ISO/TR 22087:2025

Technical
Report
ISO/TR 22087
First edition
Intelligent transport systems —
2025-05
Collection of agent behaviour
information and sharing between
ITS stations
Systèmes de transport intelligents — Collecte d'informations sur
le comportement des agents et partage entre les stations ITS
Reference number
© ISO 2025
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ii
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms, definitions and abbreviated terms . 1
3.1 Terms and definitions .1
3.2 Abbreviated terms .2
4 Introduction of DBIS . 2
4.1 Ego-vehicle’s DBIS .2
4.2 Driver's intention .4
4.2.1 General .4
4.2.2 Intention of longitudinal control .4
4.2.3 Intention of lateral control .4
4.2.4 State of driver .4
4.3 Status of vehicle .4
4.3.1 Speed of vehicle .4
4.3.2 Distance of vehicles .4
4.3.3 Vehicle type .4
4.3.4 Vehicle location .4
4.4 Road-environment information .5
4.4.1 Traffic property of road .5
4.4.2 Additional property of road .5
4.5 Egocentric surrounding object’s information .5
4.6 Related messages .5
4.6.1 Collection of DBIS.5
4.6.2 Sharing DBIS.5
4.7 Functional components .6
5 Use case overview and principles . 7
5.1 Basic principles for use case definition .7
5.2 Overview of collective perception .7
5.3 Overview of learning to predict and assess collision risk .8
5.4 Use case clusters .9
6 Use case definition .10
6.1 Overview .10
6.2 UC cluster 1 - Collective perception .10
6.2.1 UC 1.1 - Sharing the intention of an ego vehicle to make lane change .10
6.2.2 UC 1.2 - Situation perception of cut-in/cut-out of adjacent vehicles .11
6.3 UC cluster 2 - Learning to predict and assess collision risk . 12
6.3.1 UC 2.1 - Collision prediction if vehicle suddenly attempts to enter left/right lane . 12
6.3.2 UC 2.2 – Situation awareness of the collision with speed-up straight-ahead
vehicle when vehicle attempts to change lane . 13
6.3.3 UC 2.3 – Assessment of driving method when all vehicles ahead suddenly slow
down .14
Bibliography .16

iii
Foreword
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This document was prepared by Technical Committee ISO/TC 204, Intelligent transport systems.
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iv
Introduction
Autonomous driving technology using artificial intelligence is becoming increasingly important for the safe
operation of vehicles on the road. To be effective, artificial intelligence needs to gather a lot of information
about a vehicle's behaviour and use it to learn. In order to drive safely on the road, self-driving vehicles
need to be aware of the status of other vehicles, road conditions, weather conditions and other external
conditions, in addition to their own vehicle.
As the need for defensive driving increases, it is also important for driver assistance or autonomous driving
systems to understand the driving intentions of other vehicles.
The driving behaviour information set (DBIS) consists of the operations of the subject vehicle and the
associated traffic situation, locally perceived from an egocentric perspective. By sharing this DBIS between
vehicles, it can be used for driving situation prediction algorithms based on artificial intelligence technology
or for real-time optimal driving decisions.

v
Technical Report ISO/TR 22087:2025(en)
Intelligent transport systems — Collection of agent behaviour
information and sharing between ITS stations
1 Scope
This document describes the common description of the driving behaviour information set (DBIS) data
structure and data exchange procedures for sharing among distributed ITS stations by nomadic devices.
2 Normative references
There are no normative references in this document.
3 Terms, definitions and abbreviated terms
For the purposes of this document, the following terms and definitions 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 Terms and definitions
3.1.1
nomadic device
ND
implementation of a personal ITS station which provides communication connectivity via equipment such
as cellular telephones, mobile wireless broadband (WIMAX, HC-SDMA, etc.), WiFi etc. and includes short
range links, such as Bluetooth or Zigbee to connect portable devices to the motor vehicle communications
system network
3.1.2
personal ITS station
P-ITS-S
implementation of an ITS station in a personal ITS subsystem
3.1.3
roadside ITS station
R-ITS-S
system, is installed at the road side, that receives and processes vehicular and pedestrian information
within a certain zone and determines the situation, in order to provide the safety warning and parking guide
service to vehicles and pedestrians
3.1.4
central ITS
C-ITS
ITS station assuming a central role.
3.1.5
vehicle ITS station
V-ITS-S
implementation of an ITS station in a vehicle ITS subsystem.

