| Title |
Forecasting of Motorway Path Travel Time by Using DSRC and TCS Information |
| Authors |
장현호(Chang, Hyun-ho) ; 윤병조(Yoon, Byoung-jo) |
| DOI |
https://doi.org/10.12652/Ksce.2017.37.6.1033 |
| Keywords |
대용량 자료;고속도로;출발지기준 경로통행시간;k-최근린 이웃 Big data;Motorway;Departure time based path travel time;TCS;DSRC;k-Nearest Neighbor |
| Abstract |
Path travel time based on departure time (PTTDP) is key information in advanced traveler information systems (ATIS). Despite the necessity, forecasting PTTDP is still one of challenges which should be successfully conquered in the forecasting area of intelligent transportation systems (ITS). To address this problem effectively, a methodology to dynamically predict PTTDP between motorway interchanges is proposed in this paper. The method was developed based on the relationships between traffic demands at motorway tollgates and PTTDPs between TGs in the motorway network. Two different data were used as the input of the model: traffic demand data and path travel time data are collected by toll collection system (TCS) and dedicated short range communication (DSRC), respectively. The proposed model was developed based on k-nearest neighbor, one of data mining techniques, in order for the real applications of motorway information systems. In a feasible test with real-world data, the proposed method performed effectively by means of prediction reliability and computational running time to the level of real application of current ATIS. |