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The European Navigation Conference ENC 2020, November 22-25, 2020, Dresden, Germany
978-3-944976-28-0 ©2019 DGON
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BIM-based simulation of intelligent transportation systems
Kay Smarsly and Mahsa Mirboland
Computing in Civil Engineering, Bauhaus University Weimar,
Coudraystr. 13 b, 99423 Weimar, GERMANY
Email: kay.smarsly@uni-weimar.de
Abstract: Intelligent transportation systems, coupling information, communication and
sensor technologies, aim to improve traffic safety and energy efficiency, while reducing
traffic congestion and air pollution. To meet the challenges of the 21st century in the field
of road transport, simulation platforms are receiving increasing attention, in an attempt
to advance intelligent transportation system (ITS) optimization. Although a plethora of
simulation platforms for intelligent transportation systems exist, formalism have not yet
been reported that ensure reliable data exchange among different ITS simulation
platforms. This paper presents a conceptual model serving as a formal basis for
designing ITS simulation platforms for roads based on building information modeling
(BIM), which is a method mandated in many European countries when designing and
building public infrastructure. In this paper, an extension of the current BIM standard,
the Industry Foundation Classes (IFC) schema, is proposed, enabling standard-
compliant, BIM-based simulation of intelligent transportation systems for roads. First,
the conceptual model is presented, serving as a basis for the IFC schema extension. Then,
the IFC schema extension is described and verified with the test software of the official
IFC certification program. Next, an illustrative BIM-based simulation scenario is
presented for validating the IFC schema extension. The paper concludes with a summary
and an outlook on potential future research.
1. Introduction
Electric mobility, reducing greenhouse gas emissions and air pollution, builds upon intelligent
transportation systems [1]. An intelligent transportation system (ITS) comprises various
applications and data-sharing processes intermittently connected that result in a system of
critical heterogeneity and complexity [2]. Therefore, developing intelligent transportation
systems to advance electric mobility, it is vital to design ITS simulation platforms for
monitoring, evaluating, and optimizing ITS performance.
Besides monitoring, evaluating and optimizing ITS performance, ITS simulation platforms
are deployed to investigate ITS capabilities, design flaws, potential improvements, and future
mobility demands [3]. In recent years, research in ITS simulation platforms has matured into
an essential field. For example, Ghariani et al. have presented a comparative analysis
framework for performance assessment of simulation platforms used for public transport
control systems [4]. Boschian et al. have proposed a reference framework of intermodal
transportation systems with an information management layer between different modes of
transport. The reference framework integrates a simulation module and forms a platform for
operational processes [5]. A model-driven engineering framework to develop ITS simulations
has been proposed by Fernández-Isabel and Fuentes-Fernández [6]. The framework comprises
ITS data models for traffic simulations and sensor network components as well as guidelines
on how to use the data models for different simulations, such as traffic lights control. Datta et
al. have presented an ITS framework for road traffic containing building blocks and software
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elements that define operational phases of intelligent transportation systems [7], while
proposing technical solutions relevant to interconnected vehicles in the Internet of Things
ecosystem, referred to as “Internet of Vehicles”.
Although substantial advancements have been made in ITS simulation platform research,
most ITS simulation platforms focus on traffic-related applications or on improvements that
render simulation platforms more user-friendly [8]. However, optimizing ITS simulation
platforms on a sound mathematical basis requires a common formalism that provides
mathematical descriptions of intelligent transportation systems as well as reliable data
exchange among different simulation platforms. For data description and data exchange in
civil engineering, building information modeling (BIM) is a methodology that has become a
standard in planning and designing infrastructure projects in many European countries, such
as Denmark, Finland, United Kingdom, the Netherlands, and Norway. The Industry
Foundation Classes (IFC), standardized in ISO 16739, specify a neutral and open BIM data
format for vendor-independent description and exchange of building and infrastructure data
[9]. The IFC standard is maintained by the non-profit organization buildingSMART, and it is
described in the IFC schema. However, while civil infrastructure and “conventional”
transportation systems may be described in compliance with the IFC standard, the IFC
standard does not cover intelligent transportation systems.
