ISO 6029-2:2026

International
Standard
ISO 6029-2
First edition
Intelligent transport systems —
2026-01
Seamless positioning for
multimodal transportation in ITS
stations —
Part 2:
Nomadic and mobile device dataset
for positioning data fusion
Systèmes de transport intelligents — Positionnement homogène
pour le transport multimodal dans les stations ITS —
Partie 2: Ensemble de données d'appareils nomades et mobiles
pour la fusion de données de positionnement
Reference number
© ISO 2026
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Published in Switzerland
ii
Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms. 4
4.1 Abbreviated terms .4
5 Seamless positioning system overview . 6
5.1 General .6
5.1.1 Objective .6
5.1.2 Standard references and scope of application .6
5.1.3 Compliance requirements .6
5.1.4 Positioning scenario .6
5.2 Positioning system components .9
5.2.1 Global navigation satellite systems (GNSS) .9
5.2.2 Inertial measurement units (IMU) .9
5.2.3 Short-range sensor (SRS) .9
5.2.4 Long-range sensor (LRS) .9
5.2.5 Infrastructure components .10
5.2.6 Nomadic devices .10
5.2.7 Integration and fusion units .10
5.2.8 Data transmission and networking .10
5.2.9 User interfaces and applications .10
5.3 Multimodal transportation concepts .11
5.4 Seamless positioning system architecture .11
5.5 System reliability and security .14
5.5.1 Data exchange protocols .14
5.5.2 Communication infrastructure configuration .14
5.5.3 Rational error handing and security measures . 15
5.5.4 Robust error handling and security measures .16
6 Data fusion for seamless positioning .16
6.1 Sensor data specification .16
6.1.1 Data specification by sensor type .16
6.1.2 Sensor data types and characteristics .17
6.1.3 Data format and structure . .18
6.1.4 Data size and length . 20
6.2 Sensor data fusion process . 20
6.3 Positioning output process .21
6.3.1 Positioning output calculation .21
6.3.2 Additional considerations for confidence estimation . 22
7 Requirements and guidelines .23
7.1 Domain requirement level (DRL) . 23
7.1.1 General . 23
7.1.2 Actor requirements . 23
7.1.3 Functional requirements . 23
7.1.4 Performance requirements .24
7.2 Sensor requirement level (SRL) .24
7.3 Required and recommended data . 25
7.4 Quality of service (QoS) requirements .27
7.4.1 QoS of seamless positioning system .27
7.4.2 System performance metrics . 28
7.4.3 Data processing efficiency . 28

iii
8 Implementation considerations .29
8.1 Sensor integration strategies and implementation . 29
8.1.1 Sensor integration strategies . 29
8.1.2 Sensor selection criteria . 29
8.1.3 Sensor calibration and synchronization . 30
8.1.4 Sensor fusion techniques . 30
8.1.5 Sensor placement and configuration . 30
8.2 Sensor integration testing . 30
8.2.1 General . 30
8.2.2 Documentation and maintenance . 30
8.2.3 Data transmission protocols and optimization .31
8.3 Error handling, fault tolerance and recovery mechanisms .31
8.4 Security and privacy measures in sensor deployment .32
8.5 Signal strength and sensor integration .32
8.5.1 General .32
8.5.2 Signal strength assessment for nomadic devices .32
8.5.3 Signal strength-based sensor selection . 33
8.5.4 Signal strength optimization techniques . 34
8.5.5 Dynamic signal strength adaptation for nomadic devices . 34
8.5.6 Signal strength monitoring and maintenance for nomadic devices . 34
8.5.7 Case studies and best practices . 35
Annex A (informative) Sensor fusion dataset code examples .37
Bibliography .79

