CASE STUDY: PEGASUS

Leeds, February 3rd 2016

Let’s do it now

In 1901 Daimler launched the first modern car with the Mercedes 35 HP. At the same time Gottlieb Daimler said: „The worldwide demand for automobiles will not exceed one million if only due to the lack of chauffeurs.“

It is time to solve this obviously very old problem by rollout of systems for highly automated driving!

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Time table

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© Continental

• What criteria have systems for highly automated driving to fulfil?

• What is necessary in order to assure, that systems fulfil those criteria, actually?

PEGASUS core issues

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TP 4

_____________________

Lead: Continental

TP 3

_____________________

Lead: Daimler, BMW, TÜV Süd

TP 2

_____________________

Lead: Opel

TP 1

_____________________

Lead: Volkswagen

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Sub projects (TPs) and partners

ERGEBNISREFLEKTION &EINBETTUNGTESTEN

SZENARIENANA LYSE &QUALITÄTSMAßE UMSETZUNGSPROZESSE

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Current status of automated vehicle testing

Prototypes Test tools Products

Current status

Characteristics of test levels

Virtual tests Field tests

© Palisade Corporation

Proving ground tests

Analysis of a huge number of scenarios, environments, system configurations and driver characteristics

Reproducibility by use of driving robots, self driving cars and targets; critical manoeuvres are possible

Investigation of real driving situations and comparison with system specifications

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Socially accepted risk criteria

General approach: Risk = Frequency x Damage Accident statistics on German „Autobahn“

log(

Freq

uenc

y)

log(Damage)

1

10

100

0 1 2 3Severity

Acci

dent

rate

per

1 b

n. k

m

With assumption, that there is 1 order of magnitude between severity levels according to ISO 26262:

Sources: H.-P. Schöner, CESA 2014, and DESTATIS (German Federal Statistics Agency) 2013

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Consolidation of results

Assessment Results

Scenarios (exposition, environment,

…)

Virtual Assessment

SW in the Loop

HW in the Loop

Driving Simu-lator

…

Vehicle Testing (NDS, fleet, proving ground, …)

Road Users (driver, pedestrian, …)

Vehicle (driving dynamics, …)

Sensors (radar, lidar, camera, …)

relevant situations for further investigation

models validation, verification

108 scenarios 103 scenarios 102 scenarios

results

Model Database

Legend:

Situation space mainly covered

by virtual assessment

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Thank you for your attention! For more information: www.pegasus-projekt.info (online soon)

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