ISO/TR 24856:2025
(Main)Intelligent transport systems — Mobility integration — Role model of the human-centric predictive risk information provisioning service
Intelligent transport systems — Mobility integration — Role model of the human-centric predictive risk information provisioning service
This document describes a role model for predictive safety risk information provisioning primarily applicable for non-enforcement applications, and potentially applicable for enforcement application services are out of scope of this document. This role model is dedicated to human centric road transport safety management purposes considering all road users on the roads. It can be applicable to enforcement application services.
Systèmes de transport intelligents — Intégration de la mobilité — Schéma d'application des services de fourniture d'informations prédictives relatives aux risques centrés sur l'homme
General Information
Standards Content (Sample)
Technical
Report
ISO/TR 24856
First edition
Intelligent transport systems —
2025-03
Mobility integration — Role model
of the human-centric predictive risk
information provisioning service
Systèmes de transport intelligents — Intégration de la mobilité —
Schéma d'application des services de fourniture d'informations
prédictives relatives aux risques centrés sur l'homme
Reference number
© ISO 2025
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ii
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Symbols and abbreviated terms. 1
5 Human centric safety information provisioning . 2
6 Gap and overlap analysis . 2
6.1 General .2
6.2 Analysis results.3
7 Basic framework . 5
7.1 Basics and objective .5
7.2 National variations .6
7.3 Basic role model architecture .6
7.3.1 Baseline .6
7.3.2 Smart city sensor data . . .7
7.3.3 3D HD point cloud map .7
7.3.4 Digital infrastructure .7
7.3.5 Mobility supporting facilities . .7
7.3.6 Physical infrastructure .8
7.3.7 Mobility service provider .8
7.3.8 Communications .8
7.3.9 Mobility users .8
7.4 Application layer role and functional model for mobility system .8
7.4.1 General .8
7.4.2 Role and functional model options .10
7.4.3 Certification of service providers .10
8 Use case examples .11
Annex A (informative) Use cases .12
Bibliography . 19
iii
Foreword
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iv
Introduction
Mobile entities require sufficient safety distance allowing them to efficiently reduce speed and improve
manoeuvring distance in a timely manner to avoid traffic incidents. To achieve safer road transportation
with mobile entities, an information provisioning service is indispensable which provides information
on traffic status and incident situation, i.e. predictive risk information, from locations well ahead of the
mobility’s position.
This document describes a conceptual operational framework of predictive risk safety information provision
[2]
provided by service providers. This description is based on ISO 4445 , which describes a basic role model
of smart city intelligent transport systems (ITS) service applications. There are two types of services,
enforcement (for regulated purpose) and non-enforcement (for non-regulated purpose). This document
[44]
describes non-enforcement services. For the enforcement services, see the ISO/DTS 24315 series.
For information provisioning, the technology of clouds is relevant. The cloud acts as a digital platform where
aggregated traffic data are available.
This document focuses on service provider transactions between the roles via ITS-stations and road users.
Using this system architecture, additional safety information provision services to road users can be
realized. Where authority requires such regulated monitoring (for enforcement purpose), new means of safe
road transport management and enforcement can be enabled by using this document.
Whilst currently available safety standards deal with time critical information provisioning, i.e. means
applicable close to an imminent risk, this document aims to describe means to increase safe road
transportation based on predictive risk information; see Figure 1. Providing predictive risk information has
the capability to reduce traffic incidents because road users are better prepared for incidents that could
happen later in the trip on the oncoming roads. This is also potentially applicable for automated driving
vehicles considering technologies for fast processing of a huge amount of data, referred to as "Artificial
Intelligence" (AI) technologies. Examples of potential accident events and locations are work zones, merging
traffic, tail end crushing, crossing from behind parked vehicles, blind intersection, etc.
Figure 1 — Predictive risk
v
Technical Report ISO/TR 24856:2025(en)
Intelligent transport systems — Mobility integration — Role
model of the human-centric predictive risk information
provisioning service
1 Scope
This document describes a role model for predictive safety risk information provisioning primarily applicable
for non-enforcement applications, and potentially applicable for enforcement application services are out of
scope of this document. This role model is dedicated to human centric road transport safety management
purposes considering all road users on the roads. It can be applicable to enforcement application services.
2 Normative references
There are no normative references in this document.
3 Terms and definitions
No terms and definitions are listed in this document.
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/
4 Symbols and abbreviated terms
AI artificial intelligence
AV automated vehicle
AD automated driving
API application programming interface
ATC advanced transportation controller
ATCC advanced transportation controller cabinet
C2C-CC car-to-car communications consortium
CMC connected motorcycle consortium
ConOPs concept of operations
DMS dynamic message signs
INFLO intelligent network flow optimization
ITS intelligent transport systems
SWIW-RS spot weather information warning – reduced speed
VRU vulnerable road user
WAVE wireless access in vehicular environments
3D HD three-dimensional high definition
5 Human centric safety information provisioning
The goal to achieve a society in which all mobile entities, i.e. road users, are free from traffic accidents, and
considering that most traffic accident fatalities involve vulnerable road users (VRU), requires consideration
of a human-centric approach. Thus, it is important not only to improve the safety technology of vehicles, but
also to provide support to encourage safe behaviour among all road users. This requires that the cooperative
safety system understands the traffic environment and human conditions and traits to predict risks and
provide appropriate information in due time.
Mobil
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