iv
Foreword
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This document was prepared by Technical Committee ISO/TC 204, Intelligent transport systems.
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Any feedback or questions on this document should be directed to the user’s national standards body. A
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v
Introduction
As new forms of mobility services (e.g. e-mobility, delivery robot, autonomous driving) are emerging in
the intelligent transport systems (ITS) industry, the role of the nomadic device is becoming indispensable.
Currently, mobility service platforms use position data gathered via the nomadic devices of the passengers,
and positioning systems rely on global navigation satellite system (GNSS) technology. The functionality of
the system is occasionally constrained by network interference, GNSS-denied environments and data loss.
A seamless positioning system would enable interoperability between ITS domains to provide a seamless
location-based service.
The main objective of a seamless positioning system is to support the development of a robust and ubiquitous
indoor and outdoor seamless positioning solution for a mobile user (e.g. multimodal transportation) so that
anyone can experience mobility services regardless of location, environment and disabilities.
The seamless positioning system consists of three domains:
— nomadic device [e.g. personal intelligent transport system station (P-ITS-S)],
— mobility [e.g. vehicle intelligent transport system station (V-ITS-S)], and
— infrastructure [e.g. roadside intelligent transport system station (R-ITS-S)].
The system integrates multiple data from different domains and provides positioning data (e.g. position,
velocity, time service implemented in the ITS-S) in a seamless manner.
Figure 1 shows the seamless positioning system.

vi
Key
1 exchange of data between P-ITS-S and mobility containing mobility/personal data and network environment
2 exchange of data between P-ITS-S and infrastructure containing personal data and infrastructure information
3 exchange of data between mobility end and sensor-fusion positioning application
4 exchange of data between infrastructure end and sensor-fusion positioning application
5 exchange of data between P-ITS-S and sensor-fusion positioning application
6 seamless positioning calculation
7 positioning exchange use cases
a
The P-ITS domain is represented by ITS-compliant nomadic devices carried by human beings.
b
The V-ITS domain is represented by ITS-compliant vehicles.
c
The R-ITS domain is represented by ITS-compliant roadside infrastructure devices.
d
Positioning domain of all devices in P-ITS, V-ITS and R-ITS domain.
e
Outcome is the integrated position, velocity and time service provision.
Figure 1 — Seamless positioning system

vii
International Standard ISO 6029-2:2026(en)
Intelligent transport systems — Seamless positioning for
multimodal transportation in ITS stations —
Part 2:
Nomadic and mobile device dataset for positioning data
fusion
1 Scope
This document specifies the sensor data fusion applicable to the use cases of indoor and outdoor seamless
positioning solutions for a mobile user (multimodal transportation) in intelligent transport system (ITS)
stations.
This document provides technical requirements for data fusion between three domains:
1) nomadic device [e.g. personal intelligent transport system station (P-ITS-S)],
2) mobility [e.g. vehicle intelligent transport system station (V-ITS-S)], and
3) infrastructure [e.g. roadside intelligent transport system station (R-ITS-S)].
The data exchange between these domains is based on a standardized message and data format and this
document identifies use cases for each different case of communication between domains.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO 17438-4, Intelligent transport systems — Indoor navigation for personal and vehicle ITS station — Part 4:
Requirements and specifications for interface between personal/vehicle and central ITS stations
ISO/TS 21176, Cooperative intelligent transport systems (C-ITS) — Position, velocity and time functionality in
the ITS station
ISO/TS 21184, Cooperative intelligent transport systems (C-ITS) — Global transport data management (GTDM)
framework
ISO 23150, Road vehicles — Data communication between sensors and data fusion unit for automated driving
functions — Logical interface
IEC 61162 (all parts), Maritime navigation and radiocommunication equipment and systems — Digital
interfaces
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 17438-4, ISO/TS 21176,
ISO/TS 21184, ISO 23150, the IEC 61162 series and the following apply.

ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1
positioning system
system of instrumental and computational components for determining position
EXAMPLE Inertial, integrated, linear, optical and satellite are examples of positioning systems.
[SOURCE: ISO 19116:2025, 3.24]
3.2
seamless positioning system
system that supports the continuity of positioning data (3.7) for nomadic device [personal intelligent
transport system station (P-ITS-S)] (3.6) location-based services using multiple positioning technologies
3.3
multimodal transportation
multiple different modes of transport
3.4
handler
routine or function
3.5
motion
change in the position of an object over time, represented by change of coordinate values with respect to a
particular reference frame
[SOURCE: ISO 19116:2025, 3.18, modified — the Example has been removed.]
3.6
personal intelligent transport system station
P-ITS-S
intelligent transport system (ITS) station implemented on a personal device
3.7
positioning data
POS
moving object position data
3.8
requirement level
required or recommended status of domain data and sensor data based on the availability of sensor data
3.9
required
status of data whereby data are always required for the system operation
3.10
recommended
status of data whereby data are permitted but not required for system operation
3.11
domain requirement level
DRL
specification of the priority and criticality of a requirement for seamless positioning, indicating the extent
to which the requirement needs to be satisfied to ensure accurate, reliable and uninterrupted positioning
performance
3.12
sensor requirement level
requirement level (3.8) specified at the sensor level
3.13
common dataset
dataset for sensor data fusion (3.14) within the positioning domain
3.14
sensor data fusion
process of computing positioning output by integrating sensor data, either from the same domain or different
domains, after converting the sensor data to a common message format
Note 1 to entry: This integration process involves combining data from various sensors to enhance the accuracy and
reliability of positioning information. The common message format facilitates seamless integration by providing a
standardized format for representing sensor data, allowing for efficient processing and analysis.
3.15
vehicle-mounted device
device physically attached to or installed on a vehicle, designed primarily to enhance or assist the vehicle's
internal operations, without necessarily being integrated into an intelligent transport system (ITS)
3.16
fusion algorithm
method for integrating data from multiple sensors to generate a positioning output, selected according to
sensor type, required accuracy, environmental conditions and computational resources
3.17
sensor data integration
process of combining information from multiple sensors using a selected algorithm to generate a unified
representation of the vehicle's position
3.18
error modelling and correction
techniques applied to account for inaccuracies and uncertainties in sensor data, using methods such as
Kalman filtering, particle filtering, or Bayesian inference to reduce errors and improve position estimation
accuracy
3.19
dead reckoning
navigation technique that estimates position based on a previously known location and measured changes
in velocity and orientation, often used in conjunction with sensor fusion to maintain continuous positioning
when satellite signals are unavailable or obstructed
3.20
map matching
process that refines position estimates by comparing sensor-derived positions with digital map features,
such as road networks, landmarks, and geographical constraints, to improve accuracy and provide additional
contextual information
3.21
confidence estimation
confidence level or uncertainty measure assigned to the calculated position to indicate the reliability of the
estimation
Note 1 to entry: The confidence estimation is crucial for decision-making processes, as it helps users understand the
level of trust they can place in the calculated position.

4 Symbols and abbreviated terms
4.1 Abbreviated terms
AES advanced encryption standard
ASCII American standard code for information interchange
ASN.1 abstract syntax notation one
AT autonomous tech
BT Bluetooth
CAN controller area network
CRC cyclic redundancy check
DRL domain requirement level
EKF Extended Kalman filtering
GDPR General Data Protection Regulation
GLONASS global navigation satellite system (Russian Federation)
GNSS global navigation satellite system
GPS global positioning system (US)
GSM global system for mobile communications
GTDM global transport data management
GW gateway
HIPAA Health Insurance Portability and Accountability Act
HMAC hash-based message authentication code
HTTP hypertext transfer protocol
I-COMM infrastructure communication
I-FPH infrastructure floor profile handler
I-LPH infrastructure location profile handler
IMU inertial measurement unit
IP internet protocol
IRNSS Indian regional navigation satellite system
ITS intelligent transport system
JSON JavaScript object notation
KPI key performance indicator
KPS Korean positioning system
LaaS logistics as a service
LiDAR light detection and ranging
LRS long-range sensor
LTE long-term evolution
MaaS mobility as a service
M-PSG motion positioning station gateway
MQTT message queuing telemetry transport
M-SPH motion status profile handler
ND nomadic device
NFC near-field communication
NMEA national marine electronics association
OAuth open authorization
PF particle filtering
P-FPH personal floor profile handler
PII personally identifiable information
P-ITS-S personal intelligent transport system station
P-LPH personal location profile handler
P-RI personal registration information
P-SPH personal status profile handler
POS positioning data
PVT position, velocity, time
QZSS quasi-zenith satellite system (Japan)
RF radio-frequency
RFID radio-frequency identification
R-ITS-S roadside intelligent transport system station
RL requirement level
RSA Rivest–Shamir–Adleman asymmetric cryptography
RSSI received signal strength indicator
SRL sensor requirement level
SRS short-range sensor
SSL secure sockets layer
TCP transport control protocol
TLS transport layer security
UC use case
UDP user datagram protocol
UMTS universal mobile telecommunications system
V-ITS-S vehicle intelligent transport system station
WGS world geodetic system
Wi-Fi wireless fidelity
XML extensible markup language
5 Seamless positioning system overview
5.1 General
5.1.1 Objective
The objective of the seamless positioning system is based on:
— extensibility, e.g. artificial intelligence, block-chain and sensor fusion technology;
— simplification, e.g. standardized message format based on ISO/TS 21184 (GTDM) and the IEC 61162 series
(NMEA);
— reliability, e.g. system reliability, data precision, fast first to fix, dilution correction factors;
— application, e.g. the ISO 17438-4, autonomous driving features, location-based service, safety-related
industry.
5.1.2 Standard references and scope of application
This document provides comprehensive guidelines and requirements for continuous positioning systems
between indoor and outdoor environments, defining datasets by sensor type and data exchange sequences
by sensor fusion type. Sensor modules are categorized by data type, with corresponding data exchange
processes defined by use cases.
This document particularly focuses on the moment at which a nomadic device moves between areas with
and without satellite signals, with all processes initiated based on GNSS availability information.
5.1.3 Compliance requirements
This document encompasses most technical requirements for sensor fusion among nomadic devices,
mobility-related data, and infrastructure-related data. It is developed to optimize continuous positioning
systems between indoor and outdoor environments while minimizing additional processing.
This document provides guidelines and requirements for seamless integration of sensor data from various
domains, ensuring precise and reliable positioning under diverse environmental conditions.
5.1.4 Positioning scenario
Figure 2 illustrates a positioning scenario in an open space with GNSS satellite signals. It shows the data
fusion of satellite data as the primary source for positioning, with other sensor data utilized for sensor

