1. NGSIM Framework

2. Objectives  Define simulation framework Simulation package componentsSimulation package components Core model components – NGSIM focusCore model components – NGSIM focus  Clarify bounds of NGSIM focus Focus on traveler behavior as it determines the traffic stream in a network settingFocus on traveler behavior as it determines the traffic stream in a network setting Develop and validate behavioral algorithms within context of larger modelDevelop and validate behavioral algorithms within context of larger model  Help in prioritization of user requirements (separate presentation)  Receive input on “low-hanging” core algorithms and data sets (separate presentation)

3. Overview  Framework definitions Simulation packageSimulation package Core modelCore model  Core model components Behavioral algorithmsBehavioral algorithms Influencing factorsInfluencing factors Interaction mechanisms (System state)Interaction mechanisms (System state)

4. Simulation Package Framework Core Model Input API Output API GUITools User NGSIM Focus

5. Simulation Package Components  User-centric components GUI, analysis tools, data management toolsGUI, analysis tools, data management tools Out of scope for NGSIMOut of scope for NGSIM Meeting user needs best handled by vendorsMeeting user needs best handled by vendors  Core model components Behavioral algorithms and other core componentsBehavioral algorithms and other core components In scope for NGSIMIn scope for NGSIM Goal is to increase accuracy, consistency, flexibility of modelsGoal is to increase accuracy, consistency, flexibility of models FHWA is leading effort to improve core modelsFHWA is leading effort to improve core models

6. Core Model Framework  Behavioral Algorithms Define traveler behavior within the core modelDefine traveler behavior within the core model Primary focus of NGSIMPrimary focus of NGSIM  Influencing Factors Components of the system, which influence traveler behaviorComponents of the system, which influence traveler behavior  System State Time-specific interaction mechanisms of traffic components and traveler behaviorsTime-specific interaction mechanisms of traffic components and traveler behaviors

7. Behavioral Algorithms  Types Pre-Trip (Strategic)Pre-Trip (Strategic) En-route (Strategic)En-route (Strategic) Driving (Tactical)Driving (Tactical)  En-Route and driving behaviors are focus of NGSIM  Definitions follow Pre-Trip (Strategic) En-Route (Strategic) Driving (Tactical) NGSIM focus

8. Pre-Trip Strategic Behaviors (Behavior)  Definition High-level traveler choices, which take place before departure (i.e. trip making decisions)High-level traveler choices, which take place before departure (i.e. trip making decisions)  Examples: Route choiceRoute choice Destination choiceDestination choice Mode choiceMode choice  Outside of NGSIM scope Purview of travel demand models, TRANSIMSPurview of travel demand models, TRANSIMS These behaviors are assumed exogenous to NGSIMThese behaviors are assumed exogenous to NGSIM

9. En-Route Strategic Behaviors (Behavior)  Definition High-level choices, which take place during tripHigh-level traveler choices, which take place during trip  Examples: Route modification (in response to information)Route modification (in response to information) Destination modification (in response to information)Destination modification (in response to information)  Inside NGSIM scope Secondary focus of projectSecondary focus of project

10. Driving Tactical Behaviors (Behavior) Driving Tactical Behaviors (Behavior)  Definition Traveler behaviors to meet tactical needsTraveler behaviors to meet tactical needs  Examples: Car-followingCar-following Lane-changing and gap acceptanceLane-changing and gap acceptance Departure (discharge) processes at signalized intersectionsDeparture (discharge) processes at signalized intersections  Inside NGSIM scope Primary focus of projectPrimary focus of project

11. System Management Network Environment Vehicle Characteristics Traveler Characteristics System Traveler Traveler Influencing Factors  Traveler: traveler characteristics, vehicle characteristics  System: network, environment, system management  Of interest only as related to behavioral inputs and outputs

12. Traveler Characteristics (Influencing Factor)  Definition Attributes of travelers, which affect traveler behaviorAttributes of travelers, which affect traveler behavior  Examples: Perception (age, skill)Perception (age, skill) Decision making (aggressiveness, familiarity)Decision making (aggressiveness, familiarity) Control (attention, impairment)Control (attention, impairment)  NGSIM behavioral algorithms must take into account all relevant traveler characteristics, keeping in mind ability to calibrate for practical use

13. Vehicle Characteristics (Influencing Factor)  Definition Properties of vehicles, which affect traveler behaviorProperties of vehicles, which affect traveler behavior  Examples: Dynamic (maximum acceleration, turning radius)Dynamic (maximum acceleration, turning radius) Physical (size, mass)Physical (size, mass) Type (motorized, non-motorized, emergency)Type (motorized, non-motorized, emergency)  NGSIM behavioral algorithms must take into account a complete set of potential vehicle characteristics, keeping in mind ability to calibrate model for practical application

14. Network (Influencing Factor)  Definition Collection of elements which define roadway and transit path characteristicsCollection of elements which define roadway and transit path characteristics  Examples: Element type (link, intersection, destination, toll plaza)Element type (link, intersection, destination, toll plaza) Element characteristics (grade, lanes, surface quality)Element characteristics (grade, lanes, surface quality) Element use restrictions (HOV, transit)Element use restrictions (HOV, transit)  NGSIM behavioral algorithms must be able to work with a fully realized network

15. Environment (Influencing Factor)  Definition Events on or states of the network which affect traveler behaviors – not originating from system control strategiesEvents on or states of the network which affect traveler behaviors – not originating from system control strategies  Examples: WeatherWeather IncidentsIncidents Sight restrictionsSight restrictions  NGSIM behavioral algorithms must consider environmental conditions

16. System Management (Influencing Factor)  Definition Events on or states of the network which affect traveler behaviors – originating from system control strategiesEvents on or states of the network which affect traveler behaviors – originating from system control strategies  Examples: Traffic managementTraffic management Transit managementTransit management Incident managementIncident management Electronic payment systemsElectronic payment systems  NGSIM behavioral algorithms must consider the effects of system control strategies

17. System State  Defines the interactions between travelers and the system at a given point in time  System state must be measurable (via performance measures), to understand the accuracy of algorithms  For NGSIM Interaction mechanisms and dynamic behaviors must be taken into account when developing behavioral algorithmsInteraction mechanisms and dynamic behaviors must be taken into account when developing behavioral algorithms

18. Performance Measures (State)  Definition Measurements of state of system and individual vehiclesMeasurements of state of system and individual vehicles  Example performance measures Queue lengthsQueue lengths Travel timesTravel times Travel time reliabilityTravel time reliability  NGSIM behavioral algorithms must report enough information to produce a full set of appropriate performance measures

19. Summary  NGSIM scope Core models in scope, not full simulation packageCore models in scope, not full simulation package Of the core model, focus is on traveler behaviors and interaction mechanisms that determine resulting traffic propertiesOf the core model, focus is on traveler behaviors and interaction mechanisms that determine resulting traffic properties  Supporting components Influencing factors interface with behavioral algorithmsInfluencing factors interface with behavioral algorithms Interaction mechanisms are implementation details of behavioral models that are essential to the resulting traffic stream behaviorInteraction mechanisms are implementation details of behavioral models that are essential to the resulting traffic stream behavior Both must be taken into account, in order to validate behavioral algorithmsBoth must be taken into account, in order to validate behavioral algorithms