A latent class modelling approach for identifying vehicle driver injury severity factors at highway-railway crossings

TABLE 4: LSOL II model Elasticity Effects

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TABLE 4: LSOL II model Elasticity Effects

Variables	No Injury	Severe Injury	Fatal Injury
Crossing Characteristics
Total No. of trains through the crossing	0.1	-0.1	-0.1
Roadway classification
Rural Local highway	4.2	-6.7	-7.1
Rural Minor Collector	4.6	-7.4	-7.5
Urban Minor Arterial	3.9	-6.3	-6.4
Urban Collector	6.5	-10.4	-10.5
Urban Local highway	5.5	-8.8	-8.8
Pavement Markings
Stop sign	7.6	-12.1	-12.3
Obstacles to road drivers near the crossing
Permanent structure	-11.6	18.5	19.5
Posted Train Speed for the crossing
Maximum	-0.1	0.1	0.1
Minimum	0.1	-0.2	-0.2
Crossing Safety Equipment
Type of Warning Device present
Cantilever flashing light signals	-2.9	4.6	4.7
Stop sign	2.8	-4.4	-4.5
Crossbucks	-4.6	7.4	7.6
Gates	16.3	-24.9	-29.6
Driver Demographics
Male	4.4	-5.9	-10.1
Age	-0.3	0.3	1.2
Occupancy of the roadway vehicle involved in the crash	-7.6	9.9	18.7
Vehicle Characteristics
Vehicle type
Van	1.0	0.1	-6.2
Environmental Factors
Time period of the day
12 AM to 6 AM	3.7	-13.5	14.1
7 PM to 12 AM	1.5	-7.1	10.0
Temperature
33 F – 60 F	4.0	-5.5	-9.0
> 60 F	2.1	-2.8	-4.7
Weather conditions
Rain	3.0	-4.1	-6.6
Snow	13.1	-13.4	-41.9
Crash Characteristics
Role of vehicle in the crash
Struck by the train	-8.5	10.7	21.3
Motorist action at the event of a crash
Drove around or through the gate	-11.6	8.6	45.7
Motorist stopped on the crossing	33.0	-44.5	-76.2
Motorist did not stop	6.3	-5.4	-22.7
Estimated Train Speed	-1.2	1.0	4.6

1 The reader will note that we chose to employ BIC because it imposes substantially higher penalty on over-fitting with excess parameters compared to the penalty imposed by Alkaike Information Criterion (AIC). AIC is defined as − 2ln(L) + 2K.

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