Resource Allocation Procedure
In lieu of the economic analysis procedures described above, USDOT has developed a resource allocation procedure for highway-rail crossing improvements. The FRA’s User’s Guide, Rail-Highway Crossing Resource Allocation Procedure, Third Edition (1987), can be accessed here: https://www.fra.dot.gov/Elib/Document/1537 . This procedure was developed to assist States and railroads in determining the effective allocation of federal funds for crossing traffic control improvements. 132The resource allocation model is designed to provide an initial list of crossing traffic control improvements that would result in the greatest collision reduction benefits based on cost ‑ effectiveness considerations for a given budget. As designed, the results are checked by a diagnostic team in the field and revised as necessary. It should be noted that the procedure considers only traffic control improvement alternatives as described below:
•For passive crossings, single track, two upgrade options exist: flashing ‑lights or gates
•For passive, multiple-track crossings, the model allows only the gate option to be considered in accordance with the Federal-Aid Policy Guide
•For flashing ‑light crossings, the only improvement option is gates Other improvement alternatives, such as removal of site obstructions, crossing surface improvements, illumination, and train detection circuitry improvements, are not considered in the resource allocation procedure. The input data required for the procedure consists of the number of predicted collisions, the safety effectiveness of flashing ‑lights and automatic gates, improvement costs, and the amount of available funding.The number of annual predicted collisions can be derived from the USDOT Accident Prediction Model or from any model that yields the number of annual collisions per crossing. Safety effectiveness studies for the equipment used in the resource allocation procedure have been completed by USDOT, the California Public Utilities Commission, and William J. Hedley. Effectiveness factors are the percent reduction in collisions occurring after the implementation of the improvement. The model requires data on the costs of the improvement alternatives. Life-cycle costs of the devices should be used, such as both installation and maintenance costs. Costs used in the resource allocation procedure are usually developed for each of the following three alternatives, as applicable:
•Passive devices to flashing ‑lights1
•Passive devices to automatic gates
•Flashing-lights to gates Caution should be exercised in developing specific costs for a few selected projects while assigning average costs to all other projects. If this is done, decisions regarding the adjusted crossings may be unreasonably biased by the algorithm. The amount of funds available for implementing crossing signal projects is the fourth input for the resource allocation procedure are at multiple track crossings. The discussion which follows assumes that a group of crossings, some of which are at single- track sections and others where there are two or more tracks are being evaluated and that some 1 Practitioners are cautioned to determine whether use of flashing lights without g ates is appropriate for such locations; refer to the Technical Working Group guidance in this section. 133crossings are passive whereas others have flashing ‑lights but no gates. The goal of the analysis is to prioritize crossings for improvement based upon cost-effectiveness, as explained further below. If, for example, a single-track passive crossing is considered, it could be upgraded with either flashing ‑lights, with an effectiveness of E1, or gates, with an effectiveness of E2. The number of predicted collisions at crossing “i” is Ai. Therefore, the reduced accidents per year is AiE1 for the flashing ‑light option and AiE2 for the gate option. The corresponding costs for these two improvements are C1 and C2. The accident reduction/cost ratios for these improvements are AiE1/C1 for flashing ‑lights and AiE2/C2 for gates. The rate of increase in accident reduction versus costs that results from changing an initial decision to install flashing ‑lights with a decision to install gates at the crossing is referred to as the incremental accident reduction/cost ratio and is equal to: If, on the other hand, the crossing was a passive crossing in multiple-track territory, then improvements to flashing ‑lights would not be an option. In this scenario, the upgrade from passive to gates would result in an effectiveness of E2, a cost of C2, and an accident reduction/ cost ratio of AiE2/C2. If this multi ‑track crossing was originally a flashing ‑light crossing, the improvement from flashing ‑lights to gates would be characterized with an effectiveness of E3, a cost of C3, and an accident reduction/cost ratio of AiE3/C3. The individual accident reduction/cost ratios associated with these improvements are selected by the algorithm in an efficient manner to produce the maximum accident reduction that can be obtained for a predetermined total cost. This total cost is the sum of an integral number of equipment costs (C 1, C2, and C). The total maximum accident reduction is the sum of the individual accident reductions of the form AxE. The USDOT Rail-Highway Crossing Resource Allocation Procedure, as described in the Rail- Highway Crossing Resource Allocation Procedure’ s Guide, Third Edition , August 1987, DOT/ FRA/OS -87/10, uses three “normalizing constants” in the accident prediction formula.(45) These constants need to be adjusted periodically to keep the procedure matched with the current accident trends, the current number of open public at-grade crossings, and the changes in the warning devices. For the most recently calculated 2013 normalizing constants, the collision data that was used was for calendar years 2007–2011 (to predict 2012 accidents/incidents). The process of determining the three new normalizing constants for 2013 was performed such that the sum of the 2012 accident prediction values of all open public at-grade crossings in the National Highway Rail Crossing Inventory data that was used was made to equal the sum of the observed number of collisions. Note that while mismatched data records between accident/inventory reporting are included, those accidents which occurred prior to the date of a warning device change are excluded, and also excluded are accidents which occurred at closed crossings and nonpublic at-grade crossings as included in the Inventory data used. This process was performed for each of the respective formulae for the three types of warning device categories: passive, flashing ‑lights, and gates. This process normalizes the calculated predictions for the current trend in collision data for each category and relative to each of the three types of warning device categories (see Table 8). 134Table 8. Collision Prediction and Resource Allocation Procedure Normalizing Constants
Warning
Device
GroupsNew* Prior years 2013 2010 2007 2005 2003 1998 1992 1990 1988 1986 Passive 0.5086 0.4613 0.6768 0.6407 0.6500 0.7159 0.8239 0.9417 0.8778 0.8644 Flashing-lights0.3106 0.2918 0.4605 0.5233 0.5001 0.5292 0.6935 0.8345 0.8013 0.8887 Gates 0.4846 0.4614 0.6039 0.6513 0.5725 0.4921 0.6714 0.8901 0.8911 0.8131 Source: Federal Railroad Administration website (http://safetydata.fra.dot.gov/officeofsafety/default.aspx ). The most current Normalizing Constants are used in FRA’s Web Accident Prediction System (WBAPS), on the FRA Safety Data website. Practitioners are encouraged to access this system which can provide the risk reduction factors based upon data in the USDOT grade crossing database.(46) If the resource allocation procedure is used to identify high-hazard crossings, a field diagnostic team should investigate each selected crossing for accuracy of the input data and reasonableness of the recommended solution. A worksheet for performing this analysis is included in Figure 61 (or download from this link https://safety.fhwa.dot.gov/hsip/xings/com_ roaduser/07010/sec05form3.pdf ). This worksheet also includes a method for manually evaluating or revising the results of the computer model. 135Figure 61. Resource Allocation Procedure Field Verification Worksheet Source: Federal Highway Administration website .