safespeeds: safespeeds Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

safespeeds Bayesian Network

Description

Modelling driver expectations for safe speeds on freeway curves using Bayesian belief networks.

Format

A discrete Bayesian network to model driver expectations using measured speeds in 153 curves and data on the characteristics of the curve approaches. The probabilities were given in the referenced paper. The vertices are:

Angle

(A010-100, A100-200, A200-310);

CurveSign

(Present, Not Present);

Direction

(Left, Right);

ExpectedSafeSpeed

(S060-069, S070-079, S080-089, S090-099, S100-109, S110-119, S120-129, S130-140);

NumberOfLanes

(One, Two, Three, Four);

PrecedingCurveSpeed

(S060-080, S080-100, S100-120, S120-140, Tangent);

PrecedingRoadwayType

(Connector Road, Deceleration Lane, Fork, Main Carriageway, Merge, Weaving Section);

SpeedSign

(AdvSpeed50, AdvSpeed60, AdvSpeed70, AdvSpeed80, AdvSpeed90, SpeedLimit50, SpeedLimit60, SpeedLimit70, SpeedLimit80, SpeedLimit90, NoSpeedLimit);

WarningSign

(Present, Not Present);

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

References

Vos, J., Farah, H., & Hagenzieker, M. (2024). Modelling driver expectations for safe speeds on freeway curves using Bayesian belief networks. Transportation Research Interdisciplinary Perspectives, 27, 101178.

bnRep documentation built on April 12, 2025, 1:13 a.m.