the predictability on travel speed: the road segment associated with intermediate average travel speed is most difficult to be predicted. We also explore the possibility of re-covering the traffic condition of an inaccessible segment from its adjacent segments with re-spect to limited observability. The highly predictable traffic patterns in spite of the heterogeneity of drivers ' behaviors and the variability of their origins and destinations en-ables development of accurate predictive models for eventually devising practical strategies to mitigate urban road congestion