Traffic flow behavior at un-signalized intersection with crossings pedestrians

Khallouk, A.; Echab, H.; Ez‐Zahraouy, H.; Lakouari, N.

doi:10.1016/j.physleta.2017.12.006

Cited by 15 publications

(4 citation statements)

References 23 publications

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“…It was found that most vehicles accelerate prematurely before entering the crosswalk, significantly reducing their speed as they approach pedestrians, but suddenly accelerate before reaching the closest distance (Noh et al, 2021). Later, microsimulation techniques such as cellular automata (Khallouk et al, 2018, Layegh et al, 2020 and driving simulators (Fisher andGaray-Vega, 2012, Hoekstra-Atwood et al, 2019) have also been used to study the interaction behavior between pedestrians and vehicles in mixed traffic environments.…”

Section: Relevant Work 21 Empirical Analysis Of Pedestrian-vehicle In...mentioning

confidence: 99%

“…Therefore, at unsignalized crosswalks where there is no traffic control, the phenomenon of pedestrians and motor vehicles competing for right of way is common, and the intricate interactive mechanisms involved are complex. The decision-making of pedestrians in crossing the street is usually determined by the distance between motor vehicles and the crosswalk, but also by factors such as the safe distance for pedestrians to stand and the time required for waiting (Li et al, 2013, Khallouk et al, 2018. The driving behavior of motor vehicles is mainly determined by factors such as the speed of pedestrians, the distance to the conflict point, and other factors (Obeid et al, 2017, Noh et al, 2021.…”

Section: Introductionmentioning

confidence: 99%

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Investigating the Critical Characteristics of Pedestrian-Vehicle Game Modes at Unsignalized Crosswalks: Based on MCMC and BP Network

Yang,

Xie,

Yuan

et al. 2023

Preprint

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There is weak traffic control at unsignalized crosswalks, and the operation of pedestrians and motor vehicles is based on their recognition of the surrounding road conditions, environment, and degree of danger. This is fundamentally a game process of mutual compliance and obstacles. Currently, there is still insufficient understanding of the characteristics and mechanisms of this game behavior. In this paper, a large number of human-vehicle interaction examples in the non-signaled pedestrian crossing are collected by UAV to analyze the pedestrian-vehicle interaction mode, and a comprehensive index called Pedestrian-Vehicle Game Index (PVGI) that depicts the pedestrian-vehicle game process considering the change of motion state is proposed. Then, the Markov-chain Monte Carlo (MCMC)has been used to identify the critical conditions for game modes. Additionally, a BN model based on the Gaussian Mixture Model (GMM) and the Expectation-Maximum algorithm (EM) algorithm is applied to model and analyze multiple games between pedestrians and vehicles. The results show that pedestrian-vehicle interaction includes 11 typical game modes in 3 categories, and there are significant differences in each interaction mode. MCMC identified the PVGI domain of the pedestrian-vehicle as [-4.0s, 2.0s]. In this game interval, the game mode will be divided into "pedestrian yield - vehicle dominant" and " vehicle yield - pedestrian dominant ", with corresponding game intervals of [-4.0, 0] and [0, 2.0]. The Naive Bayes (NB) model for second-round game recognition based on the EM algorithm and GMM model performs better, with a total accuracy of 83.78%.

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Section: Relevant Work 21 Empirical Analysis Of Pedestrian-vehicle In...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Investigating the Critical Characteristics of Pedestrian-Vehicle Game Modes at Unsignalized Crosswalks: Based on MCMC and BP Network

Yang,

Xie,

Yuan

et al. 2023

Preprint

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“…These have necessitated regulating and managing vehicles to have an adequate traffic flow. However, traffic congestion is inevitable, but can be minimized to the barest level, and for a smart city to become livable, it is necessary to couple the general activities with smoother and sustainable transportation systems; these systems can be supported by cooperating with Intelligent Transportation Systems [13].…”

Section: Introduction 1background Of the Studymentioning

confidence: 99%

Sustainable Traffic Management for Smart Cities Using Internet-of-Things-Oriented Intelligent Transportation Systems (ITS): Challenges and Recommendations

et al. 2023

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The emergence of smart cities has addressed many critical challenges associated with conventional urbanization worldwide. However, sustainable traffic management in smart cities has received less attention from researchers due to its complex and heterogeneous nature, which directly affects smart cities’ transportation systems. The study aimed at addressing traffic-related issues in smart cities by focusing on establishing a sustainable framework based on the Internet of Things (IoT) and Intelligent Transportation System (ITS) applications. To sustain the management of traffic in smart cities, which is composed of a hybridized stream of human-driven vehicles (HDV) and connected automated vehicles (CAV), a dual approach was employed by considering traffic as either modeling- and analysis-based, or/and the decision-making issues of previous research works. Moreover, the two techniques utilized real-time traffic data, and collected vehicle and road users’ information using AI sensors and ITS-based devices. These data can be processed and transmitted using machine learning algorithms and cloud computing for traffic management, traffic decision-making policies, and documentation for future use. The proposed framework suggests that deploying such systems in smart cities’ transportation could play a significant role in predicting traffic outcomes, traffic forecasting, traffic decongestion, minimizing road users’ lost hours, suggesting alternative routes, and simplifying urban transportation activities for urban dwellers. Also, the proposed integrated framework adopted can address issues related to pollution in smart cities by promoting public transportation and advocating low-carbon emission zones. By implementing these solutions, smart cities can achieve sustainable traffic management and reduce their carbon footprint, making them livable and environmentally friendly.

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“…The definition of traffic flow is a system used to describe the interacting vehicles of which the feature is self-driven and many-particle. [1] Carfollowing theory, which can explain the complex phenomena of traffic flow such as critical phase transitions, [2][3][4][5][6][7][8][9][10][11][12][13][14][15] is indispensable in microscopic traffic modeling.…”

Section: Introductionmentioning

confidence: 99%

Solid angle car following model*

Ma¹,

Han²,

Jin³

2020

Chinese Phys. B

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Existing traffic flow models give little consideration on vehicle sizes. We introduce the solid angle into car-following theory, taking the driver’s perception of the leading vehicle’s size into account. The solid angle and its change rate are applied as inputs to the novel model. A nonlinear stability analysis is performed to analyze the asymmetry of the model and the size effect of the leading vehicle, and the modified Korteweg–de Vries equation is derived. The solid angle model can explain complex traffic characteristics and provide an important basis for modeling nonlinear traffic phenomena.

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Traffic flow behavior at un-signalized intersection with crossings pedestrians

Cited by 15 publications

References 23 publications

Investigating the Critical Characteristics of Pedestrian-Vehicle Game Modes at Unsignalized Crosswalks: Based on MCMC and BP Network

Investigating the Critical Characteristics of Pedestrian-Vehicle Game Modes at Unsignalized Crosswalks: Based on MCMC and BP Network

Sustainable Traffic Management for Smart Cities Using Internet-of-Things-Oriented Intelligent Transportation Systems (ITS): Challenges and Recommendations

Solid angle car following model*

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