# Pedestrian tracks crossing: how to conceive safety systems based on human cognitive and biomechanical understanding?

Elise Grison, Christopher Paglia, Aurélie Foucault, Inès Djelloul-Daouadji, Ahmed Yacine Lardjane, Laura Wallard, Fabien Jazeron

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## To cite this version:

Elise Grison, Christopher Paglia, Aurélie Foucault, Inès Djelloul-Daouadji, Ahmed Yacine Lardjane, et al.. Pedestrian tracks crossing: how to conceive safety systems based on human cognitive and biomechanical understanding?. Transport Research Arena conference, Apr 2024, Dublin, Ireland. hal-04880276

HAL Id: hal-04880276

https://hal.science/hal-04880276v1

Submitted on 10 Jan 2025

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# Pedestrian tracks crossing: how to conceive safety systems based on human cognitive and biomechanical understanding?

Elise Grison<fnref n="1" />, Christopher Paglia<fnref n="2" />, Aurélie Foucault<fnref n="4" />, Djelloul-Daouadji Inès<fnref n="1" />, Ahmed Yacine Lardjane²³, Laura Wallard<fnref n="3" />, Fabien Jazeron<fnref n="5" />

**Abstract.** The paper presents the methodology developed in a collaborative project between academic and industrial partners set-up to develop and test new safety systems at pedestrian tracks crossing installed in little French train stations. While these installation benefit from a safety system installation indicating approaching trains, they still lead to frequent accidents, mainly due to travelers' inattention, misunderstanding or environmental factors that impact traveler perception. Few research has been conducted on this specific situation, resulting on a lack of knowledge on human behavior when crossing this installation. Moreover, when developed, safety systems are rarely objectively tested in terms of efficiency on behavior leading to currently few perspectives to reduce the number of accidents. Thus, to fill this gap, the research project exposed in this paper propose a new approach based on cognitive and biomechanical analyses to develop and test in real-like situation, using a virtual reality environment completed to a scale 1:1 physical train station mock-up, various new safety systems. These analyses completed with technical and economic ones will help to produce better well-sourced data to ground decision-makers choice concerning more effective future safety system to implement.

**keywords:** Biomechanics; Human Behavior; Neurosciences; Safety.

## 1 Introduction

In train stations, in the absence of a footbridge or an underpass, a passage can be directly installed on the tracks, to enable travelers to go from one platform to another. This installation, called Pedestrian Tracks Crossing (PTC, see Fig 1.), is relatively common all around the world, especially in Europe and America. In France alone, there are approximately 1000 train stations equipped with PTC. To ensure travelers' safety during crossing, various type of "safety systems" are installed before or on the PTC to alter

<footnote n="1">¹SNCF, 93210, La Plaine Saint-Denis, France</footnote>

<footnote n="2">²Railenium, 59308, Valenciennes, France</footnote>

<footnote n="3">³Université Polytechnique Hauts-de-France, CNRS, UMR 8201-LAMIH, F-59313, Valenciennes, France</footnote>

<footnote n="4">⁴SNCF Réseau, 93210, La Plaine Saint-Denis, France</footnote>

<footnote n="5">⁵SCLE SFE, 13014, Marseille, France
elise.grison@sncf.fr</footnote>
and/or explain the risks to travelers, such as lights, signage, ringing alarms or barriers. However, a constant number of accidents are observed every year. One assumption to explain the lack of efficacy of safety systems on travelers' behavior is that the safety systems were not developed considering human cognitive and physical activity when moving through train stations and PTC. This can be explained by the past poor practices that do not include human factor and cognitive science in industrial and technological development, but also by the lack of methodologies to objectively measure the effectiveness of a product before its release.

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Photograph of a train station (Belloy Saint Martin, France) equipped with pedestrian tracks crossing.</figcaption></figure>

However, this past decade, both cognitive sciences and methodologies to measure human behavior and movement precisely have been developed. Therefore, it can be assumed that moving and safely crossing tracks involve many high-level cognitive processes to [1, 2, 3]:

* acquire information (schedules, weather, presence of a train),

* form a global representation of the situation and the crossing track situation,

* evaluate the risks (collision, fall, delay), and

* make a decision (to cross or not).

