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Table 2 Description of predictor variables and interaction terms included in models without (NO_MET) and with (MET) meteorological variables

From: Modeling hourly weather-related road traffic variations for different vehicle types in Germany

Variable name

Variable type

Variable description

Potential predictor variables for NO_MET

hour

Categorical (24)

Hour of the day

dow

Categorical (7)

Day of the week (public holidays are treated as Sundays)

mon

Categorical (12)

Month of the year

holiday

Categorical (2)

School holiday in the federal state of the traffic station

trend

Continuous

Linear trend in time

hour:dow

Interaction

Different diurnal cycles on different days of the week

break

Categorical (n)

\(n={2,3,4}\) segments determined by breakpoint detection (if \(n=1\) this term and its interactions are excluded)

break:trend

Interaction

Different trends in different segments

break:hour

Interaction

Different diurnal cycle in different segments

Potential predictor variables for MET

temp\(^k\)

Continuous

Daily maximum temperature at 2 m height at the ERA5 grid cell closest to the traffic station

cloud\(^k\)

Continuous

Daily mean total cloud cover at the ERA5 grid cell closest to the traffic station

wind\(^k\)

Continuous

Daily maximum wind gust at 10 m height at the ERA5 grid cell closest to the traffic station

precip\(^{1/k}\)

Continuous

Average hourly precipitation sum of all RADOLAN grid cells within a radius of 10 km around traffic station

weekend

Categorical (3)

Distinguish between working day, Saturday, and Sunday (only included in interaction terms below, but not as single variable)

weekend:temp\(^k\)

Interaction

Different relationships between temperature and traffic

weekend:precip\(^{1/k}\)

Interaction

Different relationships between precipitation and traffic

weekend:clt\(^k\)

Interaction

Different relationships between cloud cover and traffic

weekend:wind\(^k\)

Interaction

Different relationships between wind speed and traffic

  1. For categorical variables the number of categories is shown in brackets. Meteorological variables are introduced to the model selection process with different exponents k \(=\) {1,2,3,4} to allow non-linear functional relationships