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Fig 1.

The road section of us-101.

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Table 1.

Basic information of NIGSIM data.

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Table 1 Expand

Fig 2.

Vehicle braking process.

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Fig 2 Expand

Table 2.

Driving style evaluation index.

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Table 2 Expand

Fig 3.

Principal component contribution rate and cumulative contribution rate.

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Fig 3 Expand

Table 3.

Principal component score coefficient matrix.

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Table 3 Expand

Fig 4.

Relationship between cluster number and SSE.

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Fig 5.

Driving style recognition results.

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Fig 5 Expand

Table 4.

Bayesian network node variables and their discrete values.

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Table 4 Expand

Table 5.

Node variable symbol correspondence.

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Table 5 Expand

Fig 6.

DAG structure matrix.

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Fig 6 Expand

Fig 7.

Bayesian network structure diagram.

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Fig 8.

Bayesian network model after learning with Netica software parameters.

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Fig 8 Expand

Table 6.

CPT of node Sty.

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Table 6 Expand

Table 7.

Sensitivity analysis results of node Typ.

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Table 7 Expand

Fig 9.

Known network changes on rapid acceleration and deceleration.

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Fig 10.

Network changes with known risk status.

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Fig 11.

Video during normal driving time.

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Fig 12.

Video of the time of risk driving.

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Fig 13.

Vehicle operation risks in different time periods.

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