Modelling the pedestrian's willingness to walk on the subway platform: A novel approach to analyze in-vehicle crowd congestion

D Huang, Y Yang, X Peng, J Huang, P Mo, Z Liu… - … research part E …, 2024 - Elsevier
A common behavior pattern observed on subway platforms is that pedestrians walk
downstairs from the escalator and choose a door to wait for a rail train. Interestingly …

A Multi-Task Network With Dynamic Segmentation for Sea Ice Classification in Arctic Shipping Route Optimization

Z Ma, J Wu, S Wang, Y Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Ice floes and icebergs pose serious risks to ship navigation in the Arctic. It is important to
identify the sea ice distribution around ships, and subsequently generate a sea ice map and …

Exploring passengers' choice of transfer city in air-to-rail intermodal travel using an interpretable ensemble machine learning approach

Y Ren, M Yang, E Chen, L Cheng, Y Yuan - Transportation, 2023 - Springer
The transfer city is a key point in air-to-rail intermodal travel (ARIT) that directly influences
the service level of the entire system. Although some studies have investigated factors that …

PaCS: A Parallel Computation Framework for Field-Based Crowd Simulation

H Zhao, T Guo, W Tong, H Yin… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Crowd simulation is a convenient method to evaluate pedestrians' status and their
corresponding management strategies in large public spaces. However, the performance of …

Exploring the heterogeneities in vehicle-involved traffic violations at intersections using latent class clustering and partial proportional odds models

Y Sun, J Lu, G Ren, J Ma - Journal of Transportation Safety & …, 2024 - Taylor & Francis
Vehicle-involved road crashes, mainly caused by traffic violations, result in major property
damage and life losses annually. Thus, it is of vital importance to clarify the heterogeneities …

Explainable Stacking-Based Learning Model for Traffic Forecasting

C Chen, J Liu, Y Li, Y Zhang - Journal of Transportation …, 2024 - ascelibrary.org
This paper implements a two-staged ensemble learning model for traffic forecasting,
focusing on the interpretability of predictions. The stacking model leverages the advantages …

A Multimodal Trajectory Prediction Method for Pedestrian Crossing Considering Pedestrian Motion State

Z Zhou, B Liu, C Yuan, P Zhang - IEEE Intelligent Transportation …, 2023 - ieeexplore.ieee.org
Predicting pedestrian crossing trajectories has become a primary task in aiding autonomous
vehicles to assess risks in pedestrian–vehicle interactions. As agile participants with …

Spatial and timeframe distribution of diverse pedestrian activities in the street network of southeast asian developing cities

S Miura, M Yoshida, F Nakamura… - Journal of Asian …, 2024 - Taylor & Francis
This research clarifies the spatial and timeframe distribution of pedestrian activities with the
demand for “place function” in the street network of central business district areas of two …

Recent Developments in Crowd Management: Theory and Applications

K Nishinari, C Feliciani, X Jia, S Tanida - Journal of Disaster …, 2024 - jstage.jst.go.jp
Managing crowds is important not only during evacuation in disasters such as earthquakes
and fires but also during normal situations. In particular, places where many people gather …

The challenges of implementing evidence-based strategies to inform building and urban design decisions: a view from current practice

A Stanitsa, SH Hallett, S Jude - Journal of Engineering, Design and …, 2022 - emerald.com
Purpose This study aims to raise awareness of the key challenges, opportunities and
priorities for evidence-based strategies' application to inform building and urban design …