Traffic forecasting is important for the success of intelligent transportation systems. Deep
learning models, including convolution neural networks and recurrent neural networks, have …

Modeling complex spatial and temporal dependencies in multivariate time series data is
crucial for traffic forecasting. Graph convolutional networks have proved to be effective in …

With the abundance of public transportation in highly urbanized areas, it is common for
passengers to make inefficient or flawed transport decisions due to a lack of information. The …

Travel time estimation from GPS trips is of great importance to order duration, ridesharing,
taxi dispatching, etc. However, the dense trajectory is not always available due to the …

公交行驶轨迹预测是对公交车到达线路上的重要轨迹点, 如站点和道路交叉口等,
进行到达时间预测. 准确预测公交车到达站点和道路交叉口的时间, 可以提高城市公交系统的 …

Due to the rapid development of Internet of Things (IoT) technologies, many online web
apps (eg, Google Map and Uber) estimate the travel time of trajectory data collected by …

Pereira es una ciudad que se está expandiendo a nivel infraestructural, sin embargo, no
cuenta con una malla vial muy amplia para la cantidad de vehículos que circulan por ella …