This study aims at evaluating the congestion level of pedestrians in metro stations. Twelve hours (4 h × three facilities) of video data were collected in the channel, stairway, and platform in a metro station in the city of Ningbo, China. The indicator of GPC (grade of pedestrian crowd) was proposed to quantify the congestion level of pedestrians. Four levels of congestion (level I, level II, level III, and level IV) were determined based on the GPC. A normal-cloud (NC) model was proposed and calibrated for the evaluation of three facilities including channel, stairway, and platform. The evaluation results showed that the GPC of L1-L2 and L2-L1 in channel are level II and level I, respectively. The GPC of upward and downward of stairway are level III and level I. The GPC of platform is level IV. Crowd management countermeasures were proposed for the management of pedestrians in metro station.

Many pavement distress (PD) indexes are defined only from the perspective of the PD physical structure, which cannot describe the change of traffic efficiency. Some PD indexes are defined considering the influence of traffic efficiency, but it is unpractical to calculate them out due to their complex processes. We quantify the impact of the cohesive whole of PD points on the traffic flow and also define the corresponding PD index which is easy to compute. Firstly, the lane cell based on the idea of road discretization is introduced. Secondly, the PD degree for the lane cell is defined by the reduction of the average vehicle speed given the same flow condition. The cell whose PD degree is larger than 0 is defined as the PD cell. Then, considering (1) the ratio of PD cells, (2) PD cell distribution, and (3) the influence of the vehicle lane changing, we define the holistic road-damage degree (HRDD) as the PD index. At last, the relationship among HRDD, flow speed, and flow volume is analyzed through the simulated experiments. The results show that (1) the average speed is inversely proportional to HRDD, and the reduction of vehicle speed is more significant with the increase of the traffic flow input; (2) the inverse relation between road capacity and HRDD can be seen on the whole HRDD range. In another word, the proposed HRDD describes the change of traffic efficiency indeed.