Article citation information:

Gill, A., Smoczyński, P., Ławniczak, D. Measuring the variability of the pedestrian crossing function in the socio-technical system of urban road transport. Scientific Journal of Silesian University of Technology. Series Transport. 2022, 117, 57-68. ISSN: 0209-3324. DOI: https://doi.org/10.20858/sjsutst.2022.117.4.

 

 

Adrian GILL[1], Piotr SMOCZYŃSKI[2], Damian ŁAWNICZAK[3]

 

 

 

MEASURING THE VARIABILITY OF THE PEDESTRIAN CROSSING FUNCTION IN THE SOCIO-TECHNICAL SYSTEM OF URBAN ROAD TRANSPORT

 

Summary. In some areas of transportation systems, reduction of risk using typical safety engineering tools can be difficult due to the relatively small number of events that can be analysed to draw conclusions for the future. One way out of this situation is to analyse systems in their normal operation when no adverse event occurs. It can be done, inter alia, with the Functional Resonance Analysis Method. An important research problem in this context is how to describe the variability of system functions. In this article, we propose an original method, based on the number of hazard sources present in a given analysis domain and apply it to a real pedestrian crossing. The obtained results indicate that the quantitative coincidence measures proposed by us are a convenient way to capture ‘functional vibrations’ in real socio-technical systems. This allows the prediction of undesired states of such systems based on their normal operation.

Keywords: pedestrian crossing, hazard sources, public urban transport, Functional Resonance Analysis Method

 

1. INTRODUCTION

 

Intuitively, the traditional three-colour traffic lights remain the best form of crossing protection that practically eliminates the possibility of activating hazards. A similar phenomenon can be seen concerning railway level crossings equipped with barriers [11], although in both cases – despite advanced safety systems – there are still many hazard sources left. One of the most important of these sources was indicated by Krukowicz et al. [10]. Road traffic observations conducted by them in a large city in Poland made it possible to formulate an observation indicating that despite the improvement of traffic organisation and modernisation of traffic lights at intersections, a large number of road accidents and collisions are caused by inappropriate, often illegal behaviour of road users. A detailed literature review on the assessment of pedestrian-vehicle interaction on urban roads has been presented by Thakur and Biswas [19].

Problems in raising an already high level of safety are noticeable in many areas of human activity, including in rail transport [2, 14]. This is an example of a controller paradox [21], quoted in [4]), whose task is to minimise system variability; however, this variability is also the only way to measure the effectiveness of this controller. In such situations, it is now proposed to abandon the use of traditional methods of safety engineering (FTA, FMEA) for the benefit of new ones, allowing a comprehensive description of the system during its operation – both when everything goes fine as well as in the event of hazard activation.

Examples of new methods include the Systems-Theoretic Accident Model and Processes (STAMP), proposed by Leveson [12] and used among others for modelling maritime [8] or railway transport systems [20], where, however, its theoretical character was pointed out. STAMP is also used as an enhancement of the Event Analysis of Systemic Teamwork (EAST) method [16], which was used independently, among others, in studying the behaviour of road traffic participants during crossing intersections [15].

Another popular method of the ‘new approach’ (often referred to as ‘Safety-II’) is the Functional Resonance Analysis Method (FRAM) proposed by Hollnagel [5], and still being developed [4]. The use of the FRAM method is shown in the example of air [18] or maritime transport [13]. However, there are no applications in urban transport [17]. Furthermore, the existing publications focus primarily on modelling using characteristic hexagons rather than on the attempts to define how ‘functional vibrations’ manifest themselves in real socio-technical systems.

This article aims to propose an original understanding of functional vibrations for the pedestrian crossing function, as well as to determine their waveform based on our observation of a selected real pedestrian crossing in Poznan (Poland). Section 2 presents the necessary theoretical information on functional vibrations and functional resonance, as well as the applied research methodology for determining the pedestrian crossing function vibrations. While section 3 discusses the results of the observation study and shows how to apply these results for determining functional vibrations. Finally, section 4 contains conclusions and directions for further research.

