To establish the optimal route layout estimation technology based on reliability optimization, a more accurate and realistic reliability model of a weighted public transit network (PTN) is the indispensable basis. This paper establishes a cascading failures (CFs) perspective based mesoscopic reliability model for measuring PTN survivability. First, a modeling method for abstracting weighted PTN and determining its initial passenger flow and bearing capacity is proposed, making the network passenger flow pattern follow the aggregated flow pattern. Second, three basic concepts (time step, congestion effect of a road section, and CFs judging method) for establishing the CFs model are defined to clarify the overall evolution process of CFs. Furthermore, the aggregated passenger flow evacuation that exists in an emergency occurring at a station (i.e., failure load dynamic redistribution (FLDR)) is considered as a conscious dynamic game process through following the user equilibrium rule. As a result, a novel CFs model that considers congestion effect and user equilibrium evacuation is obtained. Finally, based on the collected data of Jinan’s PTN, a case simulation analysis is conducted to verify the adaptability of this model through showing a significantly different dynamics characteristic with the existing FLDR patterns and to provide optimization direction for effectively controlling PTN survivability, that is, guide the transformation among varying FLDR patterns through some technical measures or traffic policies.

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Identifying road accident blackspots is an effective strategy for reducing accidents. The application of this method in rural areas is different from highway and urban roads as the latter two have complete geographic information. This paper presents (1) a novel segmentation method using grid clustering and K-MEDOIDS to study the spatial patterns of road accidents in rural roads, (2) a clustering methodology using principal component analysis (PCA) and improved K-means to create recognition of road accident blackspots based on segmented results, and (3) using accidents causes in police report to analyze recognition results. The proposed methodology will be illustrated by accident data in Chinese rural area in 2017. A grid-based partition was carried on by using intersection as a basic spatial unit. Appended hazard scores were then added to the segments and using K-means clustering, a result of similar hotspots was completed. The accuracy of the results is verified by the analysis of the cause extracted by Fuzzy C-means algorithm (FCM).

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