Do you often complain about taxi (yes, we always do)?
Well, your trouble may be ending now. A paper, presented at the First Workshop on Pervasive Urban Application summarized on the last issue of “IEEE Pervasive Computing”, shows that taxi performance in cities can be largely improved by analyzing and modeling their GPS traces. 
According to the authors, Xiaolong Li, Gang Pan, Guande Qi, Shijian Li working at the Zhejiang University, Hangzhou, China, the vacant driving time and distance can be reduced by 67% and 50% respectively by their improved Auto-Regressive Integrated Moving Average method, based on the classical Box-Jenkins approach. The result has been obtained by modeling a large sample of taxi GPS traces collected in Hangzhou. Such a performance, if confirmed by further tests, would drastically reduce the environmental impact of taxis and the costs for taxi drivers, which would reflect on lower fees for taxi users.
