Abstract
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.
Highlights
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
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. e 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. e 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
The calculation method of the LTT is analysed in the continuous traffic flow by using the detection data collected when vehicles pass through urban links from RFID collections, and a theoretical derivation formula for estimating link travel time is proposed by considering the typical vehicle’s travel time and the fluctuation of the time headway upstream and downstream of the links as the main parameters, namely, LTT is decomposed into two parts including typical vehicle travel time and time headway deviation, and two parts have been discussed with actual data
Summary
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. For different data collection methods and data analysis purposes, the data collected by continuous movement methods such as floating car data (taxi) or GPS data [6, 7] can be used to extract travel patterns, such as the floating car or typical vehicle travel time, the waiting time at the node to detect the incident [8], and the OD travel path in the network, but the sample data come from the special vehicles; for fixed collection methods such as video and microwave collection, and the use of radio frequency technology to collect the identity information of the vehicle, the data of the full sample on the road can be obtained, and the objects of collection and analysis can focus on the road operation characteristics, such as the traffic flow volume, speed, headway of the collection node, or the link travel time. We intend to use electronic vehicle license plate data from continuously collection between road segments and extract the license plate information to obtain road travel time information and time headway information
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