In this paper, the calculation method of the link travel time is firstly analysed in the continuous traffic flow by using the detection data collected when vehicles pass through urban links, and a theoretical derivation formula for estimating link travel time is proposed by considering the typical vehicle travel time and the time headway deviation upstream and downstream of the links as the main parameters. A typical vehicle analysis method based on link travel time similarity is proposed, and the theoretical formula is optimized, respectively. Then, an estimation formula based on maximum travel time similarity and an estimation formula based on maximum travel time confidence interval similarity are proposed, respectively. Finally, when analysing the fitting conditions, the collected data from urban roads in Nanjing are used to verify the proposed travel time estimation method based on the radio frequency identification devices. The results show that time headway deviation converges to zero when the hourly vehicle volume is more than 20 veh/h in the certain flow direction, and there are more positive and negative fluctuations when the hourly vehicle volume is less than 10 veh/h in the certain flow direction. The accuracy of the proposed improved method based on typical vehicle travel time estimation is significantly improved by considering the typical vehicle travel time, and typical vehicles on the road segment mainly exist at the tail of the traffic platoon in the corresponding period.

Radio Frequency Identification (RFID) plays an important role on road traffic management and basic data could be collected from automotive electronic registration identifications, which could be applied for road traffic management and planning. Firstly, road section volume-time function was discussed in the paper, and then urban road RFID data collected from the city of Nanjing were analyzed with mature methods on identifying redundant and wrong data based on license plate number. Then the function from Bureau of Public Road (BPR) was calibrated to get the basic volume-time function with RFID data, and the basic function was improved based on the time periods, and the improved functions were used to describe relationships between volume and travel time in weekdays and weekends, and the fitting effect is compared with the basic function. It was indicated that the fitting effort R2 was increased by 40% at least. The results can provide reference and support for urban road traffic planning.