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Updated: Mar 11, 2026
16:14
Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
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The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach
Qiang Guo1, Pengpeng Xu2, Xin Pei1
1Department of Automation, Tsinghua University, Beijing, 100084, China.
Accident; Analysis and Prevention
|November 29, 2016
Summary
Road network patterns significantly impact pedestrian safety. Irregular networks are safest, while grid patterns pose the highest risk for pedestrian-vehicle crashes, highlighting the need for spatial analysis in safety studies.
Area of Science:
- Urban planning
- Transportation engineering
- Public health
Background:
- Pedestrian safety is a critical public health issue.
- Previous studies examined crash variables but overlooked road network patterns.
- The relationship between road network topology and pedestrian crashes is not well understood.
Purpose of the Study:
- To investigate the influence of road network patterns on pedestrian-vehicle crashes.
- To quantify road network topology using a global integration index from space syntax.
- To model crash data using Bayesian Poisson-lognormal models with spatial correlation.
Main Methods:
- Utilized space syntax to calculate a global integration index for road networks.
- Developed Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) priors.
- Employed three proximity structures: contiguity, geometry-centroid distance, and road network connectivity.
- Compared CAR models with a non-spatial PLN model using Hong Kong crash data.
Main Results:
- Higher global integration in road networks correlated with increased pedestrian-vehicle crashes.
- Irregular road network patterns were associated with lower pedestrian crash occurrences.
- Grid-patterned networks showed the highest risk for pedestrian crashes.
- The CAR model incorporating road network connectivity demonstrated superior model fit.
Conclusions:
- Road network design significantly influences pedestrian safety.
- Irregular and less integrated road networks appear safer for pedestrians.
- Accounting for spatial correlation is crucial for accurate crash data modeling.
- Findings can inform urban planning and traffic safety interventions.
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