An improvement of the conceptual system of the sequential events model of road crashes (i-MOSES)

Abstract

Background: The circulation of vehicles, motorized or not, is a risky activity that can lead to a traffic accident in which all road users can be affected. Road accidents generate high personal, labor, health and economic costs, as well as civil, administrative and even criminal responsibilities. Therefore, it is necessary to carry out a correct investigation of these road accidents. This paper reviews one of the models used for this investigation, the sequential events model for road crashes called MOSES. This model simplifies into a single sequential analysis the actions and conditions that have generated the occurrence and correlation of events that have led to a collision between two bodies, at least one of which is a vehicle, with harmful consequences for the environment, people and things.

Methods: Analyzing the road accidents that occurred in the city of Badajoz between 2018 and 2022, this work proposes a new position of the sequential events in road accidents. This new position is present in more than fifty percent of the analyzed road accidents. How this new position can improve the description of traffic accidents is tested by analyzing an actual traffic accident recorded in the city of Badajoz between a motorcycle and a car.

Results: The new position has been called Trust Position (TP) and is located between the Real Perception Position (RPP) and the Decision Enforcement Position (DEP) in the sequential events model for road crashes (i-MOSES). Furthermore, in this improvement of the MOSES model (i-MOSES), the reaction time (RT) is analyzed in more depth with the PIEV (Perception, Intellection, Emotion and Volition) theory, establishing that between RPP and TP are present the phases of perception and intellection, and between TP and DEP are present the phases of emotion and volition.

Conclusions: This analysis shows how the proposed i-MOSES model allows for a deeper and more effective analysis of the causes that generated the traffic accident and all its circumstances. Moreover, it provides conclusions closer to the reality of how the accident actually happened and why it could have happened, ultimately leading to preventive measures to avoid future accidents.

Keywords: Accident analysis; Evasive action; Reaction time; Response time; Road safety; Traffic conflicts.

Fig. 1

Phases of the Theory of Accident Evolution in relation to the MOSES model. Perception phase (PPP-RPP), decision phase (DEP) and conflict phase (PNE-POI-FP).

Fig. 2

Positions of a road accident according to MOSES model.

Fig. 3

Matrix analysis of MOSES model.

Fig. 4

Analyzed positions of a road accident according to MOSES model. Detail. The average RT of a normal person is taken as 0.75 s for all calculations in Spain.

Fig. 5

Analyzed positions of a road accident according to MOSES model. Detail. Reaction time based on PIEV theory.

Fig. 6

Positions of a road accident according to i-MOSES model.

Fig. 7

Analyzed positions of a road accident according to i-MOSES model. Detail. RT based on PIEV theory and adding the new position between RPP and DEP.

Fig. 8

Matrix analysis of i-MOSES model.

Fig. 9

Side impact collision between a car and a motorcycle. POI. a) video recording of the road accident, b) sketch of the road accident.

Fig. 10

Car position. a) reference point is the beginning of the crosswalk in frame 09:54:13, b) reference point is the POI in frame 09:54:15.

Fig. 11

Sketch of the distance measured on the public road according to the reference points in Fig. 10(a and b).

Fig. 12

Motorcycle position. a) reference point is the second tree in frame 09:54:14, b) reference point is the last road marking in frame 09:54:15.

Fig. 13

Sketch of the distance measured on the public road according to the reference points in Fig. 12(a and b).

Fig. 14

Calculation results with MOSES model. First hypothesis (RPP does not coincide with PPP).

Fig. 15

Sketch of the road accident with MOSES model. First hypothesis (RPP does not coincide with PPP).

Fig. 16

Calculation results with MOSES model. Second hypothesis (RPP coincides with PPP).

Fig. 17

Sketch of the road accident with MOSES model. Second hypothesis (RPP coincides with PPP).

Fig. 18

Motorcyclist evasive maneuver. a) video recording of where the motorcyclist's evasive maneuver begins, b) sketch of this complete evasive maneuver.

Fig. 19

Calculation results with i-MOSES.

Fig. 20

Sketch of the road accident with i-MOSES.

Fig. 21

Matrix analysis of i-MOSES model. Road accident analyzed in this paper.