A review of spatial approaches in road safety

A Ziakopoulos, G Yannis - Accident Analysis & Prevention, 2020‏ - Elsevier
Spatial analyses of crashes have been adopted in road safety for decades in order to
determine how crashes are affected by neighboring locations, how the influence of …

[HTML][HTML] Research on the big data of traditional taxi and online car-hailing: A systematic review

T Lyu, PS Wang, Y Gao, Y Wang - Journal of Traffic and Transportation …, 2021‏ - Elsevier
The purpose of this paper is to provide a summary of a quick overview of the latest
developments and unprecedented opportunities for scholars who want to set foot in the field …

A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data

J Bao, P Liu, SV Ukkusuri - Accident Analysis & Prevention, 2019‏ - Elsevier
The primary objective of this study is to investigate how the deep learning approach
contributes to citywide short-term crash risk prediction by leveraging multi-source datasets …

[HTML][HTML] Geographically weighted machine learning for modeling spatial heterogeneity in traffic crash frequency and determinants in US

S Wang, K Gao, L Zhang, B Yu, SM Easa - Accident Analysis & Prevention, 2024‏ - Elsevier
Spatial analyses of traffic crashes have drawn much interest due to the nature of the spatial
dependence and spatial heterogeneity in the crash data. This study makes the best of …

Short-term prediction of safety and operation impacts of lane changes in oscillations with empirical vehicle trajectories

M Li, Z Li, C Xu, T Liu - Accident Analysis & Prevention, 2020‏ - Elsevier
Lane changes made during traffic oscillations on freeways largely affect traffic safety and
could increase collision potentials. Predicting the impacts of lane change can help to …

Exploring topics and trends in Chinese ATC incident reports using a domain-knowledge driven topic model

J Bao, Y Chen, J Yin, X Chen, D Zhu - Journal of Air Transport …, 2023‏ - Elsevier
The primary objective of this study is to discover hidden topics and trends from historical
ATC incident reports. A novel domain-knowledge driven topic (DDT) model is proposed to …

Optimized structure learning of Bayesian Network for investigating causation of vehicles' on-road crashes

T Chen, YD Wong, X Shi, X Wang - Reliability Engineering & System Safety, 2022‏ - Elsevier
A vehicle's crash can be seen as a failure of microscopic road transportation system. The
causal investigation of vehicles' crashes has drawn much attention from academia and …

Topic analysis of Road safety inspections using latent dirichlet allocation: A case study of roadside safety in Irish main roads

C Roque, JL Cardoso, T Connell, G Schermers… - Accident Analysis & …, 2019‏ - Elsevier
Abstract Under the Safe System framework, Road Authorities have a responsibility to deliver
inherently safe roads and streets. Addressing this problem depends on knowledge of the …

[HTML][HTML] A novel framework for crash frequency prediction: Geographic support vector regression based on agent-based activity models in Greater Melbourne

Q Duong, H Gilbert, H Nguyen - Accident Analysis & Prevention, 2024‏ - Elsevier
The field of spatial analysis in traffic crash studies can often enhance predictive performance
by addressing the inherent spatial dependence and heterogeneity in crash data. This …

Spatial analysis of moving-vehicle crashes and fixed-object crashes based on multi-scale geographically weighted regression

X Tang, R Bi, Z Wang - Accident Analysis & Prevention, 2023‏ - Elsevier
Previous researches have demonstrated that traffic crashes in urban areas are geographical
events and strongly linked to local characteristics such as road network and land attributes …