Traffic Psychology as a field of applied psychological research: opportunities and perspectives in Russia

Кочетова, Т В

doi:10.17759/sps.2018090402

Cited by 3 publications

(6 citation statements)

References 8 publications

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“…Based on the research of Russian and foreign scientists [7,14,16,17], we identified the criteria for the formation of positive stereotypes in relation to public transport in the following areas: 1) social and administrative, 2) cultural and household, 3) advertising and information. The degree of significance of the criteria in each group was determined on the basis of the analysis of the questionnaire results.…”

Section: Resultsmentioning

confidence: 99%

“…In this sense, this process has its own specifics and laws inherent only to it. In our case, the use of transport psychology data [5,6,7,8] is quite natural and brings our work to the level of interdisciplinary research. Competent management of the social and cultural adaptation of a foreigner implies an understanding of the importance of the interconnection and interdependence of all aspects of human life in society, the adoption of a new culture by household factors, which include transport infrastructure [4,9,10].…”

Section: Introductionmentioning

confidence: 99%

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Ethnic stereotypes in the assessment of transport infrastructure

Pozdnyakova¹,

Zotov²,

Тарасова

et al. 2023

E3S Web Conf.

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The assessment of transport infrastructure is one of the significant criteria for a foreigner who chooses another country as a place of work or study. This article is aimed at identifying and scientifically describing ethnic stereotypes in the assessment of transport and transport infrastructure of the host country, analyzing the elements of ethnic consciousness involved in the formation of prejudices towards foreign culture or everyday phenomena. Since any ethnic stereotypes are "fragments of contacts" between peoples, their assessment in terms of historical and cultural interaction seems important and timely. Ethnic stereotypes in the assessment of transport infrastructure have a significant impact on the formation of the image of the country and affect the process of social and cultural adaptation of a foreigner. Research carried out in this direction makes it possible to find effective solutions to specific problems and to take into account the specifics and the influence of the human factor on the artificial environment, and the transport environment is part of it. Given the diversity of real ethnic groups, which include traffic users, it is necessary to raise the issue of developing verified programs of social and cultural adaptation for various categories of foreign citizens.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ethnic stereotypes in the assessment of transport infrastructure

Pozdnyakova¹,

Zotov²,

Тарасова

et al. 2023

E3S Web Conf.

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“…A literature review shows that researchers are actively engaged in exploring data on characteristics of various aspects of drivers' behaviour (Brackstone and McDonald, 1999, Chliaoutakis et.al, 2002, Kochetova, 2018, Miles and Johnson, 2003.…”

Section: Introductionmentioning

confidence: 99%

“…Quite obviously, emphasis on investigation of stylistic features of driving does not imply investigation of sociopsychological aspects of interactions between drivers as road traffic participants. Since road traffic is a complex social system, which includes multiple participants -transportation subjects, it is necessary to pay attention at the analysis of driving features that characterize a driver's behavior in a wide range of interactions with the other traffic participants (Efremov and Kochetova, 2018, Efremov, 2018. We consider such interactions to be the contents of a driver's behavior in the context of his movement in relation to other drivers nearby in traffic.…”

Section: Introductionmentioning

confidence: 99%

“…In other words, driving strategies differ from vehicle control styles since they are stable patterns of traffic behavior characterized by certain ways and means for solving socalled "driving tasks" in traffic and interactions with other drivers (Wilde, 1976), for instance, while changing lanes or overtaking. Based on this perception of strategic behavioral characteristics, by a "driving strategy" we will mean steadily recurring patterns of a driver's traffic behavior (Kochetova andMeinhard, 2020, Wilde, 1976) that characterize his interactions with other traffic participants.…”

Section: Introductionmentioning

confidence: 99%

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Neural network model for recognition and classification of types of interactions in road traffic

