Research Article

Road Rescue Demand Prediction for the Improvement of Traffic System Resilience

Table 2

The coefficients of the road rescue demand prediction models.

CoefficientsSubmodels with groupingModel without grouping
Submodel 1Submodel 2Submodel 3Submodel 4Submodel 5Submodel 6Submodel 7Submodel 8Submodel 9

Constant−1693181859122025−358361−136743−199345−195245−70642−212155−171190
Year84.120.00−60.35179.6767.9298.9897.2135.20105.2685.00
Month4.36−119.65117.87−156.6723.3217.9732.5033.0323.6517.38
Week1.6721.78−15.88−44.00−0.64−2.11−3.31−17.47−3.34−3.16
Three-day holiday−43.450.000.000.000.000.000.000.000.00−19.90
National Day0.00−14.490.000.000.000.000.000.000.00−20.97
Spring Festival0.000.00−22.810.000.000.000.000.000.00−20.91
Snow1.860.000.00−344.000.000.000.000.000.000.57
Rain−5.22−33.070.000.009.50−31.37−9.17−6.470.00−5.60
Low temperature 0°C−10.420.000.000.000.000.000.000.000.00−20.73
High temperature 32°C1.120.000.000.000.000.00−15.113.370.001.69
Precipitation on the previous day4.950.000.000.0029.720.0020.04−146.0469.3321.31
The highest temperature4.53−23.11−12.70−33.670.00−7.790.000.005.01−0.35
The lowest temperature−1.3412.92−11.6656.000.00−8.710.000.00−0.276.69
R20.7770.9790.77010.4710.7630.2980.3340.7180.717