A DIYD (DO IT YOURSELF DESIGN) SYSTEM FOR VEHICLE

DESIGN BASED ON 3D VISUALIZATION AND ONTOLOGIES

Lambros Makris, Nikolaos Karatzoulis, Dimitrios Tzovaras

Informatics & Telematics Institute, 1

km Thermi-Panorama, Thessaloniki, Greece

Evangelos Bekiaris

Hellenic Institute of Transport, 6

km Charilaou - Thermi, Thessaloniki, Greece

Keywords: DIYD system, Configurator, 3D Visualization, Ontologies.

Abstract: The customization level of vehicles is growing in order to deal with increasing user needs. Web browsers

are becoming the focal point of vehicle customization, forming personalized market places where users can

select and preview various setups. However the state of the art for the completion of the transaction is still

very much characterized by a face-to-face sales situation. Direct sales over the internet, without sales person

contacts, are still a small segment of the market, of only a few percent, for European manufacturers. This

paper presents an Intelligent DIY e-commerce system for vehicle design, based on 3D Visualization and

Ontologies that aims at enabling a suitable representation of products with the most realistic possible

visualization outcome in order to help prospective customers in their decision. The platform, designed for

the vehicle sector, includes all the practicable electronic commerce variants and its on-line product

configuration process is controlled by an ontology that was created using the OWL Web Ontology

Language.

1 INTRODUCTION

Automotive enterprises are becoming more

customer-centric to meet today’s challenging market

demands. This calls for restructured B2C relations

and related new technologies. The automotive

industry has furthermore become highly networked

and requires improved communication on products

and components in relation to its B2B relations.

Information and communications technology

(ICT) can be used to support business and design

activities. ICT does not change the fundamental

goals of any organisation but makes it possible to

optimize and coordinate design, manufacturing and

marketing. In the automotive industry, ICT can:

• Improve design procedures;

• Allow optimization of design, manufacturing

and marketing;

• Fine tune manufacturing processes;

• Provide the best product or service to current

and potential customers; and

• Respond rapidly to customers’ needs.

It has been envisioned that e-commerce and mass

customization will emerge as a primary style of

manufacturing in the coming decade and beyond.

The integration of design, manufacturing, and

logistics over the Internet will be the trend for the

factory of the future. Effective supply chain

management for mass customization will enhance

profitability through a synergy of increasing

customer-perceived value while reducing the costs

of design, production and distribution. Companies

successfully adapting to this new style of

manufacturing will be able to reduce reliance on the

traditional marketing channels, to gain more market

shares globally, and to achieve high-efficiency

product realization.

This technology can enhance the established

strengths of nowadays’ industries in global

manufacturing. It will benefit a wide variety of

industries such as electronics, machinery,

appliances, and logistics.

376

Makris L., Karatzoulis N., Tzovaras D. and Bekiaris E. (2008).

A DIYD (DO IT YOURSELF DESIGN) SYSTEM FOR VEHICLE DESIGN BASED ON 3D VISUALIZATION AND ONTOLOGIES.

In Proceedings of the Third International Conference on Computer Graphics Theor y and Applications, pages 376-383

DOI: 10.5220/0001096103760383

 SciTePress

2 DIYD SYSTEMS AND THE

AUTOMOTIVE BUSINESS

DIYD (Do It Yourself Design) systems enable

companies to extend their markets anywhere,

anytime via the Internet. BMW, for example, sells

six out of ten cars to order. Although the order-to-

delivery time is very long, up to two months, much

longer than that for regular cars, customers are

prepared to wait (The Economist 2004). However

current systems usually only allow for a simple

selection of options and a visual presentation of the

result in the format of data sheets, tables and

photographs of the vehicle exteriors and/or interior.

The configuration system is not driven by customer

requirements. The user has to interpret to what

extent the various technical features will satisfy

his/her functional requirements and needs.

In order to support the user in his/her choices,

information should be presented in the most

comprehensible way. This can be accomplished by

offering the user detailed access to information using

reconfigurable electronic catalogues and presenting

the resulting configuration using 3D virtual

prototypes.