fusion to enhance the accuracy and reliability of location data. The determination of positioning reference
points for sensor data fusion is based on attenuation information of sensor signals (e.g. PVT) as specified in
ISO/TS 21176 .
V-ITS-S
(In-vehicle)
UVIP UVIP
msg (odometer, speed, etc)
Reference signal strong area
: open sky
Autonomous tech based
AT
(LiDAR, radar, ultrasonic,
msg
camera, etc)
P-ITS-S
(Nomadic device)
LRS Long-range sensor
(LTE, 5G, etc)
msg
Satellite GNSS
(GPS, GLONASS, KPS, QZSS, etc) msg
Required
SRS Short-range sensor
Positioning
msg (BT, NFC, Wi-ˆi, etc)
IMU IMU
(6-axis, 9-axis, etc) msg Recommended (If available)
PVT based on
data fusion
R-ITS-S
(infrastructure)
Long-range sensor LRS
(LTE, 5G, etc) msg
Common
RSU RSU
dataset
msg
(roadside unit)
Short-range sensor SRS
(BT, NFC, Wi-ˆi, etc) msg
LRS
Long-range sensor
msg (LTE, 5G, etc)
Required
Integrated PVT service
SRS Short-range sensor
msg (BT, NFC, Wi-ˆi, etc)
Recommended (If available)
Key
1 satellite sensor data flows from P-ITS-S to support positioning through data fusion
2 IMU sensor data flows from P-ITS-S to support positioning through data fusion
3 long-range sensor data flows from P-ITS-S to support positioning through data fusion
4 short-range sensor data flows from P-ITS-S to support positioning through data fusion
5 unified vehicle interface protocol-based data flows from V-ITS-S to support positioning through data fusion
6 autonomous technology-enabled sensor data flows from V-ITS-S to support positioning through data fusion
7 long-range sensor data flows from V-ITS-S to support positioning through data fusion
8 short-range sensor data flows from V-ITS-S to support positioning through data fusion
9 roadside unit data flows from R-ITS-S to support positioning through data fusion
10 long-range sensor data flows from R-ITS-S to support positioning through data fusion
11 short-range sensor data flows from R-ITS-S to support positioning through data fusion
12 P-ITS-S domain
13 satellite-based sensor components
14 IMU sensor components
15 long-range sensor components
16 short-range sensor components
17 positioning through data fusion
18 data fusion common dataset
19 integrated PVT output for the service
20 V-ITS-S domain
21 unified vehicle interfaces protocol related components
22 autonomous technology-enabled sensor related components
23 long-range sensor components
24 short-range sensor components