This paper presents a proposal for extending the current IFC standard towards describing
intelligent transportation systems for roads. First, sources that provide knowledge relevant to
semantically describing intelligent transportation systems are analyzed and structured. Next, a
conceptual model for intelligent transportation systems is introduced that comprises all
elements as well as relationships between elements that constitute an ITS. Then, the proposed
conceptual model is mapped into the IFC schema, referred to as “IFC schema extension”,
enabling BIM-based description of intelligent transportation systems for roads in compliance
with the IFC standard. The IFC schema extension is verified with test software that is used in
the official IFC certification program. To illuminate details of the IFC schema extension, an
illustrative scenario demonstrating the BIM-based simulation of intelligent transportation
systems for roads is showcased. The simulation scenario also serves to validate the IFC
schema extension. The paper concludes with a summary and an outlook on potential future
research.
2. A conceptual model for describing intelligent transportation systems
To develop the conceptual model, sources that provide knowledge on physical, computing,
and networking subsystems of intelligent transportation systems for roads, hereinafter termed
“knowledge sources”, are analyzed and hierarchically structured. The knowledge sources
analyzed and structured in this study are divided into the following categories within the field
of intelligent transportation systems for roads,
• Architecture,
• Applications,
• Infrastructure, and
• Communication networks.
As an outcome of the analysis and structuring efforts, a hierarchy of terms is achieved that
forms the basis for developing the conceptual model. For details, the reader is advised to
consult [10]. The conceptual model, describing ITS elements and the relationships between
the ITS elements, provides a technology-independent, neutral formalism for intelligent
transportation systems for roads. From a computer science perspective, the conceptual model
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is designed as a “metamodel” to describe instances (“models”) of intelligent transportation
systems. The main elements and relationships included in the conceptual model are shown in
Figure 1 and are described in the following paragraphs. In the following paragraphs, the main
elements of the conceptual model are printed in italics and, for the sake of clarity, attributes
and methods of the elements are omitted.
Figure 1. Conceptual model for intelligent transportation systems for roads.
As depicted in Figure 1, the DigitalRoad class describes “non-conventional” roads, i.e. roads
furnished with ITS infrastructure, and it is composed of the conventional RoadStructure and
ITSStation classes. The class RoadStructure represents the underlying physical body of a
road, including spatial structural elements (e.g. bridges, tunnels, roads, ramps, and resting
areas). The abstract class ITSStation describes the core elements of intelligent transportation
systems that may be mobile (abstract class MobileITSStation) or fixed (abstract class
FixedITSStation). The MobileITSStation abstract subclass is further categorized into the
Vehicle and Personal subclasses, which represent vehicles of any type and personal smart
devices, respectively. The FixedITSStation abstract subclass is designed as a parent class to
the CentralUnit and RoadsideUnit subclasses to account for ITS control centers and roadside
intelligent infrastructure, respectively. Furthermore, as a specific type of network nodes
(Interface NetworkNode), ITS stations may perform a variety of operations, such as data
processing, signaling, recording, data packet routing, and resource renting. The SensingUnit,
ComputingUnit, PowerUnit, and CommunicationUnit classes, being integral parts of every
ITS station, represent the four main on-board units of all ITS stations. In addition, some ITS
stations may also have actuating capabilities, such as roadwork warning devices and traffic
signal controllers, reflected in the ActuatingUnit class.
Regarding the communication in intelligent transportation systems, the abstract class
ITSCommunication is devised, facilitating both internal and external communication, i.e.
communication within an ITS station (class InternalNetwork) and communication between
ITS station (class ExternalNetwork). On-board units as well as all equipment and assets
attached to each ITS station, whether wirelessly or cable-based connected, are denoted by the
ProprietaryNetwork class. Based on cooperative ITS communications in the vehicular
environment, the ExternalNetwork class is categorized into V2X (vehicle-to-anything) and I2I
(infrastructure-to-infrastructure) communications The Wireless abstract class describes
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wireless communication technologies and standards used in intelligent transportation systems.