 


 

2. MATERIALS AND METHODS

 

2.1. Functional vibrations

 

The concept of functional vibration is a key element of the Functional Resonance Analysis Method (FRAM) used for modelling socio-technical systems [5]. An important and sometimes overlooked aspect of the theory behind FRAM is the mere phenomenon of functional resonance, explaining the mechanism of activating hazards. According to this theory, adverse events occur not as a result of breaking (intentional or accidental) applicable procedures and specifications of the system operation but as a result of the unfavourable superposition of the functions performed in it. This is well illustrated by the diagram shown in Figure 1.

 

 

Fig. 1. Mechanism of hazard activation according to
the functional resonance theory
[17], based on [6]

 

In the theory of functional resonance (Figure 1), it is assumed that the result of the system's operation is the composition (superposition) of its functions. The superposition is variable over time but usually remains below a certain limit, which exceeding results in the activation of a hazard (an adverse event, an accident). Such a view on the work of socio-technical systems allows them to be improved also when there are no adverse events. Thus, one should examine the various ways of correct system operation – the variability, as Hollnagel calls it – and undertake actions aimed at limiting this variability.

In this study, we suggest that variability is described using the hazard sources that appear during the implementation of a given function. A hazard source (also called 'a risk source') is an element, which alone or in combination with other elements, has the potential to give rise to (typically) undesirable consequences [1, 7]. A broader discussion on the motivation to choose such a definition was presented in [3]. The most important is that two or more hazard sources may not be harmful; however, when combined they interact to become dangerous [9]. This is graphically depicted in Figure 2.

We, therefore, propose that variability  of the function performed by the socio-technical system in time would depend on the number of occurrences of hazard sources identified in the analyses domain in subsequent observation time intervals of this domain, that is:

 

                                                                  (1)

 

where V is the value of variability determined in the observation time interval  and  denotes the number of occurrences of the -th hazard source from the  sources identified in a given analysis domain in the -th observation time interval. Because the data can be registered in several measuring sessions (for example, different days of the week) covering the same observation time interval , a counter  was introduced to denote observation time intervals occurring at the same clock time in several measuring sessions.

 

 

Fig. 2. Schematic representation of the relation between the hazard source (HS)
and the hazard (H), as considered in this study

 

Describing variability using Equation (1) allows differentiating between two levels of superposition. First, there can be many hazard sources occurring during the performing of one function of a socio-technical system, and their number is variable over time. The variability of a particular function will therefore be given by the superposition of the number of occurrences of individual hazard sources. Second, in the context of performing all functions by a socio-technical system, the superposition concerns variations coming from all its functions – and this superposition, following the FRAM assumptions, determines the possibility of having an adverse event.

 

2.2. Selection of case study crossing

 

To carry out the variation measurement, we have selected a pedestrian crossing equipped with traffic lights located near two significant pedestrian traffic generators (Figure 3). The first of them is the campus of the Poznan University of Technology, used by approx. 20,000 students. In the immediate vicinity of the crossing, both the most important didactic buildings and dormitories are located. The second generator is Posnania, one of the largest shopping centres in Poland. In addition, near the pedestrian crossing, there is an intersection of two tram routes. This makes the tram stop located at the crossing to be often used by passengers who make transfers.

The crossing leads through two roadways and two tram tracks between them. The street is a fragment of the second communication frame, that is, the bypass of the city centre. The western roadway has two lanes, the eastern – four lanes, including one for turning into the shopping centre. The maximum valid speed for all roadways is 50 km/h. Three sets of traffic lights are installed at all parts of the crossing: two on the roadway crossing, and one on the tram track crossing. The condition of the roadway surface and tracks were assessed as good, not interfering in any way with the movement of vehicles. Visibility is very good, as there are no buildings or advertisements near the crossing that could limit it. Within the crossing, there is street and tram stop lighting that is sufficient to light the roadways as well.

To facilitate the collection of observational data at the pedestrian crossing, it was divided into two zones (Figure 4). Zone I includes the crossing through the tram track and the adjacent tram stop Kórnicka. While Zone II covers the rest of the pedestrian crossing, that is, the roadways in both directions.