The use of 3D virtual prototypes in a virtual

environment can enhance visualisation and

perspective viewing of the designed car. Unlike 2D

graphics, users can interact via the web browser to

navigate around an object and to move and rotate it.

This type of Virtual Reality is much more flexible

than a static image and allows for an apparently

infinite number of different views on the vehicle. It

is characterized by the use of 3D computer models

presented on a 2D computer screen using 2D

interaction devices like a mouse. The use of such

interactive visuals has already undergone two cycles

of hype in the internet business. But it was not

successful due to overloaded solutions and

bandwidth problems of the internet. Recently the

technologies behind have gained momentum in the

European automotive industry in the field of Digital

Mock-ups (Döllner & Kellner 2000), which are used

very successfully in the development process

employing again the internet for both intranet and

B2B communication. Thus the time has come to

transfer this success to field of mass customization

and DIY design.

But Virtual Environments go beyond. Immersive

systems allow for a dynamic stereoscopic view on

the vehicle exterior and interior and add intuitive 3D

interaction by tracking technology to the user

interface. These sophisticated VR solutions are

currently used in vehicle design and development.

Internal projects in the automotive industry showed

that VR technology was still too expensive to be

used in customer communication and vehicle

configuration around 5 years ago. This was mainly

due to the use of expensive hardware. In the

meantime inexpensive VR systems on commodity

hardware basis have been developed in Europe, e.g.

within the VIEW project (Wilson & D’Cruz 2006).

These results can be further exploited to develop

appropriate VR systems for mass customization and

visualisation.

3 THE CATER SYSTEM

As already stated, current systems usually only

allow for a simple selections and 2D visual

presentation. We present an intelligent and user-

friendly e-commerce solution, namely CATER, by

adopting additional technologies such as a

configuration engine supported by ontologies,

advanced search mechanisms, and 3D visualisation

in a virtual reality environment. The focus of the

system is on the vehicle industrial sector; however

the intention is that the system will be suitable for

suppliers, and wholesalers, from other sectors, such

as furnishing, clothing etc.

In our use scenario a customer is connected to

the CATER system using a traditional web browser.

He searches in the 3D object database, by example,

to find particular components that are of interest to

him. The system, using an ontology, prevents him

from selecting components which are incompatible.

At the same time the user can pose particular

constraints, such as maximum cost, which are

honoured by the system. He can then use a VR

interface to connect the components together and

form a design that suits him. The final selection can

then be saved or forwarded to the factory for

realization. Figure 1 presents the basic modules of

the CATER system architecture.

Figure 1: The main modules of the DIYD system.

A DIYD (DO IT YOURSELF DESIGN) SYSTEM FOR VEHICLE DESIGN BASED ON 3D VISUALIZATION AND

ONTOLOGIES

377

3.1 Intelligent Configurator Module

and Ontology

The Intelligent Configurator module in CATER is a

web based application that allows the user to

assemble vehicles based on the available vehicle

parts that are being stored in the systems repository

maintained by the vehicle manufacturer. Figure 2

displays the Units of the Configurator module.

Figure 2: The Units of the Configurator Module.

The Assembly Unit allows the user to insert

individual 3D objects to the scene that can consist of

a fully functional vehicle. The user can compose the

desired vehicle according to his/her needs by

selecting the vehicle’s parts. The vehicle part and the

texture selection processes are being controlled by

the restriction mechanisms that are generated from

the system Ontology (Kompatsiaris et al 2005,

Tsampoulatidis et al 2004, Mezaris et al 2003). The

main functionalities of the Assembly Unit are the

following: (i) Insertion of 3D object parts, (ii)

Selection of texture and (iii) Assembly process

based on dynamic constraints (e.g. weight).

Figure 3: The web interface of the Configurator.

Once the user has selected the preferred vehicle

parts then the selected parts are loaded to the 3D

scene and the user is allowed to modify the

colouring scheme of each selected part by activating

the textures menu option (Figure 4). The allowed

colouring scheme is defined in the CATER

ontology.

Figure 4: Modification of the colouring scheme of the

inserted 3D parts based on the CATER ontology.

The purpose of the Visualization Unit is to

record and store the 3D object assembly steps in

real-time. The assembly sequence is being stored in

the 3D animation repository for future reproduction.

