Assessment of Fuel Economy Technologies for Medium and Heavy ...

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or non-existent. One exception is that some regulations may lead to the use of technologies that add modestly to the weight of the vehicle, which will modestly reduce cargo capacity on a weight basis. This will only be an issue for shipments that ―weigh out‖ (i.e., are limited by the maximum load allowed), and not those that ―cube out‖ (i.e., are limited by volume). It is also conceivable that some truck purchasers might purchase smaller engines due to the higher cost of meeting more stringent fuel economy standards. If this is the case, the purchaser has still determined that the reduced performance will not be a significant detriment to their ability to conduct business, and therefore, by definition, there is no significant impact to shippers or to the overall economy. (vi) Congestion Impacts Key Question: If regulations reduce truck performance and/or reduce or increase truck VMT, what are the potential implications for congestion Background: Section (ii) describes how the demand for long-haul trucking could increase if fuel economy regulations effectively reduce the net operating cost of long-haul trucking. Truck demand is estimated to increase by 3.2 to 15 billion VMT (an increase of 2.2 to 10.5 percent), depending on the technology alternative selected, the prevailing national truck price elasticity and rail cross price elasticity, regulation, and technology response. While degraded truck performance could also impact congestion, the concurrent white paper produced by ERG suggests that the impacts of fuel economy regulations on truck performance will be minimal, if any. The remainder of this analysis focuses on basic freeway sections because fuel economy regulations are most likely to affect long-haul truck traffic, which spend the vast majority of their time on freeways. (Trucks have a significant impact on congestion at other traffic control locations, such as signalized and unsignalized intersections, merge sections, and freeway-to-freeway off-ramps, but the data to analyze these impacts is not readily available.) In the highway capacity manual (HCM), in basic freeway analysis, trucks are represented as ―passenger car equivalents‖ (PCE). 20 The PCE concept is meant to capture the effect that heavy vehicles have on traffic flow on a freeway because heavy vehicles occupy more space, travel more slowly up steep grades and more quickly down them, accelerate more slowly, brake more slowly, and change lanes more slowly than passenger cars. Furthermore, different passenger car operators react differently to the presence of trucks; for example, following further behind trucks than cars. An increase in the total truck traffic PCEs on the road could be attributable to a number of effects, most significantly an increase in total traffic, although there could also be modest impacts if trucks have lower power output, higher weight, or regulations that encourage class-shifting. The HCM increases the PCE for trucks based on roadway conditions such as grade, number of lanes, distance to roadside obstructions, and width of lanes. It does not, however, distinguish between truck PCEs under congested and uncongested conditions. FHWA simulated the effect of combination trucks as part of its Truck Size and Weight Study to estimate how effective truck PCEs change based on the weight-to-horsepower ratio of the truck itself, the grade of the roadway, the road type, geography, and congestion levels. They did not estimate the impacts of 20 Transportation Research Board, Highway Capacity Manual, Washington, D.C., 2000. - 12 -
other roadway characteristics such as lane width or distance to obstructions. 21 The tables from the FHWA report are reproduced in this paper and to show how different scenarios change how trucks impact roadway volumes. Generally, steeper grades, longer hills, fewer lanes, and a higher weight-to-horsepower ratio increase the number of PCEs for a single truck. Truck PCE conversions are necessary to calculate a volume-to-capacity (V/C) ratio, which can be used to estimate congestion and delay measurement. Figure A-1 at the end of this document shows PCEs for trucks on rural highways. While different formulas have been developed to estimate traffic speeds based on V/C ratios, an illustrative example can be provided through the use of the Bureau of Public Roads (BPR) formula: Congested Speed = (Free-Flow Speed) / (1 + 0.15 * [volume/capacity] ^ 4) The formula implies that as a basic freeway segment approaches capacity (as the V/C ratio approaches 1.0), traffic speed will be reduced. To calculate delay, one must calculate both congested and free-flow travel time from the segment length and congested and free-flow speeds, then measure the difference between the free-flow travel time and the congested travel time. An alternative perspective on congestion measurement uses estimates from literature of the marginal cost of one combination truck on overall congestion. In one study, Parry estimates the marginal congestion cost of combination trucks to be $0.168 per mile in urban areas and $0.037 per mile in rural areas. 22 The marginal congestion cost describes the cost, measured in lost travel time, that a single additional combination truck imposes on the rest of the traffic already on the roadway. Generally, as congestion increases, the marginal cost increases. In his analysis, Parry uses an estimate of PCEs that is consistent with the HCM but does not take into account the full impacts of trucks on congestion. To wit, the marginal cost estimates are likely to be larger. Approach: For estimation of change in delay: The approach taken is to conceptualize an average high-truck traffic basic freeway scenario, create a comparison scenario with additional 2.2 - 10.5 percent truck traffic (from Section (1)(ii)), estimate the V/C ratio for each scenario, estimate congested segment speeds based on the BPR formula, and calculate delay for each scenario. This approach assumes that the average nationwide increase in truck traffic occurs on this hypothetical congested segment. For estimation of change in marginal cost: An alternative approach uses Parry‘s marginal congestion costs. To estimate total increased marginal congestion costs, the current urban and rural Class 8 truck VMT is identified, and the percent change in VMT calculated in Section (1)(ii) applied to estimate the total marginal costs. 21 Battelle, ―Traffic Operations and Truck Size and Weight Regulations, Working Paper 6,‖ prepared for the Federal Highway Administration, February 2005. 22 Parry, Ian, ―How Should Heavy-Duty Trucks Be Taxed‖ Resources for the Future, April 2006. See Table 1 for his benchmark parameter values for mileage-related marginal external costs. - 13 -
Page 1 and 2: Assessment of Fuel Economy Technolo
Page 3 and 4: no effect on congestion as a result
Page 5 and 6: vehicle fuel consumption (78 percen
Page 7 and 8: eduction; logical fuel economy tech
Page 9 and 10: million gallons, for a combined reb
Page 11: e defined as something similar to
Page 15 and 16: capacity and with high truck volume
Page 17 and 18: Table 1 Historical and Recent Long-
Page 19 and 20: truck-specific congestion pricing s
Page 21 and 22: In Stockholm, the cordon pricing sc
Page 23 and 24: Findings: The following studies eit
Page 25: Figure A-1 Vehicle Passenger Car Eq

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