A Baselined Gated Attention Recurrent Network for Request Prediction in Ridesharing

Shen, Jingran1; Tziritas, Nikos2; Theodoropoulos, Georgios1,3

2022

10.1109/ACCESS.2022.3199423

IEEE Access   Impact Factor & Quartile

2169-3536

Ridesharing has received global popularity due to its convenience and cost efficiency for both drivers and passengers and its strong potential to contribute to the implementation of the UN Sustainable Development Goals. As a result, recent years have witnessed an explosion of research interest in the RSODP (Origin-Destination Prediction for Ridesharing) problem with the goal of predicting the future ridesharing requests and providing schedules for vehicles ahead of time. Most of the existing prediction models utilise Deep Learning. However, they fail to effectively consider both spatial and temporal dynamics. In this paper the Baselined Gated Attention Recurrent Network (BGARN), is proposed, which uses graph convolution with multi-head gated attention to extract spatial features, a recurrent module to extract temporal features, and a baselined transferring layer to calculate the final results. The model is implemented with PyTorch and DGL (Deep Graph Library) and is experimentally evaluated using the New York Taxi Demand Dataset. The results show that BGARN outperforms all the other existing models in terms of prediction accuracy.

Attention deep learning request prediction ridesharing

SCI ; EI

English

First ; Corresponding

Shenzhen Science and Technology Program, China[GJHZ20210705141807022] ; Guangdong Province Innovative and Entrepreneurial Team Program, China[2017ZT07X386]

Computer Science ; Engineering ; Telecommunications

Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications

WOS:000844234900001

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

20223512671072

Deep learning ; Forecasting ; Human engineering ; Taxicabs

Ergonomics and Human Factors Engineering:461.4 ; Automobiles:662.1

Web of Science

1.Southern Univ Sci & Technol SUSTech, Dept Comp Sci & Engn, Shenzhen 518055, Peoples R China
2.Univ Thessaly, Dept Informat & Telecommun, Lamia 35131, Greece
3.Southern Univ Sci & Technol SUSTech, Res Inst Trustworthy Autonomous Syst, Shenzhen 518055, Peoples R China

Shen, Jingran,Tziritas, Nikos,Theodoropoulos, Georgios. A Baselined Gated Attention Recurrent Network for Request Prediction in Ridesharing[J]. IEEE Access,2022,10:86423-86434.

Shen, Jingran,Tziritas, Nikos,&Theodoropoulos, Georgios.(2022).A Baselined Gated Attention Recurrent Network for Request Prediction in Ridesharing.IEEE Access,10,86423-86434.

Shen, Jingran,et al."A Baselined Gated Attention Recurrent Network for Request Prediction in Ridesharing".IEEE Access 10(2022):86423-86434.