Efficient Real-Time Support for Automotive Applications: A Case Study

Gurulingesh R.

Gurulingesh R., Neera Sharma , Krithi Ramamritham, Sachitanand Malewar

Indian Institute of Technology BombayINDIA

Motivation(1/2)• Rapid increase of computer-controlled functions in

automotive applications– e.g.: New Mercedes S-class cars employ atleast 70 networked

ECUs

• Independent black-box implementation is practically infeasible:– Cost, Integration Complexity

Motivation(2/2)

• Safety-critical applications:– Brake-by-Wire, Collision Avoidance system,

Adaptive Cruise Control, etc…– deal with critical data and deadline bound

computations– have stringent requirements on:

• Freshness of data• Completion time of tasks

Introduction to ACC (1/2)

• Adaptive Cruise Control tries to maintain:

• Safe Distance when there is a leading vehicle

• Set Speed when there is no leading vehicle in its path

Introduction to ACC (2/2)

• Extension of Cruise Control.

• Operates either in

• Distance Control state

• Speed Control state

Des_Dist = Host_Vel * Timegap + ∆ where

Host_Vel is Host Vehicle velocity

TimeGap is set by the driver

∆ for additional safety

Focus of Our Work

• Efficient utilization of computing resources while satisfying safety-critical properties

Issues (1/3)

1. Effective tracking of dynamically varying data.

… …

General Practice: Prepare for the Worst

Over-Sampling

…

Di

st

Time

Issues (2/3)

Unnecessary Updates

2. Timely updates of derived data

WS1 WS2 WS3 WS4

HostVel

W4 W1 W2 W3 Radar

RDist RSpeed

LeadDist LeadVel

General Practice: Periodic updates

Issues (3/3)

3. Some tasks will execute only in some modes

Poor CPU utilization

Not modular

Scheduling Overhead

• Adapt parameters when lead car is far

• Sense adjacent lane, time to collision when car is near

General Practice: Single mode design for simplicity

Our Approach(1/3)

1. Dual Mode System:

• Two mutually exclusive phases of operation– Safety Critical Mode– Non Safety Critical Mode

• Current mode depends on:– Distance of Separation– Rate of change of Distance

LeadDist RoD Mode

FAR DECR-FAST SC

FAR INCR-FAST NC

FAR DECR-SLOW NC

FAR INCR-SLOW NC

CLOSE ---- SC

FOLLOW ---- RETAIN

Our Approach(2/3)

2. Real-Time Data Repository:

• Two level data store– Environment Data Repository– Derived Data Repository

• Task Scheduling– Constant Bandwidth Server (CBS)

Our Approach(3/3)

2. Real-Time Data Repository:

Hierarchical ACC Controller

Upper-level controller

Lower-level controller

(EDR)

Current status

Stable store

Log currentstatus

Raw data-items

Base data-items

host_vel

ang_vel

Sensor parameters

Controller constants

To actuators

Update DDR

store desired velocity

Read sensor values

` Read DDR

On demand

update

lead_vel

separation

radar_data

(DDR)

Robotic Vehicle: Experimental Setup

Capabilities:• Obstacle detection Range

– 2m

• Maximum speed– 0.50 cm/s

• White-line following

Results & Observations

• Basic Experiments: 1. Cruise Control Set Speed = 25 cm/s

Results & Observations (cont…)

• Basic Experiments: 2. ACC: Varying Velocity

- Velocity Response

Results & Observations (cont…)

• Basic Experiments: 2. ACC: Varying Velocity

- TimeGap

Results & Observations (cont…)• Basic Experiments:

– 1. Cruise Control• Set Speed = 25 cm/s

– 2. Adaptive Cruise Control• Varying Velocity

1. ACC tries to maintain:

Set speed when there is no leading vehicle

Safe Distance when there is leading vehicle

2. Variation in graphs due to Shaft Encoder error

Results & Observations (cont…)• Real-Time Data Repository Experiments:

– Task under observation: DistT (which updates DoS)– Threshold Value: 5cm– Leading vehicle with uniform speed

Results & Observations (cont…)• Real-Time Data Repository Experiments:

– Task under observation: DistT (which derives DoS)– Threshold Value: 5cm– Leading vehicle with varying speed

Results & Observations (cont…)

• Real-Time Data Repository Experiments:

– Task under observation: DistT (which derives DoS)– Threshold Value: 5cm– Time Window: 0-12 sec

DistT Task Invocation

Leading Distance With 2-level Without 2-level

Const 3 40

Incr-Decr 16 40

Results & Observations (cont…)• Real-Time Data Repository Experiments:

– Task under observation: DistT

DistT Task Invocation

Lead Dist With 2-level No 2-level

Const 3 40

Incr-Decr 16 40

– Threshold Value: 5cm

1. Less number of Updates

2. Compared to conventional approach:

Efficient usage of computing resource

Functionality/Safety not affected

Results & Observations (cont…)• Dual Mode Experiment:

– Mode change criteria: Lead Dist ≤ 65 cm/s– Periodicity of tasks: P(SC mode) = ½ * P(NC mode)

Results & Observations (cont…)

• Dual Mode Experiment:

– Mode change criteria: Lead Dist ≤ 65 cm/s– Periodicity of tasks: P(SC mode) = ½ * P(NC mode)

Results & Observations (cont…)• Dual Mode Experiment:

– Mode change criteria: • leading distance: 65 cm/s

– Periodicity of Tasks: • P(SC Mode) = ½ * P(NC Mode)

1. Compared to conventional approach:

Efficient usage of computing resource

Functionality/Safety not affected

2. Conservative Approach while deciding SafeDist

Contributions

• Presented issues involved in developing real-time support for ACC

• Efficiently utilized processor capacity by designing ACC using following concepts:

• Mode change• Real-time data repository

• Provided scheduling strategies to meet timing requirements

Ongoing Work

• More analysis of the system design (mode-change criteria, threshold values, etc.)

• Application needs are being mapped to distributed platform

• Study of controller’s stability and performance

• Usage of communication protocols such as CAN or TTP

References• Petros Ioannou; Cheng-Chih Chien. “Autonomous Intelligent

Cruise Control”. IEEE Trans. On Vehicular Technology, 42(4):657-672, 1993.

• Thomas Gustafsson; Jörgen Hansson. “Dynamic on-demand updating of data in real-time database systems”.

In Proceedings of ACM SAC 2004.

• Gerhard Fohler; “Flexibility in Statically Scheduling Real-Time Systems”. PhD Thesis, Technischen Universitat Wien Austria, Apr. 1994.

• L. Sha; R. Rajkumar; J. Lehoczky; K. Ramamritham. “Mode Change Protocols for Priority-Driven Preemptive Scheduling”. In Journal of Real Time Systems, 1(3):243-265, Dec 1989.

THANK YOU

Embedded Real-Time Systems Group

Indian Institute of Technology Bombay

INDIA

http://www.it.iitb.ac.in/car/