Accurately predicting traffic speed is critical for traffic system scheduling, management, and optimization. Three essential elements should be considered in highway traffic speed prediction: (1) complex traffic spatial diffusion process with time, (2) considerable influence of traffic patterns for predicting, and (3) bi-directed learning mechanism on time series forecasting task occupy a vital place. A self-supervised spatio-temporal bilateral learning network (3S-TBLN) for long-term traffic speed forecasting is proposed to address the above challenges. 3S-TBLN adapts an encoder-decoder, which is bilateral architecture, where both the encoder and the decoder consist of the semantic transformer, multiple spatio-temporal blocks (ST-Blocks), and bridge transformer (BridgeTrans). The semantic transformer is presented convert speeds from source to high-dimension representations; ST-Blocks is designed to model dynamic spatio-temporal correlations in both encoder and decoder; in the encoder, BridgeTrans is applied to learn the forward traffic patterns from the last week's observations, and vice versa; a self-supervised learning method is proposed to reconstruct historical variables as pretext job combined with speed prediction task learn the bi-directed context. Experimental results demonstrate that the proposed 3S-TBLN model significantly outperforms state-of-the-art baselines and can efficiently solve the problem of long-term highway speed prediction. © 2023 IEEE.

Vehicles and traffic management departments have a strong desire to know the traffic speed on the high-way network in a certain future time. A multi-task-based spatio-temporal generative inference network (MT-STGIN) is proposed to predict highway traffic speed in this paper. MT-STGIN can handle the following three challenges: (1) dynamic spatio-temporal correlations, (2) prediction error propagation elimination, and (3) traffic speed heterogeneity on the highway network. First, the encoder is used to extract the dynamic spatio-temporal correlations of the highway network. Second, the decoder concentrates on correlating historical and target sequences and generates the target hidden outputs rather than a dynamic step-by-step decoding way. Finally, a multi-task learning method is used to predict traffic speed on different types of roads because of heterogeneity and shares the underlying network parameters. The evaluation experiments demonstrate that the performance of the proposed prediction model is better than that of the baselines, which are conducted based on the monitoring data of the highway in Yinchuan City, Ningxia Province, China. © 2023 IEEE.

There is a close interaction between the urban built environment and the spatial behavior characteristics of individuals in time. Youths are an important group in urban development, and their travel affects the overall efficiency of the city. This study uses cell phone signaling data and POI data to build linear regression models and geographically weighted regression models, respectively, to analyze the impact of built-up environment on the peak hour travel of youth groups. It is found that there are similarities in the morning and evening peak models, and there are significant differences in travel time and space; residential population and job density have significant effects on the travel of the youth population, and commuting travel is still the most important which exists a separation of jobs and residences; construction of new cities in Shanghai is steadily advancing, and accessibility and equity of urban services and facilities need to be strengthened. © ASCE.

Taking the Batong Line of Beijing subway as our research object, it includes nine stations, such as Communication Univ. of China Station, Shuang Qiao Station and soon on. The attraction range of passenger flow of the subway station is a circle which takes 800 m as the radius. The surrounding land use types of the subway station and its corresponding area within its attraction limit are determined based on the remote sensing images of each site. The prediction model of the passenger flow of each subway station and the area of different land use types surrounding it is established by using regression analysis. It is found that the average daily passenger flow on weekdays and the average daily passenger flow on weekends of each subway station are positively correlated with its surrounding total land use area. The passenger flow in and out of the subway station at different time periods has different relationship with the surrounding land use types and their corresponding area. Therefore, the average daily passenger flow and passenger flow in different time periods of the subway station can be predicted by its surrounding different land use types. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

