Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades. Its applications in land-based urban traffic network studies have been fruitful, but have suffered from the lack of a systematic cognitive and integration framework. This paper reviews complex network theory related knowledge and discusses its applications in urban traffic network studies in several directions. This includes network representation methods, topological and geographical related studies, network communities mining, network robustness and vulnerability, big-data-based research, network optimization, co-evolution research and multilayer network theory related studies. Finally, new research directions are pointed out. With these efforts, this physics-based concept will be more easily and widely accepted by urban traffic network planners, designers, and other related scholars.

Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality’s closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network’s growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

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Construction of exclusive motorcycle lanes is one of the measures to reduce motorcycle fatalities. Previous studies highlighted the risk of crashes with roadside objects and the tendency of motorcyclists to ride with excessive speed on exclusive motorcycle lanes. However, the risk of same-direction crashes on exclusive motorcycle lanes was not explored in much detail, especially on the impact of lane geometry and roadside configurations. This study used naturalistic riding data to determine the effects of lane width and roadside configurations on overtaking speed, lateral position and likelihood of comfortable overtaking on tangential sections of an exclusive motorcycle lane. Twenty-nine recruited motorcyclists rode the instrumented motorcycles along a 20km stretch of an exclusive motorcycle lane along a major urban road. Results revealed that both the roadside configurations and lane width significantly affect the participants' lateral position, while the roadside configurations only affects the overtaking speed. Participants' overtaking speeds and the front motorcycles' lateral position contribute significantly to the likelihood of comfortable overtaking in exclusive motorcycle lanes. The findings highlight the importance of micro-level behavior indicators in improving the design and overall safety of the exclusive motorcycle facility.