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Design Example: Alignment of a Road Line Using GIS01:17

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Advancing road safety strategy development: A data-driven multi-objective optimisation integrated approach.

Bosong Jiao1, Harry Evdorides1

  • 1School of Engineering, University of Birmingham, Edgbaston, Birmingham, B15 2TT, United Kingdom.

Heliyon
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This study presents a novel model for road infrastructure management, integrating multi-objective optimization and association rule mining to improve decision-making and resource allocation for enhanced road safety.

Keywords:
Data-drivenResource allocationRoad safetyStrategic management

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Area of Science:

  • Road Safety Engineering
  • Transportation Management
  • Data Mining

Background:

  • Road traffic accidents are a major global health issue, causing over 1.19 million fatalities in 2021.
  • Current road safety strategies often depend on subjective expert opinions.
  • There is a need for systematic, data-driven approaches to optimize road infrastructure management.

Purpose of the Study:

  • To introduce an adaptive two-stage model for road infrastructure management.
  • To minimize expert interference in decision-making processes.
  • To enhance the efficiency of resource allocation for road safety.

Main Methods:

  • Integration of multi-objective optimization with association rule mining.
  • Utilizing the non-dominant sorting genetic algorithm (NSGA-II).
  • Employing crash database mining for tailored investment plans.

Main Results:

  • The model demonstrated significant improvements across various objectives in a Utrecht case study.
  • It enables road authorities to customize investment plans based on specific network characteristics.
  • The approach provides a systematic framework for adaptive decision-making.

Conclusions:

  • The novel model offers a systematic framework for optimizing road infrastructure management and resource allocation.
  • Further refinement is needed to account for interactive effects of road attributes in risk assessment.
  • The approach represents a substantial advancement in data-driven road safety strategies.