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c. Detail of the arrival and departure curve for scenario 2. Different traffic characteristics, such as free travel time, delay and number of pedestrians in the observed area, have been indicated. 1h iis ee sek shee cai

Figure 7 c. Detail of the arrival and departure curve for scenario 2. Different traffic characteristics, such as free travel time, delay and number of pedestrians in the observed area, have been indicated. 1h iis ee sek shee cai

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To identify the aspects influencing pedestrian behavior in and around revolving doors, a behavioral framework has been derived, based on the general demand — supply framework (see FIGURE 1). Such a framework is a common approach to predict the performance of a traffic system as function of demand, supply, interaction and environmental information (/5). FIGURE 1 Behavioral framework for revolving doors (14).
To identify the aspects influencing pedestrian behavior in and around revolving doors, a behavioral framework has been derived, based on the general demand — supply framework (see FIGURE 1). Such a framework is a common approach to predict the performance of a traffic system as function of demand, supply, interaction and environmental information (/5). FIGURE 1 Behavioral framework for revolving doors (14).
The supply represents the revolving door characteristics. Examples are door size, free rotation speed, number of wings and properties of the safety sensors. Each revolving door is equipped with multiple safety sensors, which force the door to stop when someone enters the safety sensor area. This avoids people getting stuck between the revolving door and the surrounding structure, but it may have a large effect on system performance. The safety regulations differ per country, thus influencing the safety sensor tuning and the revolving door performance. To get an idea of the different types of revolving doors, FIGURE 2 gives an overview of commonly used revolving doors as well as their most important characteristics.
The supply represents the revolving door characteristics. Examples are door size, free rotation speed, number of wings and properties of the safety sensors. Each revolving door is equipped with multiple safety sensors, which force the door to stop when someone enters the safety sensor area. This avoids people getting stuck between the revolving door and the surrounding structure, but it may have a large effect on system performance. The safety regulations differ per country, thus influencing the safety sensor tuning and the revolving door performance. To get an idea of the different types of revolving doors, FIGURE 2 gives an overview of commonly used revolving doors as well as their most important characteristics.
Daamen, W, Hoogendoorn, SP, Landman, RL & Wijngaarden, H van (2008). Pedestrian behavior experiments in and around automated revolving doors. In Compendium of papers TRB 87th Annual Meeting (pp. 1-15). Washington DC: Mira Digital.
Daamen, W, Hoogendoorn, SP, Landman, RL & Wijngaarden, H van (2008). Pedestrian behavior experiments in and around automated revolving doors. In Compendium of papers TRB 87th Annual Meeting (pp. 1-15). Washington DC: Mira Digital.
Daamen, W, Hoogendoorn, SP, Landman, RL & Wijngaarden, H van (2008). Pedestrian behavior experiments in and around automated revolving doors. In Compendium of papers TRB 87th Annual Meeting (pp. 1-15). Washington DC: Mira Digital.
Daamen, W, Hoogendoorn, SP, Landman, RL & Wijngaarden, H van (2008). Pedestrian behavior experiments in and around automated revolving doors. In Compendium of papers TRB 87th Annual Meeting (pp. 1-15). Washington DC: Mira Digital.
a. Location of arrival (X;, A(t)) and departure curve (X2, D(t)). Ta RR OL mates oMetncee een iy mes! SSSR CREAGRERS “AWA Ces gbheaic To obtain data on pedestrian travel times and door capacity, we use cumulative curves. A cumulative curve describes the time moments that passengers pass a given cross-section. To determine travel times, we have determined two cross-sections: one at the start of the walking area and a second one downstream of the revolving door (see FIGURE 5). Since the revolving door is considered to be the bottleneck, the departure curve can also be used to determine the capacity of the revolving door.
a. Location of arrival (X;, A(t)) and departure curve (X2, D(t)). Ta RR OL mates oMetncee een iy mes! SSSR CREAGRERS “AWA Ces gbheaic To obtain data on pedestrian travel times and door capacity, we use cumulative curves. A cumulative curve describes the time moments that passengers pass a given cross-section. To determine travel times, we have determined two cross-sections: one at the start of the walking area and a second one downstream of the revolving door (see FIGURE 5). Since the revolving door is considered to be the bottleneck, the departure curve can also be used to determine the capacity of the revolving door.
b. Arrival curve (blue) and departure curve (red) in scenario 2. The green line indicates the departure curve when pedestrians would not have experienced hinder.
b. Arrival curve (blue) and departure curve (red) in scenario 2. The green line indicates the departure curve when pedestrians would not have experienced hinder.
d. Detail of the departure curve, downstream of the revolving door. The step wise function is clear, caused by emptying a segment.
d. Detail of the departure curve, downstream of the revolving door. The step wise function is clear, caused by emptying a segment.
