Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Predicting and preventing road accidents

Prediction model providing risk scores on road accidents based on a broad dataset of road characteristics and accidents.

Last change on 23rd of August 2024, at 15:37 (CET) | Publication Standard 1.0
Publication category
Impactful algorithms
Impact assessment
Field not filled in.
Status
In development

General information

Theme

Traffic

Begin date

Field not filled in.

Contact information

datashop@denhaag.nl

Link to publication website

https://ongevalrisico.nl/

Responsible use

Goal and impact

The purpose of the model is twofold. First, to develop effective road safety policies and reduce accidents. Second, the model can be used to compare two or more designs on road safety scores in actual projects.

Citizens ultimately see road modifications and hopefully fewer accidents.

Considerations

At the time, this was the only model examining correlations between accident rates and road, intersection or environment characteristics.

Human intervention

The outcomes are advisory to weather experts. Model outcomes are never adopted 1:1. The model is a tool for prioritising road safety policies. There is therefore no automated decision-making.

Risk management

No data that can be traced back to personal level is explicitly linked. The outcomes are assessed by an expert before use.

Legal basis

This follows from the statutory duty of the road authority and the Road Traffic Act.

Operations

Data

www.ongevalrisico.nl https://docs.google.com/presentation/d/1_Kt3_mMHhjH-KZgKJxmmqlf9rlRdJr9mgaUUBcGtBDU/edit?authuser=1#slide=id.p4 Including BGT, NWB and BRON

Technical design

Algorithm is XGBoost. Validation: AUC, ROC, confusion matrix, citizens' subjective reports on road safety.

The algorithm analyses a set of roads on which accidents have occurred and a set of roads on which no accidents have occurred. The algorithm uses 'number of accidents' as target variable (classification) and tries to find differences between properties of the two sets.

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