A vehicle routing model based on large-scale radio frequency identification data

The rapid development of sensing, computing, and wireless communication techniques has given rise to an increasing number and increasing availability of high-resolution data that record real-time traffic information. In this study, radio frequency identification (RFID) data collected in Nanjing (a major city in southern China) were used to estimate dynamic travel demands and develop an RFID data-based vehicle routing model that simultaneously considers individual benefits and social good. The proposed vehicle routing model also used information regarding driver origins that contribute to major congestion; therefore, the routing model can be applied to a group of targeted vehicles only, providing more adaptive, efficient, and feasible routing strategies to mitigate traffic congestion.