A Simultaneous Safety Analysis of Crash Frequency and Severity for Highway-Rail Grade Crossings: The Competing Risks Method

Table 1

Descriptive statistics of key variables.

Variable	Values	Frequency	Mean or percentage	Min	Max	Mode
Crash information	No crash	2835	86%
	PDO	261	8%
	Injury	147	4%
	Fatality	67	2%
Type of train service
	Freight	2855	86%
	Intercity passenger	455	14%
Train detection	None	2450	74%
	Constant warning time	438	13%
	Motion detection	42	1%
	DC	379	11%
Is commercial power available?	Yes	2202	67%
	No	1108	33%
Is roadway/pathway paved?	Yes	625	19%
	No	2685	81%
Total daylight through trains			7.26	0	35	5
Total night time through trains			6.42	0	33	4.75
Total switching trains			0.77	0	12	0.55
Maximum train speed			41.02	5	79	37
Annual average daily traffic (AADT)			360.16	5	23438	45
Percent trucks			14.06	1	22.67	15.44
Distance to nearby roadway intersection			199.28	0.775	2502	27.04
Smallest crossing angle			68.37	7.869	90	90
Number of traffic lanes			1.812	1	4	2

Note. One important influential variable, warning device type, is not included in the model mainly due to unreliable data quality: (1) historical warning device types for each crossing for 30 years are not readily available and (2) inventory data contains some quality issues and results of warning device type could not be cross-validated. This could be the reason why not many long-term studies exist in the literature and some counterintuitive countermeasure effectiveness results in the literature [72]. Moreover, the focus of the study is to demonstrate the model’s capability to model crash and severity likelihoods and its interpretive capability to provide contributors’ long-term and instantaneous effects; contributors can be easily included in the model when they become available.