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ITS simulation in ITS Modeller

ITS simulation in ITS Modeller. PLATOS 20140305 Martijn van Noort. Simulation of ITS. Simulation of ITS is used in design or evaluation of ITS applications Important differences with “ standard” traffic management and planning issues (like traffic lights, new roads):

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ITS simulation in ITS Modeller

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  1. ITS simulation in ITS Modeller PLATOS 20140305 Martijn van Noort

  2. Martijn van Noort ITS simulation in ITS Modeller Simulation of ITS • Simulation of ITS is used in design or evaluation of ITS applications • Important differences with “standard” traffic management and planning issues (like traffic lights, new roads): • Driver behaviour is important • In-car systems may change the way in which vehicles drive • In particular, different vehicles (equipped, non-equipped, …) behave differently • Requires suitable microscopic simulation tools  ITS Modeller • Next: some examples

  3. Martijn van Noort ITS simulation in ITS Modeller Changing the way vehicles drive • Eco driving • Shockwave damping • Cooperative merging assistance

  4. Martijn van Noort ITS simulation in ITS Modeller Driver behaviour is important • Speed distributions for 3 versions of ISA and for unequipped cars without ISA informative intervening overrideable , intervening non-overrideable Source: LAVIA

  5. Martijn van Noort ITS simulation in ITS Modeller Does it matter? ~ ~ • Advice via speed signs, LED and in-car • Guaranteed green if advice is followed • But it is not always followed… LED 60 50 Speed profile v x

  6. Martijn van Noort ITS simulation in ITS Modeller Not everyone follows the advice  compliance rate Not all followers fully adopt advice  adaptation rate Large effect Medium effect Small effect Driving behaviour and penetration rate have big influence on outcome!

  7. Martijn van Noort ITS simulation in ITS Modeller Why a new tool? • Classic simulation packages do not have much built-in support for ITS • There typically is an API, but • Difficult to scope functionality (One  More  All) • Black box • So may be hard to simulate (certain) ITS  need more flexible tool • Requirements: • Models fully modifiable by user • White box modelling • Stable simulation engine (not open to user)

  8. Martijn van Noort ITS simulation in ITS Modeller ITS Modeller ITS Modeller NG Input • Network • Traffic demand (A to B) Sources: • Models for vehicles, drivers and roadside controllers Output • Network level effects of ITS: • Vehicle trajectories • Distributions of speed, headway, acceleration, … Each time step: Update vehicles, drivers and controllers traffic efficiency environ-ment traffic safety GIS VISSIM

  9. Martijn van Noort ITS simulation in ITS Modeller Features - Modelling Active models • Defined per model configuration • Framework has rules to combine them Parameters of a model Model categories • Routing behaviour • Lane change behaviour • Longitudinal behaviour • Vehicle dynamics • Sensors • Wireless communication • Controllers for Traffic lights, Dynamic speed signs, Variable message signs Model configurations • Vehicle types • ITS applications • Driver types and state • Roadside controllers • Users of ITS Modeller NG can • Develop and include their own models for • driver behaviour • vehicle dynamics • road side controller decisions • Use existing models • Adapt model parameters to their needs • Select and combine models • All through an easy-to-use GUI • And in a flexible model framework that allows combinations of models to function properly • Linked to Driver Model Library

  10. Martijn van Noort ITS simulation in ITS Modeller Modelling architecture: add your own models ITSModellerNG • Default models • Drivers • Vehicles • Controllers • User defined models • Drivers • Vehicles • Controllers Model interfaces (API) JAR • More user defined models • Drivers • Vehicles • Controllers JAR

  11. Martijn van Noort ITS simulation in ITS Modeller • Driver • Desired acceleration • Lane change • Route choice • Sensors • Communication • Vehicle • Acceleration • Roadside systems • Controller API • Driver • Desired acceleration • Lane change • Route choice • Sensors • Communication • Vehicle • Acceleration • Roadside systems • Controller • Collaboration between models in a model configuration (vehicle + driver type): • No hidden models (white box) no movement without models • Desired acceleration = minimum of all desired accelerations • Lane change = max priority lane change • Route choice: one cost model, multiple cost information suppliers • One vehicle model • General model structure: • getDesiredAcceleration(DriverContext)  desired acceleration, delay