25 R-ITS-S domain
26 roadside unit components
27 long-range sensor components
28 short-range sensor components
Figure 2 — Positioning scenario common dataset conversion and PVT output based on sensor data
fusion
5.2 Positioning system components
5.2.1 Global navigation satellite systems (GNSS)
Global navigation satellite systems support:
— GPS (US);
— GLONASS (Russian Federation);
— Galileo GNSS (Europe);
— BeiDou GNSS (China);
— other regional navigation systems [(i.e. KPS (Republic of Korea), QZSS (Japan), IRNSS (India)]
NOTE See ITU-R M.1787-4 for further information.
5.2.2 Inertial measurement units (IMU)
Inertial measurement units contain:
— gyroscopes;
— accelerometers;
— magnetometers;
— wireless communication technologies.
5.2.3 Short-range sensor (SRS)
Short-range sensors include:
— radio frequency identification (RFID);
1)
— Bluetooth® (BT) technology wireless communication;
— ultrasonic; and
— infrared radar.
5.2.4 Long-range sensor (LRS)
Long-range sensors include those based on mobile cellular systems [e.g. the Global System for Mobile
Communications (GSM ETSI TS 144 000 series)], as well as sensors utilizing radar and LiDAR technologies:
— 3G: third generation mobile network: Universal Mobile Telecommunications System (UMTS);
1) Bluetooth is the trade name of a product supplied by the Bluetooth Special Interest Group (SIG). This information is
given for the convenience of users of this document and does not constitute an endorsement by ISO of the product named.
Equivalent products may be used if they can be shown to lead to the same results.

— 4G: fourth generation mobile network: Long-Term Evolution (LTE);
— 5G: fifth generation mobile network: New Radio (NR);
— radar;
— long-range LiDAR.
5.2.5 Infrastructure components
Infrastructure components include:
— roadside units (RSUs);
— base stations;
— data centres.
5.2.6 Nomadic devices
Nomadic devices are portable or mobile equipment used for positioning, communication and data collection
in indoor and outdoor environments. Examples include:
— smartphones;
— wearable devices;
— vehicle-mounted devices.
5.2.7 Integration and fusion units
Integration and fusion units are responsible for combining and processing heterogeneous sensor data to
improve positioning performance. These include:
— sensor fusion algorithms;
— data processing units;
— positioning calculation engines.
5.2.8 Data transmission and networking
Data transmission and networking components enable communication, connectivity, and interoperability
among devices and systems. Examples are:
— communication protocols (CAN, ethernet, UDP);
— network architectures (client-server, peer-to-peer);
— cloud computing platforms.
5.2.9 User interfaces and applications
User interfaces and applications provide end users with access to positioning, navigation and management
functionalities. Examples include:
— mapping and navigation apps;
— location-based services;
— fleet management systems;
NOTE 1 Fleet management systems are comprehensive software and hardware systems primarily designed
to manage and monitor extensive vehicle fleets. These systems offer functionalities such as vehicle location
tracking, driver behaviour analysis, maintenance scheduling, and trip logging to enhance the efficiency of vehicle
operation and management. Fleet management systems are generally designed to optimize vehicle efficiency and
reduce operational costs.
— nomadic device.
NOTE 2 In this context, a nomadic device can be a portable location-tracking and communication device that
can enhance interaction with fleet management systems. By receiving real-time vehicle location and driving
data through nomadic devices and transmitting this information to fleet management systems, better insights
into vehicle operation and management can be obtained. This can lead to benefits such as improved efficiency in
vehicle operations and optimization of maintenance schedules.
5.3 Multimodal transportation concepts
Multimodal transportation is a multifaceted realm, which encompasses the integration of various modes of
transportation for efficient and sustainable mobility. The key aspects, as covered in this document, are as
follows.
— Concept and benefits: seamlessly combining multiple modes of transportation to achieve efficient
mobility, alleviate traffic congestion, and reduce environmental impact.
— Key characteristics: the distinctive features of multimodal transportation, including multimodal routes
and connectivity, compatibility of infrastructure and facilities, and integration of payment and fare
systems.
— Implementation examples: real-world cases of multimodal transportation systems, showcasing how
diverse modes of transportation are integrated to facilitate efficient mobility. Examples include public
transit, bike-sharing systems and ride-sharing services.
— Technological aspects: this can encompass location tracking technologies, big data analytics, and IoT
technologies.
— Policies and regulations: government policies and regulations aimed at supporting and advancing
multimodal transportation, which can include transportation policies, traffic regulations, and support
policies.
By encompassing these aspects, this document provides a comprehensive overview of multimodal
transportation systems and their role in facilitating efficient and sustainable mobility.
5.4 Seamless positioning system architecture
The seamless positioning system architecture describes the structure and interaction of navigation and
positioning systems. This architecture is composed of the following key components.
— Nomadic device (P-ITS-S): P-ITS-S is a portable intelligent transportation system device used by human
beings or inside vehicles. This device collects location and motion data through various sensors, along
with GNSS and other positioning technologies. It tracks the human being's (user's) location in real-time
and communicates with other domains to acquire and process location data.
— Mobility (V-ITS-S): V-ITS-S is an intelligent transportation system device installed within vehicles.
It primarily collects location data of the vehicle and tracks the vehicle's motion and driving status.
Additionally, this device communicates with other vehicles and infrastructure to acquire different
location data, which is then shared with P-ITS-S.
— Infrastructure (R-ITS-S): R-ITS-S is an intelligent transportation system device installed in road
infrastructure. It mainly collects location data in the road environment and monitors the conditions
of the road and its surroundings. This device communicates with P-ITS-S and V-ITS-S to share road
conditions and location data, managing traffic flow.