TABLE 2 Travel Times, Delays and Queue Characteristics for each Scenario — TABLE 2 gives an overview of travel times, delays and queue characteristics for each scenario. The free travel times are similar for all scenarios, except for scenarios | and 5 that have higher travel times due to the ow peripheral speed of the door wings. Both the revolving door speed and the fence appear to influence pedestrian behavior. In scenario | and 5 the door speed is very low (comparable to revolving doors in hospitals), which gives pedestrians much time to completely fill the segments. This leads to frequent breakdowns, even at relatively low flows, and thus to longer delays. In the scenarios with one-directional commuter flow (1-4), pedestrians in congestion formed a bulk queue upstream of the entrance that completely occupied the opening. Their pushy behavior while entering the segments frequently activated the safety sensors. The fence appears to have a positive effect on the behavior of these hasty commuters, which are forced to stay in line and form a inear queue. The entrance can only be accessed for the right side of the fence, leading to less frequently activated sensors. Shopping pedestrians formed a linear queue, in which situation the fence might have negative influences, since it only reduces entrance width. The maximum number of pedestrians in the system is significantly higher in the scenarios where bulk queues are formed, since these queues have much higher densities than linear ordered queues.
TABLE 2 Travel Times, Delays and Queue Characteristics for each Scenario — TABLE 2 gives an overview of travel times, delays and queue characteristics for each scenario. The free travel times are similar for all scenarios, except for scenarios | and 5 that have higher travel times due to the ow peripheral speed of the door wings. Both the revolving door speed and the fence appear to influence pedestrian behavior. In scenario | and 5 the door speed is very low (comparable to revolving doors in hospitals), which gives pedestrians much time to completely fill the segments. This leads to frequent breakdowns, even at relatively low flows, and thus to longer delays. In the scenarios with one-directional commuter flow (1-4), pedestrians in congestion formed a bulk queue upstream of the entrance that completely occupied the opening. Their pushy behavior while entering the segments frequently activated the safety sensors. The fence appears to have a positive effect on the behavior of these hasty commuters, which are forced to stay in line and form a inear queue. The entrance can only be accessed for the right side of the fence, leading to less frequently activated sensors. Shopping pedestrians formed a linear queue, in which situation the fence might have negative influences, since it only reduces entrance width. The maximum number of pedestrians in the system is significantly higher in the scenarios where bulk queues are formed, since these queues have much higher densities than linear ordered queues.
a. Different probability distribution functions of the free speed. The histogram shows the observed free speed, while four distributions have been fit to the data set.
a. Different probability distribution functions of the free speed. The histogram shows the observed free speed, while four distributions have been fit to the data set.
b. Cumulative distribution functions of the free speed for different pedestrian types.
b. Cumulative distribution functions of the free speed for different pedestrian types.
TABLE 3 Free Speeds for all Pedestrian Types including Estimation Results for the Normal Distribution (in m/s) Revolving door capacity Capacity is defined as the maximum number of passengers passing a cross-section during a given time period. Capacity is stochastic, with a certain mean and standard deviation. We can distinguish between two capacities: the pre queue capacity (= outflow from bottleneck just before congestion sets in) and the queue discharge rate (= outflow from bottleneck during congestion). Although often the pre queue capacity is somewhat higher than the queue discharge rate, the latter lasts longer. In this paper, we will focus at the queue discharge capacity. D An nniiwcn ee ee ae es a: en, ae ee a : ee a es ke: Ee eae Ne
TABLE 3 Free Speeds for all Pedestrian Types including Estimation Results for the Normal Distribution (in m/s) Revolving door capacity Capacity is defined as the maximum number of passengers passing a cross-section during a given time period. Capacity is stochastic, with a certain mean and standard deviation. We can distinguish between two capacities: the pre queue capacity (= outflow from bottleneck just before congestion sets in) and the queue discharge rate (= outflow from bottleneck during congestion). Although often the pre queue capacity is somewhat higher than the queue discharge rate, the latter lasts longer. In this paper, we will focus at the queue discharge capacity. D An nniiwcn ee ee ae es a: en, ae ee a : ee a es ke: Ee eae Ne
a. Slanted cumulative curve of scenario 1, with different phases (capacity versus through put). Daamen, W, Hoogendoorn, SP, Landman, RL & Wijngaarden, H van (2008). Pedestrian behavior experiments in and around automated revolving doors. In Compendium of papers TRB 87th Annual Meeting (pp. 1-15). Washington DC: Mira Digital.
a. Slanted cumulative curve of scenario 1, with different phases (capacity versus through put). Daamen, W, Hoogendoorn, SP, Landman, RL & Wijngaarden, H van (2008). Pedestrian behavior experiments in and around automated revolving doors. In Compendium of papers TRB 87th Annual Meeting (pp. 1-15). Washington DC: Mira Digital.
b. Slanted cumulative curve of scenario | with the three capacity trends during congestion upstream of the door.
b. Slanted cumulative curve of scenario | with the three capacity trends during congestion upstream of the door.
TABLE 4 Capacity Trends and Global Capacity of each Scenario CONCLUSIONS AND FUTURE WORK
TABLE 4 Capacity Trends and Global Capacity of each Scenario CONCLUSIONS AND FUTURE WORK
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