The LongRange and ShortRange subclasses represent wireless communication standards and
protocols deployed for far-field and near-field wireless communications, respectively.
3. IFC schema extension
In this section, the IFC schema extension is presented. For technical details on extending the
IFC schema with specific semantic information, the interested reader is referred to [11-16].
The IFC schema, technically, is an entity-relationship model consisting of several hundred
entities, organized in an object-based inheritance hierarchy that is formally defined as an
EXPRESS data model. The EXPRESS data modeling language is standardized in ISO 10303-
11 [17]. Based on the conceptual model presented in the previous section, the IFC schema
extension is implemented by extending the corresponding EXPRESS data model of the IFC
schema. Precisely, two IFC entities,
• IfcITSStation and
• IfcRoadITS,
one enumeration,
• IfcITSStationTypeEnum,
and two IFC property sets,
• Pset_ITSResources and
• Pset_DistributionSystemTypeITSC,
introduced to describe intelligent transportation systems for roads, are added to the
EXPRESS-based IFC schema, as described in the following paragraphs. The IFC entities, the
enumeration, and the IFC property sets newly added to the IFC schema are shown in Figure 2
in gray color, while the existing elements, according to the most recent IFC release, are
displayed in white color.
Figure 2. Extract of the IFC schema extension with new IFC elements displayed in gray color.
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IfcITSStation. The IFC entity IfcITSStation, corresponding to the ITSStation class in the
conceptual model shown in Figure 1, provides a formal description of ITS stations. The
IfcITSStation entity is defined as a subtype of the entity IfcDistributionElement, which is a
generalization of all elements that participate in a distribution system.
IfcRoadITS. The IFC entity IfcRoadITS, introduced as a subtype of IfcDistributionSystem, is
devised to formally describe intelligent transportation systems, corresponding to the
DigitalRoad class in the conceptual model. The objectified assignment relationship
IfcRelAssignsToGroup connects the IfcITSStation entity to the IfcRoadITS entity, defining
instances of the IfcITSStation entity as distributed objects (RelatedObjects) of the global
system, i.e. instances of the IfcRoadITS entity (RelatingGroup). The connectivity relationship
IfcRelServicesBuildings links the IfcRoadITS entity to the IfcRoad entity, which is a built
facility representing spatial road structures. Instances of the IfcRoad entity (RelatedBuildings)
are connected to at least one instance of the IfcRoadITS entity (RelatingSystem).
IfcITSStationTypeEnum. The IFC enumeration data type represents different types of ITS
stations, listed as VEHICLEUNIT, PERSONALUNIT, CENTRALUNIT, and ROADSIDEUNIT
enumeration constants, representing vehicles of any type, personal smart devices, central
units, and roadside units of the conceptual model, which are complemented by
USERDEFINED and NOTDEFINED enumeration constants.
Pset_ITSResources. The IFC property set Pset_ITSResources describes the on-board units
being part of ITS stations, i.e. SensingUnit, ComputingUnit, PowerUnit, CommunicationUnit
and ActuatingUnit, according to the conceptual model. The properties defined in the IFC
property set, corresponding to the on-board units defined in the conceptual model, are referred
to as Sensors, ComputingResource, PowerResource, CommunicationResource, and Actuators.
Pset_DistributionSystemTypeITSC. For describing the communication between ITS
stations, the enumeration IfcDistributionSystemEnum, specified by the COMMUNICATION
constant is used. For characterizing the communication, the property set
Pset_DistributionSystemTypeITSC is introduced. The properties CommunicationType,
CommunicationChannel, and CommunicationDuration, representing values that specify the
communication in the ITS domain, are added to the Pset_DistributionSystemTypeITSC.