All these steps necessary for safely crossing tracks might be disrupted by other factors [4]. These factors can be related to travelers themselves such as heuristics to minimize cognitive effort (habits) or distractions (music, smartphone, talking). They can also be linked to the environment [5] such as the visibility or the behavior of other travelers.

Research on biomechanical aspect also have helped to better define this activity. The locomotive task primarily involves walking, considered a complex activity from a biomechanical point of view. Walking requires moving the body along an anteroposterior axis through a sequence of unipodal and bipodal supports [6]. This complexity requires the coordination of multiple body systems and cognitive functions, including sensory perception and motor planning [7]–[9].

Track crossings is a challenging locomotive task, where walking is intersected by the potential dangers of oncoming trains. Understanding the biomechanics of this locomotive task during track crossings is mandatory to improve safety. Historically, motion
analysis has been used to understand the effect of surroundings infrastructures, includ-
ing markings, tactical pavements on crossing behavior, by quantifying reaction-time,
head rotations, walking velocity, crossing onset and duration, and analyzing crossing
initiation [10]–[13]. The previous research methods are heavily criticized [14] [15].
For example, several studies have used uncontrolled data from surveillance cameras,
which might impact the results due the unknown participants conditions[15]. Moreover,
other methods rely on questionnaires[16] or decision measurement using a key-
board/joystick[14]. The ecological validity and objectivity of these methods are limited
as they force participants to imagine how they would act or feel.

Thus, using virtual reality combined with various physiological sensors is now pos-
sible to track human behavior (gaze, head movement, acceleration) in real-like situa-
tions. For example, two safety systems at PTC have been recently evaluated consider-
ing their effects on human behavior using virtual reality combined with physiological
as well as behavioral measures [17].

Thus, the aim of the project presented in this paper is to conceive new safety systems based on human behavior understanding to improve safety at PTC. To this end a col- laborative project has been launched between the French National Railway Company (SNCF), SNCF Réseau, the Technological Research Institute specialized in railway transport (IRT Railenium), a French company specialized in rail signage (SCLE SFE), and the haut-De-France Polytechnical University. Together, partners will develop an approach combining both cognitive and biomechanical research with industrial devel- oppement. In this paper, the authors propose to describe the methodology developed in the project to highlight the value of combining all these competencies from the early stages of conceptualization to the final stages of development of safety systems.

In the early stages of the project, literature on cognitive and biomechanical aspects
will be analyzed to propose a human model of a safe PTC. Based on that model, new
safety concepts will be developed and tested through a close-to-reality experimental
set-up combining virtual reality, a scale 1 mock-up PTC and various behavioral, phys-
iological, and biomechanical measures. These experimental studies will help to pre-
cisely understand the effect of safety concepts on human behavior, and to improve,
validate or reject them. Economical as well as technical evaluations of systems will be
then conducted to select which concept is most suitable for industrial developpement.

## 2 Method

2.1 Testing platform

To fulfil the objectives set for the project, it was deemed necessary to equip ourselves
with a test platform of our own. This will allow for the participants of the study to
progress in a virtual reality environment aiming at reproducing real-life conditions of a
situation, but with limited biases compared to what a real situation usually implies. The
test platform consists of two distinct environments. The first one is the physical plat-
form, which recreates parts of a train station true to scale (1:1) – this includes a station
platform, a portion of a double-track railway and a pedestrian tracks crossing (see Fig.2
for a 3D modeling of the 1:1 platform).
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** 3D modeling of the 1:1 scale platform. Participants will be allowed to move through a 11x20 meter platform including a PTC and height difference between the PTC and train station platform. Image created by Movida Production with HARFANG®3D.</figcaption></figure>

The second one, the virtual environment, synchronized to the physical environment, reproduces in detail all the elements of a train station cited previously as well as various scenarios depending on the weather or the aim of participants (see Fig.3 for a virtual environment view). Sensors are set up to collect behavioral and physiological data, such as eye tracking data, kinetics and kinematics data relative to walking, muscle activation data. The combination of these methodologies (mixed reality, sensors) allows for a detailed understanding of train passenger behaviors in interaction with contextual factors (weather, station layout, station footpath location, potential presence of running/stationary trains), as well as the quantification of behaviors.

