Urban Intersection Safety: An Engineering Assessment of Crash Risk, Geometric and Operational Factors, and Improvement Strategies

Urban intersections are the single largest source of conflict, delay, and crash risk in city road networks because they concentrate crossing, merging, and diverging vehicle movements, together with pedestrians and non-motorised traffic, into a small area. This paper presents an engineering assessment framework for urban intersection safety that combines (i) a structured literature review of crash-based and surrogate-safety-measure (SSM) approaches, (ii) a field-oriented methodology covering traffic volume counts, geometric inventory, conflict observation, and Post Encroachment Time (PET) analysis, and (iii) an valuation procedure for comparing candidate improvement scenarios such as channelisation, signalisation, and roundabout conversion using delay and Level of Service (LOS) as decision criteria. Representative (illustrative) data plots and comparison tables are presented to demonstrate how the framework outputs support a hazard ranking and prioritisation of low-cost engineering countermeasures. The paper is intended as a template methodology that a student or practising engineer can populate with primary data collected from an actual study intersection. The discussion synthesises recurring findings across the reviewed literature — the disproportionate severity of right-angle and pedestrian-involved crashes at unsignalized junctions, the safety trade-offs of alternative intersection forms (roundabouts, median U-turns, displaced left turns), and the growing role of video-based and UAV-based conflict analysis and machine-learning crash prediction. The paper closes with the limitations of the present treatment and a future scope outlining connected-vehicle, digital-twin, and AI-based directions for proactive intersection safety management.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-09
DOI
https://doi.org/10.5281/zenodo.22672768
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
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article

Urban Intersection Safety: An Engineering Assessment of Crash Risk, Geometric and Operational Factors, and Improvement Strategies

Preetam Bharatesh Karnawadi
Zenodo (CERN European Organization for Nuclear Research)
Traffic and Road Safety
article

Urban Intersection Safety: An Engineering Assessment of Crash Risk, Geometric and Operational Factors, and Improvement Strategies

Preetam Bharatesh Karnawadi
article en

Abstract

Urban intersections are the single largest source of conflict, delay, and crash risk in city road networks because they concentrate crossing, merging, and diverging vehicle movements, together with pedestrians and non-motorised traffic, into a small area. This paper presents an engineering assessment framework for urban intersection safety that combines (i) a structured literature review of crash-based and surrogate-safety-measure (SSM) approaches, (ii) a field-oriented methodology covering traffic volume counts, geometric inventory, conflict observation, and Post Encroachment Time (PET) analysis, and (iii) an valuation procedure for comparing candidate improvement scenarios such as channelisation, signalisation, and roundabout conversion using delay and Level of Service (LOS) as decision criteria. Representative (illustrative) data plots and comparison tables are presented to demonstrate how the framework outputs support a hazard ranking and prioritisation of low-cost engineering countermeasures. The paper is intended as a template methodology that a student or practising engineer can populate with primary data collected from an actual study intersection. The discussion synthesises recurring findings across the reviewed literature — the disproportionate severity of right-angle and pedestrian-involved crashes at unsignalized junctions, the safety trade-offs of alternative intersection forms (roundabouts, median U-turns, displaced left turns), and the growing role of video-based and UAV-based conflict analysis and machine-learning crash prediction. The paper closes with the limitations of the present treatment and a future scope outlining connected-vehicle, digital-twin, and AI-based directions for proactive intersection safety management.

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 11%
Traffic and Road Safety
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