In the metro operation environment, guiding signs provide direction and route conversion instructions to pedestrians. In metro stations with massive passenger flow, the rationality of sign setting would exert distinct effects on the efficiency of passenger flow. Currently, most studies on guiding signs focus on architecture, aesthetics and simulation. However, perspectives from humanization of pedestrian guidance signs such as pedestrian behavior needs and pedestrian cognition were seldom proposed. In this paper, the microscopic behavior characteristics data of pedestrians at different positions in typical metro stations were collected through pedestrian tracking experiments. After analyzing the characteristics of pedestrians’ microscopic behavior in metro stations, otherness of walking speed was found out among pedestrians in different types of passageways. The walking speed of pedestrians in closed-type passageways is higher than other types. Moreover, pedestrian speed at the stairs adjacent to the platform is higher than that at the stairs not adjacent to the platform. With the increase of crowd density, the change of walking speed of pedestrians can be represented by a unimodal curve. Finally, the key points of optimal setting of guiding signs in different regions and different periods were obtained according to the result analysis of the experiment. The research results of this paper can provide theoretical support and technical guidance for the optimal establishment of pedestrian guiding signs in metro stations with massive passenger flow.

Accurate, timely, and reliable traffic flow prediction is essential for an intelligent transportation system due to the complex spatio-temporal correlation of traffic flow. The prediction model based on graph convolution neural network (GCN) has become mainstream in recent years. However, most of the prediction models based on GCN only use an adjacency matrix to characterize the spatial correlation of traffic flow, ignoring the complex and dynamic relationship between road network adjacent nodes and missing the hidden connection between the global nodes of the road network. This paper proposes a SAX-STGCN network for traffic flow prediction to solve the above problems. The SAX-STGCN model uses symbolic approximation (sax) to obtain the similarity of the historical data of the predicted node in the previous period, including adjacent nodes and non-adjacent nodes, forming a similarity matrix to replace the original adjacency matrix composed of 0 and 1, which is defined as a global sax-correlation matrix to characterize the correlation between nodes in the road network and capture the implicit spatial relationships in the road network. Then, based on the dynamic global sax-correlation matrix, GCN is used to capture the spatial correlation of traffic flow, and gated recurrent unit (GRU) is used to capture the temporal correlation of traffic flow. The prediction accuracy is better than the baseline and has long-term prediction ability.

The appropriate distribution of the guide signs in subway stations can allow passengers to obtain direction and wayfinding information quickly and accurately. The existing setting methods of subway station guide signs mainly consider the locations of facilities and pedestrian flowlines in the station. Therefore, this research proposes an optimization method based on pedestrian walking behavior to set guide signs more realistically and increase the guidance efficiency of signs. Firstly, through on-site investigation, this research analyzed the walking behavior characteristics of pedestrians and measured the average speed of pedestrians in different spaces to quantify the walking characteristics. Then, the guidance level of guide signs was defined to describe the guide ability of each sign and was the basis for determining the distribution of the guide signs. The constraint of the distance between two adjacent guide signs was added according to the short-term memory of pedestrian walking identification. Moreover, the variable of the number of floors between the two adjacent signs was added to avoid calculating floor-by-floor. Finally, Xi’an Xiaozhai Station was selected as an example to verify the proposed optimization method using the AnyLogic 8.7.6. The results show that the guide sign optimization method based on pedestrian walking behavior proposed in this paper can obtain an accurate distribution of guide signs, which can decrease the outbound time by 18.51s at the most, and the thickness at the bottleneck decreases by 5.90%.

In studies investigating the property value enhancements along metro lines, study ranges in most cases are measured in Euclidean distance. However, city roads are not always straight, and Euclidean distance sometimes does not equal to actual distance the passenger travels from the public transport station to their home or a commercial spot. To solve this problem, this study analyzed the indicators affecting commercial property value in metro station accessible area in Xian, using walking time consumption in measuring the study range. Following a conceptual framework, considering empirical evidences in related studies, information in city structure, and metro distribution, the initial indicator set is built. Using hedonic price model (HPM), spatial autoregressive model (SAR), and error term (SEM), significant indicators affecting commercial property value are investigated. In this study, 14 significant indicators are determined and quantified. Threshold distance equals to 900m is found to be appropriate in addressing the autocorrelation problem with the weighted decision matrix tool. Compared to HPM and SEM, SAR is found to perform the best in evaluating the significant indicators with the largest R² (0.415) and the lowest Akaike Info Criterion (AIC) (395.214). Besides, it is discovered that the value of the commercial property lies in the study range of 20min walking time and is obviously influenced by the metro station. The results discovered in this study could provide some empirical evidences to commercial property planning in Xian.

Relying on the project of the open‐cut municipal tunnel undercrossing Ankang Freight V yard, the train dynamic response and seismic response of ultrashallow‐buried rectangular tunnel of the lower interchange are studied, respectively, by combining the method of field measurement and numerical simulation. The results show that under the action of train vibration load, the dynamic stress response of the top plate midspan and the upper end of the side wall of the tunnel cross section directly below the rail is the most significant, and the dynamic stress response of the bottom plate is the smallest. Under the rare earthquake, the tunnel structure has large transverse deformation, in which the transverse displacement of the tunnel roof is the largest. At the same time, there is a large stress concentration at the variable section of the tunnel.