Analysis of Factors Affecting the Over-Representation of Sequential Crashes in Freeway Tunnels: Using Rule-Based Data Mining Method
The paper provides an empirical analysis of road/tunnel design, traffic volume, and environmental factors associated with the increased likelihood of sequential crashes in freeway tunnels. The association rule mining and decision tree methods are employed since both of them are capable of identifyin...
Saved in:
| Main Authors: | Shun Li, Shuai Huang, Jie Wang, Shijian He |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/7128408 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Investigating patterns of freeway crashes in Jordan: Findings from a text mining approach
by: Shadi Jaradat, et al.
Published: (2025-06-01) -
Bayesian Hierarchical Modeling Monthly Crash Counts on Freeway Segments with Temporal Correlation
by: Qiang Zeng, et al.
Published: (2017-01-01) -
Using Multidimensional Data to Analyze Freeway Real-Time Traffic Crash Precursors Based on XGBoost-SHAP Algorithm
by: Jie Li, et al.
Published: (2023-01-01) -
A meta-learning approach to improving transferability for freeway traffic crash risk prediction
by: Chenlei Liao, et al.
Published: (2025-03-01) -
Predicting Freeway Traffic Crash Severity Using XGBoost-Bayesian Network Model with Consideration of Features Interaction
by: Yang Yang, et al.
Published: (2022-01-01)