Illustrating the new IFC entities and the new enumeration relevant to intelligent transportation
systems for roads, an extract of the EXPRESS file of the IFC schema extension is shown in
Listing 1. For verifying the IFC schema extension, test software is used that builds upon the
software of the official IFC certification program [18, 19]. The test software, written in Java
language, supports a three-step verification procedure consisting of syntactic checks, semantic
checks, and unit testing. The verification procedure helps identify ambiguities, deficiencies,
and bugs in the IFC schema extension. As a result of the verification procedure, the
compliance of the IFC schema extension with the IFC standard has been confirmed.
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ENTITY IfcITSStation
SUBTYPE OF (IfcDistributionElement);
StationID : IfcInteger;
HasActuator : IfcBoolean;
StationType : IfcITSStationTypeEnum;
END_ENTITY;
ENTITY IfcRoadITS
SUBTYPE OF (IfcDistributionSystem);
END_ENTITY;
TYPE IfcITSStationTypeEnum = ENUMERATION OF
(VEHICLEUNIT
,PERSONALUNIT
,CENTRALUNIT
,ROADSIDEUNIT
,USERDEFINED
,NOTDEFINED);
END_TYPE;
Listing 1. Extract of the EXPRESS file of the IFC schema extension.
4. BIM-based simulation of intelligent transportation systems
Upon verifying the IFC schema extension, this section exemplarily showcases the BIM-based
simulation of intelligent transportation systems for roads, devised to validate the IFC schema
extension. For validation, a typical ITS scenario is defined, shown in Figure 3. In the ITS
scenario, it is assumed that an accident, precisely a rear-end collision, occurs in a section of a
highway, and external networks of ITS stations form a vehicular cloud to disseminate safety-
related messages. In Figure 3, a highway section of the German Autobahn A9 is shown,
where vehicle V1 broadcasts collision risk messages to ITS stations in the vicinity with
potential interest, e.g. vehicles approaching the accident. Specifically, vehicle V1 uses short-
range wireless communication to send a message (M1) to vehicle V2. Also, V1 sends a media
footage (message M2) it has recorded from the accident to the nearest infrastructure node with
Internet access, here roadside unit RSU1. In turn, vehicle V2 utilizes the point-to-multipoint
networking protocol to ask the nearest infrastructure node (roadside unit RSU2) for an
alternative route (message M3). Using long-range wireless communication, RSU1 requests
traffic-related data from the next fixed ITS station (roadside unit RSU2) and sends a detouring
alert as well as traffic signals to RSU2 (message M4).
Figure 3. ITS scenario simulated for validation purposes.
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Essentially, the conceptual model, thus the IFC schema extension, serves as a metamodel that
specifies the properties of models that are instantiated in compliance with the IFC schema
extension. The ITS simulation scenario is one specific instance, i.e. an IFC model, instantiated
in full compliance with the IFC schema extension. The IFC standard defines multiple file
formats that may be used for storing and exchanging IFC models, with the most widely used
file format being so called „STEP files” („Standard for the Exchange of Product model data”),
standardized in ISO 10303-21 [20].
Listing 2 shows an extract of the STEP-based description of the IFC model of the ITS
validation scenario shown in Figure 3. In the IFC model described in Listing 2, an intelligent
transportation system (#2) is evolved at a section of the German Autobahn A9 (#1). The ITS
is linked to the Autobahn A9 using the relationship entity IfcRelServicesBuildings (#11). Two
vehicle ITS stations (#3 , #4) and two roadside ITS stations (#5, #6) are core components of
the ITS (#2), linked to the ITS with the IFC entity IfcRelAssignsToGroup (#7, #8, #9, #10),
and characterizing the messages M1…M4 exchanged between the ITS stations.
...
