A Method to Suggest Alternative Routes Based on Analysis of Automobiles' Trajectories

Inexperienced drivers usually use the most-known paths to move inside the cities, while drivers with a better knowledge of the road network normally taken alternative routes that are shorter, faster or safer. This knowledge about roads usage, when shared with other drivers, could offer more paths options to distribute the traffic load across the city by suggesting alternative routes. However, the problem lies in how to suggest alternative route directions for ordinary drivers considering knowledge gathered from experienced drivers. In order to try to solve this problem, it is proposed an algorithm, named TODS - Trajectory Outlier Detection and Segmentation, to group and segment car road trajectories in standard and alternative routes based on city roads usage in different day times periods. After that, the segmentation results are suggested as driving directions for ordinary drivers. To evaluate the results was performed a qualitative comparison with TRA-SOD algorithm considering the segmentation process. The tests were executed using two trajectories datasets collected by drivers in San Francisco - USA and Joinville - Brazil. The results assessment indicate that TODS is superior to TRA-SOD due to its segmentation characteristics. Besides that, it has been observed that the time period of the day influences how routes are used along the day.