Designing the conditions of road traffic in the cities taking into account the human factor

Прасоленко, О.В.; Lobashov, Oleksii; Bugayov, Igor; Gyulyev, Nizami; Filina-Dawidowicz, Ludmiła

doi:10.1109/mtits.2019.8883381

Cited by 7 publications

(5 citation statements)

References 17 publications

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“…This human factor in road traffic management, has previously been highlighted as a necessary input in the design of resilient road traffic systems [24].…”

Section: Implications Of the Outcomes Of This Exploratory Studymentioning

confidence: 99%

“…Research related to traffic congestion globally, can be categorized into four themes: studies aimed at understanding and describing traffic patterns both quantitatively and qualitatively [1] [2] [3] [22] [23] [24], research work aimed at predicting and estimating traffic congestion using various parameters [25]- [38], studies aimed at modelling road networks with a primary aim of decongesting cities and urban areas [23] [24] [25] [39] [40] [41] [42] [43], and studies aimed at quantifying the impact of traffic congestion on other socio-economic aspects such as air quality, health, economic performance, etc. [5] [6] [7] [8] [9] [11] [12] [13] [18] [19] [20] [44] [45] [46] [47].…”

Section: Introductionmentioning

confidence: 99%

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Characterizing Peak-Time Traffic Jam Incidents in Kampala Using Exploratory Data Analysis

Hamza¹,

Yahya²,

Kasule³

et al. 2023

JTTs

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Traffic congestion is associated with increased environmental pollutions, as well as reduced socio-economic productivity due to significant delays in travel times. The consequences are worse in least developed countries where motorized road transport networks are often inefficiently managed in addition to being largely underdeveloped. Recent research on traffic congestion has mostly focused on infrastructural aspects of road networks, with little or no emphasis at all on motorists' on-the-road behavior (MB). The current study thus aimed to bridge this knowledge gap by characterizing traffic jam incidents (TJI) observed over a period of 80 days in Uganda's Capital City, Kampala. MB as well as road network infrastructural factors such as road blockage (RB), were captured for each of the observed TJI. A total of 483 peak-time TJI were recorded, and exploratory data analysis (EDA) subsequently performed on the TJI dataset. EDA involved Hierarchical clustering analysis (HCA) and K-means clustering of the TJI dataset, as well as a detailed descriptive statistical analysis of both the entire dataset and the emerging TJI clusters. A highlight finding of this study is that 48.2% of the observed TJIs were as a result of on-the-road motorist behavior. Furthermore, the intervention of traffic police officers in a bid to regulate traffic flow was equally responsible for 25.9% of the TJIs observed in this study. Overall, these results indicate that whereas road infrastructural improvement is warranted in order to improve traffic flow, introducing interventions to address inappropriate on-the-road motorists' behavior could alone improve traffic flow in Kampala, by over 48%. Additionally, in-order to effectively regulate traffic flow in Kampala and other least developed cities with similar traffic congestion management practices, motorists' on-the-road behavior ought to be factored into any data-driven mechanisms deployed to regulate traffic flow and thus potentially significantly curbing traffic congestion.

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“…This human factor in road traffic management, has previously been highlighted as a necessary input in the design of resilient road traffic systems [24].…”

Section: Implications Of the Outcomes Of This Exploratory Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Characterizing Peak-Time Traffic Jam Incidents in Kampala Using Exploratory Data Analysis

Hamza¹,

Yahya²,

Kasule³

et al. 2023

JTTs

View full text Add to dashboard Cite

show abstract

“…reduce travel-related losses, such as travel time and nerve energy expenditure, with zero loss of comfort [46][47][48][49][50][51]. At the same time, the ways of realizing this goal are significantly influenced by individual characteristics of people [52,53]. However, in the present hour, information technologies for the design of transport systems of the locality do not guard the individual features of the city's citizens, who can be seen as having their temperament.…”

Section: Literature Reviewmentioning

confidence: 99%

Intelligent Decision Support System for Modeling Transport and Passenger Flows in Human-Centric Urban Transport Systems

et al. 2022

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Engineering human-centric urban transport systems should be carried out using information technology in forecasting traffic and passenger flows. One of the most important objects of urban transport systems’ progress is modeling patterns of transport flows and their distribution on the road network. These patterns are determined by the subjective choice of city residents of traffic routes using public and private transport. This study aimed to form a sequence of stages of modeling transport and passenger flows in human-centric urban transport systems and passenger flows in the human-centric urban intelligent transport systems and to determine the patterns of change to the gravity function of employees of municipal services. It was revealed that the trip distribution function of workers of urban service enterprises can be described by the attributes of the structure of the city, socio-economic data, and attributes characterizing the zones and its residents.

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“…IH  -відношення фактичного індексу напруження водія до фонового значення можна визначити за формулою: Конфліктні ситуації за ступенем небезпеки поділяються на три типи: легкі, середні і критичні (4) [18]. Для реєстрації параметрів вповільнення використовували прилад racelogic [20]. Фрагмент теплової карти місць виникнення конфліктів представлено на рис.…”

Section: виклад основного матеріалуunclassified

Modeling the Driver's Reaction Time Taking Into Account the Influence of Conflict Situations on City Streets

Прасоленко

Chumachenko²,

Grekova

2021

MEC

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The driver's reaction time is the most important characteristic when driving. The driver's reaction time is the period of time from the moment the stimulus appears in the driver's field of vision until the start of the action (application of the brake pedal, accelerator, steering wheel). The response time to stimuli depends on: the driver's age; the state of his health; mental state; alcohol or drug consumption; if at the moment he is in the vehicle alone or with a passenger, etc. The functional state of the driver is a complex of characteristics of the functions and qualities of the operator, which directly or indirectly characterizes the performance of labor activity. This definition draws a line between the state of a person and the state of his individual physiological and psychophysiological functions. One of these indicators is the stress index. Heart rate is a stable and accurate indicator of functional status. The experiment involved drivers with 10-16 years of experience. The driver's cardiogram was recorded using a portable Holter and analyzed in the CardioSens CS system. According to the degree of danger, conflict situations are divided into three types: light, medium and critical. The degree of danger of a conflict situation is determined by the appearance of critical accelerations. A racelogic device was used to register the acceleration parameters. The obtained dependences of the change in the functional state of the driver and the reaction time in accordance with the number of conflict situations while driving indicate significant fluctuations in these indicators. Change in reaction time from 0.7 sec. up to 1.5 sec. associated with significant psychophysio-logical stress on the driver, the number of conflict situations of various types: the appearance of a pedestrian, dangerous maneuvering of other vehicles, etc. At the same time, the driver's stress may increase by more than 2.5 times. The article discusses an approach to modeling the driver's reaction time, taking into account the influence of conflict situations on city streets. Experimental studies of the regularities of changes in the reaction time, the stress index of drivers in traffic on city streets have been carried out. Two factor models have been built, taking into account the mutual influence of factors of movement time in urban conditions and the number of conflict situations.

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Designing the conditions of road traffic in the cities taking into account the human factor

Cited by 7 publications

References 17 publications

Characterizing Peak-Time Traffic Jam Incidents in Kampala Using Exploratory Data Analysis

Characterizing Peak-Time Traffic Jam Incidents in Kampala Using Exploratory Data Analysis

Intelligent Decision Support System for Modeling Transport and Passenger Flows in Human-Centric Urban Transport Systems

Modeling the Driver's Reaction Time Taking Into Account the Influence of Conflict Situations on City Streets

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