The Visualization Unit allows the user to select

various viewpoints in order to preview the assembly

process from various viewing angles (Figure 5).

Figure 5: The viewpoints supported by the Visualization

Unit.

The Animation Unit allows the reproduction of

the vehicle parts assembly processes that are stored

in the animation system repository. In the Animation

Unit the user can control the viewpoints and the

playback of the loaded vehicle assembly process.

Animations can be prepared by the manufacturer to

enhance the user experience or to highlight

particular features of the vehicle. Animations can

also be useful in situations where the assembly order

is important for the customer to understand how a

particular set of parts work together. The web

interface of the Configurator Module is depicted in

Figure 3.

3.2 3D Visualisation Module

Virtual Reality (VR) interfaces can provide the most

realistic presentation of a configuration for end

users. It combines high quality visualization with the

correct perception of depth and scale, which enables

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378

a feeling for the roominess of the interior of a car.

Additionally, a highly intuitive interface allows easy

manipulations of models, assemblies and parts.

Combined with simulations (e.g. physics or a man-

model), the models can be evaluated in terms of

packaging (fit of the components) of ergonomics.

The 3D Visualization Module of the CATER

system is realized on the Visualization and

Animation Units. The structure of the individual 3D

scenes supported by the 3D Visualization Module

can be seen in Figure 6.

The 3D scene contains the viewpoints, the

lighting of the 3D world, the background, the 3D

objects and the object functionalities (interactions)

that are created dynamically according to the

ontology specifications. The user interaction with

the 3D scene is achieved by the use of predefined

VRML Protos. For every 3D object that is inserted

in the 3D scene an animation representing its

assembly process is dynamically generated.

Figure 6: The 3D scene structure of the 3D Visualization

Module.

The playback functionalities of the assembly

process are controlled by a panel (Figure 7) that was

developed using several VRML sensors

(TouchSensor & PlaneSensor).

Figure 7: The assembly process control.

3.3 3D Geometry Search Module

The 3D geometry search module utilizes novel

algorithms for low-level feature extraction from 3D

objects, based on geometric characteristics. The

algorithms are robust to affine transformations

(rotation, translation, scaling) and are applied to 3D

objects regardless of their degeneracies, formats and

levels of detail. This results in a more compact

representation of the objects, which uniquely

characterizes them. The 3D search module can be

used whenever the user wants to provide a specific

part of a vehicle as a query and retrieve similar

objects from the repository.

Every 3D object is described with a rotation,

scaling and translation invariant descriptor vector,

which is formed according to the Spherical Trace

Transform (STT) (Zarpalas at al 2007). Initially,

every object is translated and scaled so that all

objects are expressed in the same coordinate system.

To achieve the latter, a local coordinate system has

been defined centred to the centre of mass of the

object and scaled so that the object fits to the unit

sphere. Then, the object’s binary volumetric

function is computed

and the STT (Figure 8) is performed as follows:

• A set of radius segments is defined. Every

radius segment Λ

is formed by the

intersection of a radius (η

,ρ

) with the object.

• A set of spheres, concentric to the unit sphere is

defined.

• A set of plane segments is defined for every

sphere S

. Every plane segment Π

is formed

by the intersection of a plane tangent to the

sphere at point P

with the object.

The points P

and radii r

are uniformly

distributed on the sphere’s surface exploiting the

icosahedric-based tessellation.

Every Λ

segment is treated as a one-dimensional

signal and descriptors based on classical 1D Discrete

Fourier Transform and an integration transform are

computed. Every plane segment Π

is treated as a

2D signal and descriptors based on the Krawtchouk,

the Zernike and the Hu moments, the polar wavelet

transform and the 3D Radial Integration Transform

(Daras et al 2006) are computed. Then, the spherical

Fourier Transform is applied separately on every

extracted descriptor, so as the final descriptors are

invariant under rotation and, thus, appropriate for 3D

object matching.

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Figure 8: The Spherical Trace Transform.

The matching procedure is based on a mixture of

the weighted Minkowski L1 distance and the

normalized distance.

