Simulating Pedestrian Movement

Puusepp, Renee; Lõoke, Taavi; Cerrone, Damiano; Männigo, Kristjan

doi:10.1007/978-981-10-6611-5_46

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…On the basis of Open Street Map data, the network of lines is created, which determines the shortest paths. By contrast, Puusepp et al 32 underline that it is difficult to reduce pedestrian traffic to a network of paths as represented in graph-based approaches because human walking behavior can be much more unpredictable.…”

Section: Literature Review: Agent-based Modeling Applied In An Outdoo...mentioning

confidence: 99%

From dawn to dusk: daily fluctuations in pedestrian traffic in the city center

Wozniak

2023

SIMULATION

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Pedestrian traffic in a city is subject to fluctuations throughout the day due to a variety of factors. The understanding of these variations can be achieved using properly calibrated agent-based simulation models that capture the dynamics of pedestrian movement. However, despite their significance, such models are currently underrepresented in scientific discussions. In addition, acquiring real-world pedestrian localization data for model calibration poses challenges. To address these issues, this paper presents an agent-based model specifically designed to examine pedestrian traffic fluctuations at a mesoscale level. The model uses popular times data from the Google Places service and population data from the Geographic Information System (GIS) for accurate calibration. As a result, it effectively captures the real-world dynamics of pedestrian movement in the city center. By harnessing the advantages of agent-based modeling (ABM), the model generates several valuable insights into daily pedestrian traffic. It estimates the capacity and speed of pedestrian flows and determines the daily load within the simulated area. Moreover, it enables the identification of bottlenecks and areas characterized by varying levels of pedestrian density. The model’s validation process involves comparing its output with empirical studies and pedestrian traffic data from selected points of interest (POIs). The model successfully captures key aspects associated with fundamental diagrams of pedestrian flow. Furthermore, the dynamics of pedestrians closely align with Google Places popular times data for the chosen POIs. Overall, this research contributes to advancing pedestrian traffic management and optimizing public transport organization by employing empirically calibrated agent-based simulation models.

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Section: Literature Review: Agent-based Modeling Applied In An Outdoo...mentioning

confidence: 99%

From dawn to dusk: daily fluctuations in pedestrian traffic in the city center

Wozniak

2023

SIMULATION

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“…A key benefit of agent-based models is that they allow simulated agents to react to each other, capturing the effects of queuing, overcrowding and other forms of person-to-person interactions that cannot be captured in network-based models. Yet, agent-based pedestrian models have focused less on capturing route utilities that are central to transportation models, and instead typically used the visual environment around agents to guide navigation(Puusepp et al 2017).Agent-based navigation models have more recently also been combined with machine-learning approaches to improve their predictive capacity(Liebig et al 2012; Tribby et al 2012).…”

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confidence: 99%

Predicting pedestrian flow along city streets: A comparison of route choice estimation approaches in downtown San Francisco

Sevtsuk

Kalvo

2021

International Journal of Sustainable Transportation

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Street attributes are thought to play an important role in influencing pedestrian route choices. Faced with alternatives, pedestrians have been observed to choose faster, safer, more comfortable, more interesting or more beautiful routes. Literature on pedestrian route choice has provided methods for assessing the likelihood of such options using discrete choice models. However, route choice estimation, which is data intensive and computationally challenging, remains infrequently deployed in planning mobility analysis practice. Even when coefficients from previous studies are available, operationalizing them in foot-traffic predictions has been rare due to uncertainty involved in the transferability of behavioral effects from one context to another, as well as computational challenges of predicting route choice with custom attributes. This paper explores a simpler method of route choice prediction, implemented in the Urban Network Analysis toolbox, which assigns probabilities to available route options based on distance alone. We compare the accuracy of distance-weighted approaches to the more detailed utility-weighted approach using a large dataset of observed GPS pedestrian traces that include numerous trips between same intersections pairs in downtown San Francisco as a benchmark. Even though a utility-weighted model matches observed pedestrian flows most accurately, a distance-weighted model is only marginally inferior, on average. However, shortest-distance and highest-utility route predictions are both significantly inferior to the utility-weighted and distance-weighted sample-enumeration methods. Our findings suggest that simplified assumptions can be used to predict pedestrian flow in practice with existing software, opening pedestrian flow predictions to a wider range of planning and transportation applications.

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Detecting indicators of futurity urban planning by comparing them with analyzing ancient Ur city to fulfillment sustainable new city

Altimimy

2024

AIP Conference Proceedings

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Simulating Pedestrian Movement

Cited by 4 publications

References 3 publications

From dawn to dusk: daily fluctuations in pedestrian traffic in the city center

From dawn to dusk: daily fluctuations in pedestrian traffic in the city center

Predicting pedestrian flow along city streets: A comparison of route choice estimation approaches in downtown San Francisco

Detecting indicators of futurity urban planning by comparing them with analyzing ancient Ur city to fulfillment sustainable new city

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