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Screenshot of the virtual train station in development. The station includes two little buildings, two platforms and one PTC. Image created by Movida Production with HARFANG®3D.</figcaption></figure>

## 2.2 Principles of behavioral studies

### Transport Research Arena

In order to observe participants behavior as naturally as possible and avoid any expectancy effect, participants won't be informed at first of the purpose of the study, but they will be explained that their participation in the study will help SNCF to improve its services in train station. This explanation will give objective for participants to travel in the virtual environment as they will have to move through it to evaluate different services. During these moving, they will or not cross the PTC.
We will vary the condition of the PTC crossing, taking a special attention to trav-
eler's personal factors such as distraction or age, but also to environmental factors such
as visibility (night or day), social influence (other people crossing the PTC) and the
approaching of train. To appear as natural as possible, all induced factors will be fully
integrated in the scenario. For example, if we are interested by the impact of crossing
the PTC with luggage, participants will have to test a service that justify the fact they
have to carry a luggage (such as a new luggage room). This principle has already been
tested and have shown its efficiency to immerse participants in a real-like scenario
without revealing the real purpose of the study [17]. The real purpose will be thus ex-
plained and detailed at the end of the experimental session and discussed with partici-
pants.

All PTC crossing will be monitored to collect the conditions of the crossing (personal as well as environmental factors; train approaching or not; safety system) as well as all behavioral and physiological measures (safe crossing or not, gaze behavior, etc.).

Around 100 participants, representative of French population will be tested per stud-
ies to collect enough data (dangerous crossing, gaze behavior, etc.) to explore the sta-
tistical effects of our tested factors (personal, environmental, safety system), and po-
tential interaction between them. These analyses will be completed by an interview with
the participant and the fulfilment of questionnaire. We will reveal the real purpose of
the study and discuss openly of safety system with them to collect potential improve-
ment of system and to validate if our immersion has been successful [18]. Finally, re-
sults of the first study will be used to improve either the methodology or the safety
systems, to improve both through the project and be able to state on the safety system
efficacity on behavior.

## 2.3 Principles of biomechanical studies

In addition to the cognitive and physiological analysis, we will take a specific atten-
tion to biomechanical aspect of the crossing. Indeed, through motion analysis, we can
objectively quantify the impact of risk factors, surrounding infrastructures on both cog-
nitive functions, motor behavior and postural adjustments of users. The biomechanics
measurement can objectively explain the situational awareness of the users, researchers
reports that safety equipment resulting a small variation over the time horizon (std) of
the walking speed, gait pace, kinetics and kinematics metrics can confirm the improve-
ment of user's situational awareness and cognitive functioning, leading to an improved
safety [19], [20].

Using our novel approach, involving the platform built exclusively to this research,
representing a train station and allowing a natural forward movement in the safest and
most ecological situation, remains the best experimental condition as it reflects pedes-
trians' behavior in real life[14]. Additionally, this will allow the investigation of the
impact of the major's risks factors in both environmental level (i.e ramp) and pedestrian
level (i.e. distraction) identified by applying the unsafe pedestrian level crossing frame-
work [21].

Our methodology including markerless motion analysis, the use of inertial measure-
ment units will bring new insights to users' safety, by improving and validating security
equipment, based on their effect not only on the psychological aspect, but also on the
underlying human biomechanics such as energy costs, spatiotemporal parameters, kin-
ematic, kinetics and muscle activity.

3 Expected result of the project: evaluation matrix

To help decision makers, we will develop an evaluation matrix including all the objec-
tive behavioral and biomechanical variables to characterize the effect of the safety sys-
tems tested. The matrix will include all the personal and environmental factors consid-
ered in the studies. To complete this matrix, technical and economic analyses will be
performed to appreciate the degree of feasibility of the tested solution. This tool will be
used to make decision about what kind of safety system to develop in the final stage of
the project considering results of the various analyses made in the project, the current
accidentology (from personal or environmental causes), and the feasibility of the solu-
tion.

4 Conclusion

In conclusion, in this project we propose to reverse the way classical development is
made in industry regarding safety at PTC. While improvements are usually first imple-
mented and tested in the real environment, we propose to first test in real-like environ-
ment the efficacity of various possible improvement on different objective measures.
This method, based on scientific method, gives the advantage to select upstream im-
provement, based on objective efficacity results, that have the best chance to work be-
fore industrial development and installation that might be long and costly.

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