LEGION

Build precise models

Create precise models of how a space will be used

• Import architectural drawings (CAD) to define physical spaces available for pedestrian use
• Specify the anticipated pedestrian demand for the space
• Designate areas where interim activities, such as queuing or waiting, occur
• Link operational data to the model
• Plan routes and automatically lay out navigation maps
• Populate the model based on activities and characteristics, such as size, speed, and personal preferences.

Principle of Least Effort

• Uses the concept of least effort, or least cost, as the basis of pedestrian logic
• Dissatisfaction is caused by physical and psychological factors that lower journey quality. Factors that contribute to dissatisfaction:
  • Inconvenience – desire line divergence stress
  • Discomfort – personal space compression stress
  • Frustration – preferred speed relinquishment stress

Unbounded Movement Choice

• Model space is continuous, rather than structured, based on a pixel grid
• Select any vector when optimizing step choice to satisfy individual preferences and objectives in the context of changing physical constraints
• This approach follows a two-stage process:

  • Macro-navigation

    • The selection of an entity’s desired direction to its next target, from its current position
    • Represented by a sequence of intermediate, focal targets that trace the shortest path from an entity’s location to the place where it leaves the model (or reaches its final destination)

  • Micro-navigation

    • Uses advanced, proprietary, artificial intelligence algorithms to apply micro-navigation to its entities, within a simulation
    • Algorithms enable entities to exhibit realistic pedestrian movement
    • Entities have an area of perception that adjusts dynamically, based on instantaneous information and accumulated memories
    • Entities assess information to decide their best immediate step
    • Micro-navigation algorithm takes several important considerations into account, including:
      • Early detection and avoidance of physical obstacles
      • Accommodation of personal space, preferred speed and more
      • Maneuvering to avoid collisions
      • Learning from accumulated memories
      • The ability to adjust individual preferences and attributes

Intelligent Entities

• Social, physical, and behavioral characteristics are assigned probabilistically from established profiles
• Social characteristics include gender, age, culture and pedestrian type, all of which shape typical movement preferences
• Physical characteristics determine body sizes
• Behavioral characteristics include memory, adaptability, and preferences for unimpeded walking speeds, personal space, and acceleration

Output and Analyses

• Numerical and graphical outputs derived from a model and user-defined areas, interrogated to provide user-defined combinations of these, based on user-defined thresholds
• Measure and quantify the performance of a site with respect to experience, circulation, and safety
• Key metrics include counts, flows, distances, densities, journey times, speeds, and levels of service
• Heat maps provide intuitive overviews to help identify areas requiring deeper analyses, including line graphs, histograms, stacked histograms, cumulative data, or even raw data, which can then be used for statistical analyses