Evaluating the conflicts between vehicles and pedestrians

Ganichev, Alexander; Batishcheva, Oksana

doi:10.1016/j.trpro.2020.10.018

Cited by 12 publications

(4 citation statements)

References 24 publications

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“…Finally, the relative position (d t ij ) between the pedestrian and the vehicle is then calculated. Equations ( 3) and ( 4) are used to calculate the relative position using the x and y coordinates and the heading angle θ, as shown in Equation (8).…”

Section: Vehicle-pedestrian Interaction (Vpi) Feature Extractionmentioning

confidence: 99%

“…It is not surprising that pedestrian conflicts with vehicles are most problematic in urban areas, since pedestrian activity is higher there. The problem of collisions between vehicles and pedestrians has been the subject of deep study for a long time [5][6][7][8][9][10][11][12]. The meaning of traffic conflict varies among research publications.…”

Section: Introductionmentioning

confidence: 99%

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Holistic Spatio-Temporal Graph Attention for Trajectory Prediction in Vehicle–Pedestrian Interactions

Alghodhaifi,

Lakshmanan

2023

Sensors

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Ensuring that intelligent vehicles do not cause fatal collisions remains a persistent challenge due to pedestrians’ unpredictable movements and behavior. The potential for risky situations or collisions arising from even minor misunderstandings in vehicle–pedestrian interactions is a cause for great concern. Considerable research has been dedicated to the advancement of predictive models for pedestrian behavior through trajectory prediction, as well as the exploration of the intricate dynamics of vehicle–pedestrian interactions. However, it is important to note that these studies have certain limitations. In this paper, we propose a novel graph-based trajectory prediction model for vehicle–pedestrian interactions called Holistic Spatio-Temporal Graph Attention (HSTGA) to address these limitations. HSTGA first extracts vehicle–pedestrian interaction spatial features using a multi-layer perceptron (MLP) sub-network and max pooling. Then, the vehicle–pedestrian interaction features are aggregated with the spatial features of pedestrians and vehicles to be fed into the LSTM. The LSTM is modified to learn the vehicle–pedestrian interactions adaptively. Moreover, HSTGA models temporal interactions using an additional LSTM. Then, it models the spatial interactions among pedestrians and between pedestrians and vehicles using graph attention networks (GATs) to combine the hidden states of the LSTMs. We evaluate the performance of HSTGA on three different scenario datasets, including complex unsignalized roundabouts with no crosswalks and unsignalized intersections. The results show that HSTGA outperforms several state-of-the-art methods in predicting linear, curvilinear, and piece-wise linear trajectories of vehicles and pedestrians. Our approach provides a more comprehensive understanding of social interactions, enabling more accurate trajectory prediction for safe vehicle navigation.

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Section: Vehicle-pedestrian Interaction (Vpi) Feature Extractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Holistic Spatio-Temporal Graph Attention for Trajectory Prediction in Vehicle–Pedestrian Interactions

Alghodhaifi,

Lakshmanan

2023

Sensors

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“…Point B's landscape type, of single-family residences with local access to the lots, brought all evaluation units maximum rating, while A, C and D are concentrated at lower level, with streets that are more important for the neighborhood traffic. Pedestrian feelings of insecurity are caused by conflict with vehicle flow, which makes it more difficult to occupy the public space(Ganichev & Batishcheva, 2020).…”

mentioning

confidence: 99%

Unveiling Dynamics of Contemporary Cities: The Influences of Urban Form on the Potential for the Socio-Spatial Vitality of Streets

Siqueira Lima,

Antunes Hardt,

Hardt

2024

GJHSS

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Starting from the assertion that vitality can be promoted by morphological elements, the article focuses on the significance of understanding these relationships for the urban security. The research aims to develop an original methodological essay in different scalar approaches of the Cidade Industrial de Curitiba (CIC) neighborhood in the state capital of Paraná, Brazil. The study began with spatial syntax on a macroscale (CIC) associating road axes integration with crime spots, resulting in the selection of four analysis points on the microscale (street). The integration of these two scales as a unique feature of the study. Considering the lot frontage as a unit of evaluation for interpreting characteristics of public spaces, private areas, temporary conditions, and nighttime scenarios, the answers to the investigative question indicate similar behavior for the parameters of the two latter themes. At the same time, significant connections with criminal activities are found only for the second subject. This result is primarily conditioned by the existence of elements that do not generate vitalized places and are not attractive to the attention of offenders. In conclusion, the guiding hypothesis that certain variables for vitality have more relevant relationships between landscape and security is confirmed. The practical implications of this confirmation have real-world applications in structuring integrated policies for urban planning and security measures in contemporary cities.

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“…i.e., it is determined by a set (n − 1) of independent values. Every possible complete set of ES distributions corresponds to a distribution field presented as a rectangular hypertetrahedron in dimensional space (m − 1) [21,[53][54][55]. In the Cartesian coordinate system (c 1 , c 2 .…”

mentioning

confidence: 99%

Analytical Model for Information Flow Management in Intelligent Transport Systems

Terentyev,

Marusin,

Evtyukov

et al. 2023

Mathematics

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The performance of this study involves the use of the zoning method based on the principle of the hierarchical relationship between probabilities. This paper proposes an analytical model allowing for the design of information and analysis platforms in intelligent transport systems. The proposed model uses a synthesis of methods for managing complex systems’ structural dynamics and solves the problem of achieving the optimal balance between the information situations existing for the object and the subject under analysis. A series of principles are formulated that govern the mathematical modeling of information and analysis platforms. Specifically, these include the use of an object-oriented approach to forming the information space of possible decisions and the division into levels and subsystems based on the principles of technology homogeneity and information state heterogeneity. Using the proposed approach, an information and analysis platform is developed for sustainable transportation system management, that allows for the objective, multivariate forecasting-based record of changes in the system’s variables over time for a particular process, and where decision-making simulation models can be adjusted in relation to a particular process based on an information situation existing for a particular process within a complex transport system. The study demonstrates a mathematical model that solves the optimal balance problem in organizationally and technically complex management systems and is based on vector optimization techniques for the most optimal decision-making management. The analysis involves classical mathematical functions with an unlimited number of variables including traffic volume, cargo turnover, safety status, environmental performance, and related variables associated with the movement of objects within a transport network. The study has produced a routing protocol prescribing the optimal vehicle trajectories within an organizationally and technically complex system exposed to a substantial number of external factors of uncertain nature.

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Evaluating the conflicts between vehicles and pedestrians

Cited by 12 publications

References 24 publications

Holistic Spatio-Temporal Graph Attention for Trajectory Prediction in Vehicle–Pedestrian Interactions

Holistic Spatio-Temporal Graph Attention for Trajectory Prediction in Vehicle–Pedestrian Interactions

Unveiling Dynamics of Contemporary Cities: The Influences of Urban Form on the Potential for the Socio-Spatial Vitality of Streets

Analytical Model for Information Flow Management in Intelligent Transport Systems

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