— Seamless positioning data fusion: seamless positioning data fusion is the process of integrating location
and motion data collected from each domain. This process combines various positioning technologies
and sensor data to continuously track the user's location and provide accurate positioning information
in real-time.
— Communication infrastructure: the communication infrastructure is a vital element that supports
data exchange between P-ITS-S, V-ITS-S and R-ITS-S. This infrastructure securely transmits data using
various communication protocols and efficiently exchanges location and motion data. These components
interact with each other to continuously track the user's location indoors and outdoors, forming a flexible
and efficient system that provides positioning information. Figure 2 and Figure 3 visually illustrate the
interaction of these components.
Figure 3 illustrates the movement of P-ITS-S from an outdoor environment, where GNSS data is available
to an indoor facility and underground area in which GNSS signal is weak or unavailable. In the outdoor
environment, satellite data such as GNSS, gathered through P-ITS-S, becomes mandatory for positioning.
Key
1 outdoor
2 indoor
3 underground
Figure 3 — Transition of P-ITS-S from outdoor to underground through indoor environment
In the indoor and underground environments, in which GNSS data is not accessible, short-range sensor
(SRS) and long-range sensor (LRS) from the R-ITS-S domain are utilized for sensor data fusion to determine
positioning. In this scenario, any available data from R-ITS-S is considered mandatory as P-ITS-S moves
into indoor and underground environments. Communication between the SRS of P-ITS-S and R-ITS-S
facilitates the exchange of sensor data, while LRS (in this case, a cellular network) serves as a means of data
transmission between domains.
Figure 4 demonstrates the Position, Velocity, Time (PVT) output, as specified in ISO/TS 21176, while in the
underground environment by converting sensor data into a common dataset and computing PVT through
sensor data fusion.
V-ITS-S
Underground / indoor
(In-vehicle)
(weak/loss signal)
UVIP UVIP
msg (odometer, speed, etc)
Autonomous Tech based
AT
(LiDAR, radar, ultrasonic,
msg
12 camera, etc)
P-ITS-S
(Nomadic device)
LRS Long-range sensor
msg (LTE, 5G, etc)
Satellite GNSS
(GPS, GLONASS, KPS, QZSS, etc) msg
Required 8
SRS Short-range sensor
Positioning
msg (BT, NFC, Wi-‚i, etc)
IMU IMU
(6-axis, 9-axis, etc) msg Recommended (if available)
PVT based on
data fusion
R-ITS-S
18 (Infrastructure)
Long-range sensor LRS
msg
(LTE, 5G, etc)
Common
RSU RSU
Required
16 dataset
msg (roadside unit)
Short-range sensor SRS
(BT, NFC, Wi-‚i, etc) msg
LRS Long-range sensor
Required
msg (LTE, 5G, etc)
Required Integrated PVT service
11 28
SRS Short-range sensor
msg (BT, NFC, Wi-‚i, etc)
Required
Required
Key
1 satellite sensor data flows from P-ITS-S to support positioning through data fusion
2 IMU s
...