Equation 1: Weighted Minkowski L1 distance, where D

(k) is the k-th element of object.t T descriptor vector and

,T is the assigned weight

The computation of the weights for every single

descriptor is based on the statistical behaviour of

every descriptor for every class (e.g. mean value,

standard deviation, etc). Two different methods for

weight assignment have been proposed. The method

has been tested on the Princeton Shape Benchmark.

Figure 9 depicts the results in terms of precision and

recall diagrams.

Figure 9: Efficiency of the STT using combination of

different descriptors (Krawtchouk, Zernike, Hu etc).

3.4 Configurator Implementation

The Configurator Module is implemented using the

Java programming language. The system runs on

Apache Jakarta Tomcat as a Java Servlet and it is

based on the Jena framework, which is a Java

framework for building Semantic Web applications.

The ontology was created using the OWL Web

Ontology Language, and the Protégé OWL-Plugin.

The persistent store of the ontology is achieved

using the persistence subsystem of Jena, while the

3D visualization was developed using the VRML

standard and External Authoring Interface (EAI)

mechanisms.

The OWL-DL profile which was used in order to

create the ontology, is based on Description Logics.

Description Logics are a decidable fragment of First

Order Logic2 and are therefore amenable to

automated reasoning. It is therefore possible to

automatically compute the classification hierarchy

and check for inconsistencies in an ontology that

conforms to OWL-DL (Horridge et al 2004).

3.4.1 Specification of Classes

The classes in the Ontology are interpreted as sets

that contain individuals. They are described using

formal descriptions that state precisely the

requirements for membership of the class. For

example, the class “Vehicle” contains all the

individuals that are of type Vehicle in the CATER

domain. The taxonomy of the classes is being

achieved using the superclass-subclass model

hierarchy.

Class Model Object Type Property

Figure 10: Example of the class hierarchy of the class

“Vehicle” and an example of an Object Type Property for

the individual “volvo_1”.

3.4.2 Specification of Properties

There are two types of properties supported by our

ontology a) Data Type Properties and b) Object

Type Properties. These OWL Properties represent

relationships between two individuals.

In OWL, properties are used to create

restrictions. In our ontology the restrictions were

GRAPP 2008 - International Conference on Computer Graphics Theory and Applications

380

used to restrict the individuals that belong to a class.

We used the universal quantifier ∀ restrictions to

constrain the relationships along a given property to

individuals that are members of a specific class. For

example, the universal restriction ∀ hasCabin

cabin_1 describes the individuals all of whose

hasCabin relationships are members of the class

Cabin.

Table 1: List of the property restrictions applied to the

example class Volvo.

Class: Volvo

NECESSARILY

Truck

hasCabinEngineType

hasEngineType

hasRearAxle

accessType write

INHERITED

Root

owl:Thing

Vehicle

Cardinality restrictions were used to define the

order in which the individual object parts should

appear during the 3D assembly process (i.e. real-

time animation). The cardinality restrictions

provided the way to describe the class of individuals

that have at least, at most or exactly a specified

number of relationships with other individuals or

datatype values.

The hasValue restrictions, denoted by the

symbol ∋, were used to describe the set of

individuals that have at least one relationship along a

specified property to a specific individual. For

example, when we wanted to predefine the

dimensions of an individual object part we used a

hasValue restriction (dimensions ∋ “40-50-80”).

3.4.3 RDQL – Data Oriented Query Model

for the CATER Ontology

The CATER ontology uses an implementation of the

RDQL query language for quering RDF models

using the Jena API. RDQL provides a data-oriented

query model so that there is a more declarative

approach to complement the fine-grained,

procedural Jena API.

RDQL queries only the information held in the

models; there is no inference being done. The

RDQL system receives the description of what the

application requests, in the form of a query, and

returns that information, in the form of a set of

bindings.

RDQL is an implementation of the SquishQL

RDF query language, which itself is derived from

rdfDB. This class of query languages regards RDF

as triple data, without schema or ontology

information unless explicitly included in the RDF

source.

RDF provides a graph with directed edges - the

nodes are resources or literals. RDQL provides a

way of specifying a graph pattern that is matched

against the graph to yield a set of matches. It returns

a list of bindings - each binding is a set of name-

value pairs for the values of the variables. All

variables are bound (there is no disjunction in the

query).

