Mafia II Bringing city to life Martin Brandstätter Jan Kratochvíl

Content Ideas for creating living city Filling city with elements Basics of artificial intelligence Specific examples: –Pedestrians –Traffic cars

Living city Full of life Variability No restrictions for player Seamless streaming

Filling city with elements Static geometry Grass, garbage, etc Translocated objects Pedestrians Cars

Empty street

Translocated objects Translocator Many types of objects –Lamps, chairs, benches –Billboards, neons, traffic signs, semaphores –Trees, shrubs –Action points, and more

Translocator Multiple grids Storing only GUID, position, rotation & scale High & Low range Spawn is not optional

Street with translocated objects

Pedestrian spawning Where to spawn? –Position –Visibility –Usability Spawn points –Kynapse nodes

Kynapse visualization

Pedestrian despawn When to despawn a Pedestrian? –Is too far away –Is not visible for too long –Is not in any action Line of death

Car Spawn Little bit more complicated Data from roadmap Three types –“Translocated” –Parked –Moving

Spawn in black area Annulus P

Egg P

Advanced Egg P

Spawn points example

Car despawn Reasons to get despawned: –Not visible and not moving towards player –Be too far away and out of sight Visible cars are never despawned Police has special rules

Empty street

Street with translocated objects

Final Street

ActionPoints Sidewalk graph with crossings Actionpoints Destructible Objects with ActionPoints

Basics of artificial intelligence Brain Hierarchy Black Board Messaging Basic Behaviours Behaviour tree Ai and Script Comunication

Brain Hierarchy Small Brain Base Brain Single Brain Human Brain Car Brain Boat Brain Train Brain Team Brain

Basic Behaviours brain object small parallel selector composite team behaviour

More Behaviours Desire Desire Commander Desire Composite Slave and mapping factory

selector commander Composite commander commander commander Parallel Slave Action 0 Action 1

Ai and Script Communication Designers demands –script running in parallel with AI –script running without AI –script running with some parts of AI

Script Configuration Alive Parallel ScriptParallel Action 0 Action 1 Main Selector Desire Script AI Desire 0 AI Desire 1

Script commands Lua Script Message New Command Move,Turn,Anim,.. Desire Script Parallel Script

Script wants Exclusive Control Lua Script Message Script Control TRUE Desire Script Parallel Script

Script Gains Exclusive Control Lua Script Message Script Control TRUE Desire Script

Script Returns Control to AI Lua Script Message Script Control FALSE Desire Script Parallel Script

AI Gains Exclusive Control Lua Script Message Script Control FALSE Desire Script

AI wants Exclusive Control Lua Script Message AI Control - Reason Selector Script

Civilian Archetype Archetype configuration Behavior sub-tree wander Action-Point scripts

Wander Configuration Wander Parallel Wander Selector Crossing AP Scan Get In car Special Desire Wander Around Wander Slave Wander Style

Driving Roadmap Wandering driver Hunter – police, gangster, … Escaper – taxi, gangster, mission car

Roadmap Catmull-Rom splines Whole city roadmap is about 400Kb –Including all necessary meta information No 3 rd party library Crossroads are defined using splines as well

Catmull-Rom spline Special case of cubic Hermit spline Relatively easy to compute Spline is going through its interpolation points Tangents are continuous over multiple segments

Roadmap

Basic driving 1.Interpolate some position before you 2.Set wheels to point at this position 3.Set speed to something 4.You are done

Speed Desired speed is influenced by –Behavior – traffic lights, crossings, follower, … –Obstacle –Curve Every “desire” can only lower the desired speed

Curve speed Iterative algorithm Input –Preferred deceleration –Centripetal acceleration –Expected braking distance –Max speed

Curve speed ca – centripetal acceleration cr – curve radius L – segment length

Behavior speed Example: stop before crossing d – distance to crossing a – preferred deceleration of car

Obstacle speed Obstacle detection –Subdivision queries – no static scene Detection ahead on desired path Avoid obstacle if possible and desirable Adjust speed to obstacle speed Aggressiveness playing its role

Navigation point Interpolation on spline Shift to fit correct lane Random shift Obstacle shift

Navigation points

Crossroad Team AI Priority for each car Main roads Traffic lights Aggression & green wave

Crossroad

Hunter Police & gangsters Need to go off roadmap Player drops info behind him Need of collision scene tests

Escaper Special case of wandering car May be aggressive Crossroad trespassing is not random Has to ensure that he will reach its destination

Special behaviors Avoiding special cars Jam detector Collision detector Horn reaction …

Q&A