  12. Martijn van Noort ITS simulation in ITS Modeller Example – Green speed for cyclists Master thesis project Joeri van Egmond, TU Delft, 2013 Master thesis project Theofili Apostola, TU Delft, ongoing

  13. Martijn van Noort ITS simulation in ITS Modeller Green speed for cyclists • What is effect of speed advice on number of stops and travel times? • How does it depend on • controller type: predictable (fixed time) or not • acceptance by cyclist: utility of green versus disutility of higher or lower speed; accounting for uncertainty (several models)

  14. Martijn van Noort ITS simulation in ITS Modeller Scenario

  15. Martijn van Noort ITS simulation in ITS Modeller Modelling Controller Acceleration Speed advice Signal timings Signal timings or speed advice Road side infra Sensor

  16. Martijn van Noort ITS simulation in ITS Modeller Results • Fixed time controller • ~20% fewer stops • Requires significant speed range (15-23 km/h) • Effect depends on speed range that cyclists accept

  17. Martijn van Noort ITS simulation in ITS Modeller Example – Parking guidance Master thesis project Manos Chaniotakis, TU Delft, 2014

  18. Martijn van Noort ITS simulation in ITS Modeller Parking guidance • Search traffic: 10-60% of all(inner) city traffic • Intelligent parking system (IPS) • Personalized service(on smart phone, navigation device) • Real-time monitoring of vehicle position • Finds parking place at lowest generalized cost(travel time, walking distance, monetary cost) • Parking lots and optionally on-street • Reservation, route advice and payment • What is effect on traffic?

  19. Martijn van Noort ITS simulation in ITS Modeller Parking guidance – how does driver behave? • Compliant driver with IPS follows advice of system • System advice is based on personalized generalized cost of available alternatives • Non-compliant driver & driver without IPS: default parking behavior • This is much harder to model! • Strategic behavior: trip, destination, departure time and mode choice depending on parking characteristics. • Tactical behavior: route choice and parking destination choice (parking type, parking location) • Operational behavior: searching/waiting time for parking destination and turning decisions at an intersection (for on-street parking) • Familiar and unfamiliar users

  20. Martijn van Noort ITS simulation in ITS Modeller Decision model for default parking behaviour Source: Thesis Manos Chaniotakis

  21. Martijn van Noort ITS simulation in ITS Modeller Modelling Controller Controller Destination & route choice Capacity, price Capacity, price Generalized costs Route cost Back office Controller Capacities, prices Capacities, prices Capacities, prices Road side infra Sensor

  22. Martijn van Noort ITS simulation in ITS Modeller Results • Assen network • Average total travel times • Large decrease if unfamiliar drivers switch to smart parking From To

  23. Martijn van Noort ITS simulation in ITS Modeller How do you get the system and driver behaviour? Test site Lab Simulation FOT +Controlled +Cost effective +Versatile +Large scale +Choice levels -Realism -Driver behaviour +Controlled +Realism -Driver beh. -Small scale -Operational only +Controlled +Realism -Driver beh. -Small scale -Tactical only +Realism +Driver beh. +Large scale +Choice levels -Uncontrolled -Costly Or vice versa: determine relation between behaviour parameters and effect Realism, driver behavior, cost Versatility, control Choice levels, scale

  24. Martijn van Noort ITS simulation in ITS Modeller Conclusions • Simulation of ITS requires tools that allow modelling of driver behaviour and ITS applications • Especially if ITS does not force behaviour and only “persuades” • Behaviour can have large influence on outcome • This may be difficult with classical tools • ITS Modeller has stable simulation engine but fully modifiable models for drivers, vehicles, controllers in white box set-up.

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