Figure 11: Graphic representation of an example RDQL

query used for the CATER ontology.

3.5 The e-shopping Platform in

Practice

The use of the CATER platform “brings” advantages

for both suppliers and buyers regarding (i) the

cutback of transaction costs, (ii) the use of

automated supply procedures, (iii) economy of scale,

(iv) wide access on both local and international

markets, (v) dynamic real-time price

mechanisms/modules and (vi) the use of

compatible/expandable technologies.

The requirements of the described CATER

platform for vehicle products that together with the

Intelligent Configurator Module and the 3D

Visualisation Module comprises the advanced 3D

Shop system are:

• search and present all the available products,

based on multi-criteria search engines

• group products into multilevel categories (set

by the e-shop administrator)

• make offers/ sales and promote them

• update both the product catalogue and all items’

availability (set by the e-shop administrator)

• create/use shop baskets (by the end buyers)

• provide several convenient pay/receive methods

• provide a secure e-payment credit card

transaction (with the use of HTTPS and SSL

protocols).

A DIYD (DO IT YOURSELF DESIGN) SYSTEM FOR VEHICLE DESIGN BASED ON 3D VISUALIZATION AND

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However, the efficiency and overall quality of an

e-commerce service depends “heavily” on its

automatic connection with the existing ERP

(Enterprise Resource Planning) system for the

catalogue, prices, stock and product update. In order

to integrate all the available ERP data with the e-

shop database, a powerful staging mechanism is

developed and securely transfers all necessary data.

This staging process uses a smart “track changes”

algorithm, to enhance the update speed.

There are two staging processes, Real Time

Staging and Off Line Staging (that uses an

automated batch process). The characteristics of the

two staging “methods” are compared in the

following table.

Table 2: Staging Procedures comparison.

Real Time Staging Off Line Staging

Data

Update

(+) All data are

updated at all times

(-) All data are

updated at

specifically defined

time periods

Infra-

structure

(-) Reliable, high

speed, technical

infrastructure is

necessary, available

on a 24x7x365

basis

(+) Not so advanced

technical

infrastructure is

necessary

Security (-) The system can

be secure but

certain “protective”

actions must be

taken

(+) Security is

obvious

The previous table shows that a real time staging

procedure should be followed only if the nature of

the commodity traded imposes the constant database

update. In our case an every day off line procedure is

chosen for both security and convenience reasons.

Yet, if we try to deduct a general case example

we must notice that each company’s and product’s

needs, concerning the use of an e-market, are

different; therefore the connectivity solutions

(between an e-shop and an ERP) provided vary

depending on: (i) the ERP used (it can be a widely

used international ERP such as SAP, Oracle

Applications, etc. or it can be a custom made system

that fits to specific needs), (ii) the transaction

volume and the form of the data transferred, (iii) the

importance of the information transferred (regarding

time, safety etc. aspects), (iv) the use of unilateral or

bilateral communication and (v) whether it is an on-

line or a batch transfer of data.

E-commerce services offered through a B2C

(business to consumer) or B2B (business to

business) system, provide the necessary

infrastructure for real time e-business and an added

value package of services that guarantee faster and

more efficient buy and sell transactions, access to a

broadened database of buyers/suppliers and business

opportunities through the development of new

partnerships.

4 CONCLUSIONS

In conclusion, in this paper we presented an

interactive and user-friendly e commerce solution

for the vehicle sector, but appropriate for other

sectors as well. Volvo Technology Corporation

(VTEC) has been the end-user responsible for using

and testing the CATER platform, so a number of its

vehicles were integrated in the platform for

evaluation and testing purposes.

Finally, the main contribution is that our

approach adopts additional technologies such as a

configuration engine supported by ontologies,

advanced search mechanisms, and 3D visualisation

in a virtual reality environment aiming at enabling a

suitable representation of products in order to

achieve the most realistic possible visualization and

simulate an up to close shopping procedure.

ACKNOWLEDGEMENTS

We wish to acknowledge the CATER project

Consortium for their valuable contributions to this

work. The CATER project is partially funded by the

EC.

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