3.1.6
cloud ITS station
C-ITS-S
implementation of an ITS station in a cloud ITS subsystem.
3.2 Abbreviated terms
CALM communications access for land mobiles
DBIS driving behaviour information set
ITS intelligent transport systems
4 Introduction of DBIS
4.1 Ego-vehicle’s DBIS
As the need for defensive driving is emphasized, the importance of understanding the driving intention of
other vehicles in driver assistance systems or autonomous driving systems is increasing.
Ego vehicle’s dynamic driving tasks such as left/right lane change, cut-in/out can be informed to other
vehicles via the DBIS.
The DBIS is divided into
a) driver’s intention,
b) the status of vehicle,
c) the status of road, and
d) egocentric surrounding object’s information.
Figure 1 shows the use case of collection and sharing DBIS among V-ITS-S by nomadic devices. In Figure 1,
each V-ITS-S (including Ego V-ITS-S and Adjacent V-ITS-S) collects necessary information such as
driver’s intention, the status of vehicle, and road information and shares this information with utilizing
communication connectivity technologies in a nomadic device.

Key
1 ego vehicle ITS station with driver intention collector, vehicle status collector, and road information collector
2 adjacent vehicle ITS station with driver intention collector, vehicle status collector, and road information collector
3 communication protocol to share the DBIS among neighbor V-ITS-S with utilizing communication connectivity
technologies in a nomadic device
Figure 1 — Use case of collection and sharing DBIS among V-ITS-S
Figure 2 shows another use case of collection and sharing DBIS between V-ITS-S and C-ITS-S using nomadic
devices. Using these DBIS information, an ego vehicle can predict the operation of adjacent V-ITS-S and
prepare some necessary task. In Figure 2, the ego V-ITS-S collects necessary information such as driver’s
intention, the status of vehicle, and road information and shares this information to Cloud C-ITS-S with
utilizing communication connectivity technologies in a nomadic device.
Figure 2 — Use case of collection and sharing DBIS between V-ITS-S and C-ITS-S

4.2 Driver's intention
4.2.1 General
Predicting the driver's intention is necessary to prevent traffic accidents or to warn other drivers to avoid
traffic accidents. The information of driver’s intention consists of a longitudinal and lateral change mission
to be performed and the driver's state and attention to perform it. The driver's attention is the behavioural
information that is used to estimate the risk associated with performing a given task.
4.2.2 Intention of longitudinal control
Longitudinal control is to control the driving speed of a vehicle by recognizing various objects located
around the vehicle. Understanding the intention of longitudinal control of the vehicle and the driver’s state
can be helpful in predicting the driver’s intention.
4.2.3 Intention of lateral control
Lateral control is to control a vehicle to make an automatic provision without leaving the lane. For the most
part, understanding the intention of lateral control of the vehicle and the driver’s state can be helpful to
recognize white lanes on existing roads and keep the vehicle in proper lane.
4.2.4 State of driver
This is to identify the driver’s physical/emotional state, such as turning the driver’s face from side to side
and looking in the rear-view mirrors. It also aims to recognize the driver’s drowsiness, inattentiveness,
health, driver’s readiness, etc.
4.3 Status of vehicle
4.3.1 Speed of vehicle
To support lane change and cut in/out in autonomous driving, identifying the speed of adjacent vehicle is an
important piece of information to understand the status of vehicle. Based on the speed of adjacent vehicles,
autonomous driving can determine the proper operations. The speed of a static vehicle is zero.
4.3.2 Distance of vehicles
When a vehicle does lane change, identifying the distance information of adjacent vehicles can be used
to reserve the proper distance to change a lane. To do this, the DBIS includes the distance information of
adjacent objects.
4.3.3 Vehicle type
Vehicles in road can be diverse. It classifies passenger vehicle, public transportation, emergency vehicle,
bicycle, motor cycle, pedestrian, obstacles, etc.
4.3.4 Vehicle location
The information of vehicle location is used to identify the exact position of an ego adjacent V-ITS-S and it can
be use
...