Quadstone Paramics continue to push the boundaries of agent based simulation modeling with the release of the Urban Analytics Framework (UAF) V1.1. This release of the UAF pedestrian modelling software adds many new core features to help users build a wider variety of models and also sets new standards for powerful Agent and Spatial analytics.
Behavior Regions allow the user to adjust specific aspects of agent behavior as they progress through an area of space. Agent target speeds can be adjusted i.e. speed up to cross a road quickly or slow down to walk past a point of interest. In addition behavior Regions allow the user to define a number of dwell areas within the space where agents will stop and wait while they look at (face) a user defined point of interest, for example people moving through a station concourse looking at a display board before moving off to purchase a ticket and finally heading to their platform. Alternatively dwell points can be used to mimic points of interest in a museum, gallery or public monument where agents move through the space stopping to observe information at each point before continuing their journey.
Waypoint modifiers have been expanded in 1.1 to offer more flexibility in agent movement through the study area. Waypoint modifiers can now force agents to update their journey objectives at the edge of a waypoint, the centre of a waypoint or at a random point within the waypoint.
A new analytics tool has been added for Agent Marking. Similar to Vehicle Marking rules this new tools lets users drill down in to the details of agent movement by highlighting agents that are making a particular journey within the study area. In keeping with other Paramics high value tools, multiple options are available for filtering, highlighting, annotating and reporting the results of Agent Marking Rules.
Blocking regions now support a comprehensive range of filtering options i.e. they are only seen by specified agent types arriving from selected waypoints or demand regions.
Improving the UAF analytics capability a new Region Metrics Tool has been added. The Region Metrics Tool allows the user to define data collection regions of any shape and record the flow/count in and out of that region aggregated by a user definable time period. In addition the agent travel time to traverse each region is also recorded. Users can configure a range of display, Information Browser, and reporting options and of course can use pre defined or custom LOS colour scales for easy analysis.
A new powerful Connector Metrics Tool is available in UAF 1.1. This tool lets user query key agent metrics such as speed, travel time, flow/count and delay sampled between waypoints as each agent makes their way through the agent space. As with all Paramics analytics tools comprehensive graphics and reporting options are provided to maximise the value users can get from this tool.
Advanced demands specification now lets users choose from a range of agent spawning options including linear release and random or platooning release.
Compliance values for blocking regions can be set at both the blocking region itself and for each specific agent type. This feature allows greater flexibility when defining the behavior of the agent population: for example some agents will always be fully compliant to traffic rules while others will actively seek opportunist crossing gaps.
The Agent Compliance Viewer is a new analytics tool added in 1.1 which allows user to analyse agent compliance behavior at specific locations within the network. The Agent Compliance Viewer shows the ratio of compliant to non compliant agents at blocking regions and can also show the number of agents who would like to cross against the don’t walk signal but cannot do so because there is no available gap in the traffic flow. As with all Paramics analytics tools comprehensive graphics and reporting options are provided to maximise the value users can get from this tool.
UAF 1.1 now allows multiple fixed or presence call on demand phases to be associated with a single blocking region. Each phase can have its own walk/don’t walk time and presence phases will track their own specific recall counter.