Liang Chen

Metro transfer passageways are complex pedestrian systems where heterogeneity in pedestrian collision-avoidance behaviors, especially overtaking and evading, can disrupt crowd organization, and intensify local congestion. However, most existing models describe pedestrian heterogeneity using simplified behavioral rules or demographic attributes, with limited attention to how personality traits correlate with the underlying collision-avoidance decisions. This study develops an agent-based simulation framework, informed by questionnaire-derived personality classifications and behavioral parameters, to examine how personality heterogeneity influences pedestrian overtaking and evading behaviors. Based on Eysenck’s personality theory, questionnaire data on walking behaviors and safety perceptions were collected from Beijing metro users, and pedestrians were classified into three personality-informed behavioral types: Self-Directed, Flexible-Adaptor and Cautious-Altruist. The questionnaire results show that these types differ in overtaking thresholds, evading responses and perceived safety, and that personality traits are more strongly associated with these behavioral differences than gender or age. A dual-layer behavioral simulation framework was then developed by coupling personality-dependent state transitions with the social force model. The decision layer describes transitions among following, overtaking and evading states, while the movement layer reproduces microscopic motion in continuous space. Agent-based simulations of metro transfer passageways with different personality compositions show that personality composition correlates with local density accumulation, congestion evolution, interaction patterns and passageway efficiency, particularly near turning and merging regions. These findings suggest that personality-informed behavioral modeling can improve the representation of heterogeneous pedestrian interactions in high-density metro environments.

The mixed traffic flow of various types of vehicles at bus station is severe, which has an impact on the overall safety of traffic. Especially upstream of bus station, since buses need to change lane in order to stop at the bus station, it interacts with social vehicles. Thus, in this paper, a two-lane CA model considering the mixed traffic flow composing of buses, cars and nonmotorized vehicles upstream of a bus station is proposed. Through several field surveys, the movement characteristics of the vehicles are obtained and the basic parameters are calibrated. For comparison, five cases about bus stops are studied. Several indexes (i.e. parallel time, blind area dwell time, time to collision, potential collision energy) are analyzed to assess the safety upstream of the bus station. Four safety indices are used to examine, based on simulation findings, the impact of bus station on vehicle safety and the significance of establishing exclusive nonmotorized vehicle lanes and exclusive bus lanes. Finally, several safety-related recommendations for drivers and management are provided. These findings offer a theoretical basis for driver management and optimal design of bus stations.