#1= IFCROAD($,$,'A9_Section',$,$,$,$,$,$);
#2= IFCROADITS($,$,'A9_TestField',$,$,$,$);
#3= IFCITSSTATION($,$,'V1',$,$,$,$,$,935,.F.,.VEHICLEUNIT.);
#4= IFCITSSTATION($,$,'V2',$,$,$,$,$,913,.F.,.VEHICLEUNIT.);
#5= IFCITSSTATION($,$,'RSU1',$,$,$,$,$,42,.F.,.ROADSIDEUNIT.);
#6= IFCITSSTATION($,$,'RSU2',$,$,$,$,$,40,.T.,.ROADSIDEUNIT.);
#7= IFCRELASSIGNSTOGROUP($,$,'M1',$,(#3),.PRODUCT.,#2);
#8= IFCRELASSIGNSTOGROUP($,$,'M2',$,(#4),.PRODUCT.,#2);
#9= IFCRELASSIGNSTOGROUP($,$,'M3',$,(#5),.PRODUCT.,#2);
#10= IFCRELASSIGNSTOGROUP($,$,'M4',$,(#6),.PRODUCT.,#2);
#11= IFCRELSERVICESBUILDINGS($,$,'A9 ITS-enabled section',$,#2,(#1));
...
Listing 2. Extract of the STEP file of the IFC model representing the ITS simulation scenario.
The STEP file of the IFC model is verified using the test software previously introduced. The
test software checks for syntactic errors in the STEP file, and it also checks whether the
minimum semantic requirements of the IFC model are met. As a result, the IFC model of the
ITS simulation scenario shown in Figure 3 and in Listing 2, respectively, meets all
requirements. It can be concluded that the IFC schema extension proposed in this paper offers
well-structured, IFC-compliant descriptions of intelligent transportation systems. A visual
representation of the ITS scenario, exemplarily illustrating the BIM-based simulation of
intelligent transportation systems for roads, is shown in Figure 4.
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Figure 4. BIM-based simulation of intelligent transportation systems.
5. Summary and conclusions
To meet the challenges of the 21st century in the field of road transport, simulation platforms
that advance intelligent transportation systems are receiving increasing attention. However,
common formalisms to semantically describe intelligent transportation systems, while
ensuring reliable data exchange among different simulation platforms, have not yet been
reported. Serving as a foundation to implement simulation platforms, this paper has proposed
a formalism to describe intelligent transportation systems for roads, based on building
information modeling. Building information modeling has matured into a methodology that
many European countries mandate when designing and planning publicly funded
infrastructure projects, but intelligent transportation system cannot be formally described with
the current BIM standard, the Industry Foundation Classes.
As has been shown in this paper, sources that provide knowledge relevant to semantically
describing intelligent transportation systems have been analyzed and structured. Building
upon the knowledge gained from the sources being analyzed and structured, a conceptual
model for intelligent transportation systems has been designed that comprises all elements as
well as relationships between elements that constitute an ITS for roads. The conceptual model
has been mapped into the IFC schema, referred to as “IFC schema extension”. A verification
procedure has confirmed the compliance of the IFC schema extension with the IFC standard.
An illustrative simulation scenario has been defined to validate the IFC schema extension and
to exemplarily demonstrate the BIM-based simulation of intelligent transportation systems for
roads. The IFC schema extension, formally describing ITS for roads, may serve as a catalyst
to advance mathematical descriptions of intelligent transportation systems. Although the
results achieved in this study are promising, room for improvements and for potential future
work has been identified. For example, the conceptual model, thus the IFC schema extension,
may be further elaborated in more details. In addition, coupling the BIM-based simulation
approach proposed in this study with current state-of-the-art ITS simulation platforms is a
promising idea that helps link building information modeling and technologies currently
implemented in ITS simulations.
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Acknowledgments
This research is partially supported by the European Union through the European Social
Funds (ESF) and by the Thuringian Ministry for Economic Affairs, Science and Digital
Society (TMWWDG) under grant 2017FGR0068. The authors gratefully acknowledge the
generous support provided by Mr. Theiler and Dr. Tauscher of Apstex GbR in verifying the
IFC schema extension. Any opinions, findings, and conclusions or recommendations
expressed in this publication belong to those authors and do not necessarily reflect the view of
the sponsors.
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