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Full-Text Articles in Social and Behavioral Sciences
Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng
Context-Aware Graph Convolutional Network For Dynamic Origin-Destination Prediction, Juan Nathaniel, Baihua Zheng
Research Collection School Of Computing and Information Systems
A robust Origin-Destination (OD) prediction is key to urban mobility. A good forecasting model can reduce operational risks and improve service availability, among many other upsides. Here, we examine the use of Graph Convolutional Net-work (GCN) and its hybrid Markov-Chain (GCN-MC) variant to perform a context-aware OD prediction based on a large-scale public transportation dataset in Singapore. Compared with the baseline Markov-Chain algorithm and GCN, the proposed hybrid GCN-MC model improves the prediction accuracy by 37% and 12% respectively. Lastly, the addition of temporal and historical contextual information further improves the performance of the proposed hybrid model by 4 –12%.
Improving The Performance Of Transportation Networks: A Semi-Centralized Pricing Approach, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Liujiang Kang, Xuexi Zhang, Qilun Wu
Improving The Performance Of Transportation Networks: A Semi-Centralized Pricing Approach, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Liujiang Kang, Xuexi Zhang, Qilun Wu
Research Collection School Of Computing and Information Systems
Improving the performance of transportation network is a crucial task in traffic management. In this paper, we start with a cooperative routing problem, which aims to minimize the chance of road network breakdown. To address this problem, we propose a subgradient method, which can be naturally implemented as a semi-centralized pricing approach. Particularly, each road link adopts the pricing scheme to calculate and adjust the local toll regularly, while the vehicles update their routes to minimize the toll costs by exploiting the global toll information. To prevent the potential oscillation brought by the subgradient method, we introduce a heavy-ball method …