Presentation on Real Time Systems and Adaptive Cruise Control

Roadmap Introduction to RTS Problem Definition / Motivation Adaptive Cruise Control (ACC) Driver Models Functional Model & Task Model Extensions to Functional Model Conclusion & Future Work References

Functional Design & Mapping HW1HW2HW3HW4 Hardware Interface RTOS/Drivers Threa d Architectural Design F1 F2 F3 F4 F5 Functional Design (F3)(F4) (F5) (F2) Source: Ian Phillips, ARM VSIA 2001 Source: Ian Phillips, ARM VSIA 2001

What is “real” about real-time? computer world  e.g., PC  average response for user  Interactive  occasionally longer  reaction: user annoyed  computer controls speed of user  “computer time” real world  Industrial system, airplane  environment has own speed  reaction too slow: deadline miss  reaction: damage, pot. loss of human life  computer must follow speed of environment  “real-time”

A real-time system is a system that reacts to events in the environment by performing predefined actions I/O - data Real-Time Systems Real-time computing system event action within specified time intervals. time

Real-Time Systems: Properties of Interest Safety: Nothing bad will happen. Liveness: Something good will happen. Timeliness: Things will happen on time - by their deadlines, periodically,...

In a Real-Time System… correct value delivered too late is incorrect e.g., traffic light: light must be green when crossing, not enough before Real-time: (Timely) reactions to events as they occur, at their pace: (real-time) system (internal) time same time scale as environment (external) time Correctness of results depends on value and its time of delivery

Types of RT Systems Dimensions along which real-time activities can be categorized: how tight are the deadlines? --deadlines are tight when laxity (deadline -- computation time) is small. how strict are the deadlines? what is the value of executing an activity after its deadline? what are the characteristics of environment? how static or dynamic must the system be?

deadline (dl) + Hard, soft, firm Hard -- result useless or dangerous if deadline exceeded Ex: Aircraft, Chemical Plant value time - hard soft Soft -- result of some - lower value if deadline exceeded Ex: Multimedia, Interactive video games Firm -- If value drops to zero at deadline

Timing Constraints Real-time means to be in time --- how do we know something is “in time”? how do we express that? Timing constraints are used to specify temporal correctness e.g., “finish assignment by 2pm”, “be at station before train departs”. A system is said to be (temporally) feasible, if it meets all specified timing constraints. Timing constraints do not come out of thin air: design process identifies events, derives models, and finally specifies timing constraints

Overall Picture Physical properties of environment Model-design Timing constraints Analysis, Testing Run-time dispatching (In field use) Functional Temporal

Timing Properties Periodic –activity occurs repeatedly –e.g., to monitor environment values, temperature, etc. Aperiodic –can occur any time –no arrival pattern given Sporadic –can occur any time, but –minimum time between arrivals mint time

Who initiates (triggers) actions? Example: Chemical process –controlled so that temperature stays below danger level –warning is triggered before danger point …… so that cooling can still occur Two possibilities: –action whenever temp raises above warn -- event triggered –look every int time intervals; action when temp if measures above warn -- time triggered

Other Issues to worry about Meet requirements -- some activities may run only: –after others have completed - precedence constraints –while others are not running - mutual exclusion –within certain times - temporal constraints Scheduling –planning of activities, such that required timing is kept Allocation –where should a task execute?

Project Motivation

Motivation (Cont…) –Partitioning of system into TT and ET domains –Process Mapping –Optimization of parameters corresponding to communication protocol. Sequence and Slots of TDMA (TTC) Priorities of Messages (ETC) –Schedulability

Adaptive Cruise Control Adaptive Cruise Control: –automatically adjusts vehicle speed to maintain a driver-selected safe distance from the vehicle ahead in the same lane. –It then returns to the set speed when traffic clears. Requirements: –The speed should be kept close to the SET speed, if there is no vehicle ahead. –Timegap should be maintained at x sec. –Manual intervention, UI, etc…

Functions Identified Computing Current speed of our vehicle Leading Vehicle related Task Controlling Speed of our Vehicle Controlling the Throttle Controlling the Brake Detecting Manual Intervention UI to the Driver Periodicity of Tasks Hard, Firm; Periodic, Aperiodic…

Human Driver Model Structure of Human Driver in Car-Following Stimulus-Reaction Model

Car Following Models Linear Follow-the-Leader Model –Stimulus: Velocity Difference b/w Leader and Follower –Reaction: Acceleration command to vehicle Look-Ahead-Model –Driver observes the behavior of three vehicles ahead of him. –Stimulus: Majority direction of Acceleration –Reaction: Acceleration command using switching logic Others…

Simple Car Following Model v l Velocity of Leader v f Velocity of Follower r l Retardation of Leader r f Retardation of Follower t r Short Reaction Time

Acceleration profile of vehicle D min = D i – D i-1 Di = D1i + D2i + D3i

Src: Prof. Shashikant's Control System Lec-1 in DEP Mode ACC System Design (desired vehicle speed) Control I/P Physical Process Sensors Actuators Adaptive Adaptive Cruise Cont. Reference Input Actual output Sensor Noise Actuator Noise Sensed O/P Desired Control I/P Disturbances (accelerator pedal (throttle) position, brake pedal position) (wheel speed sensor) (air drag, grade, friction etc) (vehicle speed)

Src: Prof. Shashikant's Control System Lec-1 in DEP Mode Process Model Physical Process Actual Output Control I/P Disturbances E 1/M G 1/R w

Pictorial View Friction Estimator Speed Sensor Radar System Roadside Signals Control Algorithm Throttle System ABS Actuators Sensors Schematic Picture of Control Algorithm and its Environment SPEED Module DISTANCE Module Min-value Control Signal to the Actuators The structure of Control Algorithm asas adad

Block Diagram

Flow Chart

(cont…)

State Diagram

g a b Wheel S IR S f Speed Set Thrott le S Brake S c d e Throt tle A Brake A Curr_Thr Pos Curr_Br Pos Precedence Graph showing communication relation

Task Graph

Extensions to Functional Model under consideration Adaptive to –Driver Reaction Time –Roadside Signals –Friction b/w road and tyre (ABS) –Relative positioning in the lane

Future Work Partitioning tasks as TT and/or ET and as Soft, Hard or Firm. Writing Algorithm Allocation of Tasks Schedulability One or two similar application if time permits