Ефремов¹,

Кочетова²

2022

ToTS

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The article presents neural network for recognition of driving strategies based on interactions between drivers in road traffic. It analyzes the architecture of the model implemented as a self-organizing map (SOM), consisting of a group of neural networks based on radial basis functions (RBF). It is a training model grounded in the biological foundations of artificial neural networks, in which the training set should consist exclusively of input vectors; wherein the network training algorithm adjusts itself the network's weights to obtain consistent output vectors (i.e. to make presenting sufficiently close input vectors result into the same outputs).The article presents the results of using a new generation of the neural network developed by us, which includes an adaptive learning algorithm to reduce the effect of re-training (overfitting) and false recognition, as well as to improve the determination of the boundaries between clusters.The aim of the research is to outline architecture and structure of the neural network model that allows recognizing strategical characteristics of driving and can identify strategies of interactions between vehicles (their drivers) in road traffic as well as identify behavioral patterns This paper considers driving strategies that characterize the interaction of dyads of vehicles (drivers) moving in road traffic. The research results show that the SOM RBF neural networks can recognize and classify types of interactions in road traffic based on modelling of the analysis of vehicle movement trajectories. Experimental results demonstrate the neural networks architecture and networks learning involving 400 iterations of streaming the training data representing 500 possible simulated interaction situations. This paper presents a novel neural network model for recognition of drivers' behaviour patterns and for classification of driving strategies into five general classes: (1) competition strategy, (2) contest strategy, (3) evasion strategy, (4) compromise strategy, and (5) active confrontation strategy. This neural network has demonstrated a high rate of recognition and concise clusterization of similar driving strategies.The key contribution of this paper: it proposes a neural network model based on Kohonen's Self-Organizing Map (SOM) for detecting drivers' behaviours from vehicle movement patterns -driving strategies -instead of monitoring driver's specific activities.

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Features of Professional Stress of Workers in the Transport Industry

Кононов

2023

Человеческий Капитал

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В статье представлены результаты эмпирического исследования особенностей переживания стресса работниками транспортной сферы, на примере работников общественного транспорта г. Москвы. В исследовании приняли участие: водители (n=21), техники (n=8), наладчики (n=11), диспетчеры (n=7), медицинские работники (n=9). Общее количество респондентов составило N=56. Целью исследования было выявление особенности переживания стресса работниками общественного транспорта. Использовались следующие психодиагностические методики: экспресс-диагностика состояния стресса К. Шнайдера; шкала психологического стресса (PSM-25); оценочная шкала стрессовых событий Т. Холмса и Р. Раге; шкала организационного стресса А. Маклина (адаптация Н.Е. Водопьяновой); методика определения типа поведенческой активности. Анализ полученных данных позволяет говорить о наличии статистически значимых различий между группами работников общественного транспорта: по оценочной шкале стрессовых событий Т. Холмса и Р. Раге (р=0,039). Более высокие значения отмечаются в группе водителей (Ср.ранг=34,36) и механиков (Ср.ранг=33,31); по шкале организационного стресса А. Маклина (адаптация Н.Е. Водопьяновой) (р=0,018). Более высокие значения отмечаются в группе механиков (Ср.ранг=36,75) и медицинских работников (Ср.ранг=35,89), в группе водителей данный показатель составляет (Ср.ранг=30,81). The article presents the results of an empirical study of the characteristics of stress experienced by transport workers, using the example of public transport workers in Moscow. The following participants took part in the study: drivers (n=21), technicians (n=8), adjusters (n=11), dispatchers (n=7), medical workers (n=9). The total number of respondents was N=56. The purpose of the study was to identify the characteristics of stress experienced by public transport workers. The following psychodiagnostic techniques were used: express diagnostics of the state of stress by K. Schneider; Psychological Stress Scale (PSM-25); T. Holmes and R. Rahe Stressful Events Rating Scale; A. McLean's organizational stress scale (adapted by N.E. Vodopyanova); technique for determining the type of behavioral activity. Analysis of the data obtained allows us to talk about the presence of statistically significant differences between groups of public transport workers: according to the rating scale of stressful events by T. Holmes and R. Rage (p = 0.039). Higher values are observed in the group of drivers (Avg. rank = 34.36) and mechanics (Avg. rank = 33.31); according to A. McLean's organizational stress scale (adapted by N.E. Vodopyanova) (p = 0.018). Higher values are observed in the group of mechanics (Avg. rank = 36.75) and medical workers (Avg. rank = 35.89), in the group of drivers this indicator is (Avg. rank = 30.81).

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Traffic Psychology as a field of applied psychological research: opportunities and perspectives in Russia

Cited by 3 publications

References 8 publications

Ethnic stereotypes in the assessment of transport infrastructure

Ethnic stereotypes in the assessment of transport infrastructure

Neural network model for recognition and classification of types of interactions in road traffic

Features of Professional Stress of Workers in the Transport Industry

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