In order to meet the demand for passenger transport and improve the overall operation efficiency of the integrated passenger transport system in the region within the urban agglomeration, the optimization method of the layout of integrated passenger transport terminals in the urban agglomeration are researched in this paper, and the Beijing-Tianjin-Hebei urban agglomeration is considered as our research object. Firstly, the influential factors of the location and layout of the integrated passenger transport terminal are qualitatively analyzed. Secondly the degree of charm indexes are defined, and next the selection model of alternative points based on the degree of charm of the terminal is built, and then the degree of charm value is calculated comprehensively by the analytic hierarchy process (AHP) and multi-level fuzzy evaluation method. Then, on the basis of determined the alternative points of the terminal, the layout of the terminals is optimized based on the P-median location model, and Microcity software is used to solve the model. Finally, an instance is given to prove that the model method has a certain guiding effect on the layout optimization of urban agglomeration comprehensive passenger terminals. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Recent years have seen satellite technology progressed significantly, which enables free and efficient access to the latest satellite images in most urban areas throughout the world. Based on the existing research, this study establishes a remote sensing image dataset of China transportation hubs and land-use types within their passenger attraction range. The dataset contains 5 transportation hubs and 16 land-use child classes which are divided from eight parent categories. There are 300 images in each class for a total of 6,300. Compared with traditional remote sensing image dataset, the proposed one is mainly applied to identify and estimate passenger flow volume generated by transportation hubs in China. Therefore, the hubs and land-use categories that are closely related to passenger flow are selected. This dataset will provide data support for further development of passenger density assessment methods based on remote sensing images. © 2020 American Society of Civil Engineers.

Robust and accurate short-term traffic volume prediction methods are indispensable in driving assistance and active traffic control and management. With the popularity of deep learning, the hybrid methods play an important role in improving the prediction accuracy. To fully cover the spatial-temporal characteristics of traffic flow, this paper proposes an attention-based spatial and temporal model (AST) through combining convolutional neural network (CNN), gated recurrent unit (GRU). Besides, the attention mechanism is also introduced after GRU to further improve the prediction accuracy. The experiments which are carried on the Beijing expressway traffic volume data indicate that the AST model has better performance than the baseline models in terms of prediction accuracy. Compared with ARIMA, SVR, CNN, and GRU, the MAE of AST is reduced by 21.6%, 20.9%, 11.0%, and 9.9%; the MAPE is reduced by 14.4%, 15.1%, 10.7%, and 10.3%; the RMSE is reduced by 22.6%, 20.3%, 11.0%, and 10.8%. Finally, the comparison of prediction accuracy between AST and the sub-components verifies the necessity of each part of the model. © 2020 SAE International.

To some certain extent, the development of electric vehicles relies on the availability of infrastructure, especially charging facility. There have been a large amount of studies on the location of electric vehicle charging stations before. In this paper, we establish an improved p-median model that aims to minimize the time costs. This model has some constraints such as the capacity of charging stations and the demand of customers, etc. All of these constraints should be satisfied at the same time. In order to solve this problem, a greedy heuristic algorithm is proposed. Then, we use MATLAB to simulate the case of a real-city charging station layout, and the result indicates that our method is effective and reasonable. © 2020, Springer Nature Singapore Pte Ltd.

Air passenger flow can show the spatial connection among cities. Based on the ticket data of major airports in Beijing-Tianjin-Hebei region, this paper systematically explored the temporal and spatial distribution characteristics of passenger flow in this region, drew the OD map among this region and other cities, and analyzed regional differences and connection characteristics among cities. Experimental results show that the passenger flow of airports in the Beijing-Tianjin-Hebei region is uneven in time and space. In terms of space, the regional distribution of air passenger flow is extremely unbalanced. The air transportation status in the east is extremely prominent, while the western part is relatively strong, and the central and northeast parts are relatively weak. In terms of time, the major airports in the Beijing-Tianjin -Hebei region have obvious peak and low peak periods, and the distribution of passenger flow direction in different time periods is also slightly different. The research results provide a basis for the analysis of population flow and economic relationship among urban agglomerations, and provide reasonable suggestions for traffic planning and passenger travel.