THE DELAY COST OF TRUCK AND FREIGHT PRICING PRACTICES PDF Free Download
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THE DELAY COST OF TRUCK AND FREIGHT
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PRICING PRACTICES
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Running head: The Delay Cost of Truck and Freight Pricing Practices
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Areekamol Tor.Chaisuwan1, Nakorn Indra-Payoong2,
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Sarawut3 Jansuwan
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1Department of Accounting, Maejo University-Phrae Campus, Phrae 54140
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E-mail: areekamol@phrae.mju.ac.th
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2,3Faculty of Logistics, Burapha University, Chonburi, Thailand 20131
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E-mail: { nakorn.ii,sarawutj}@gmail.com
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Abstract
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This research first analyses the pricing and delay cost of truck on the Interstate
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highway 15 (I-15) in Utah. A practical framework uses the data source from
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Utah Department of Transportation (UDOT), Freight Analysis Framework
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version 3 (FAF3) and American Transportation Research Institute (ATRI) to
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estimate the delay cost of truck. Compared with the online shipping
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marketplace in the US, and the average truck operating costs per mile, the
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markup of freight price can implicitly be derived. The seasonal factor is also
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introduced to adjust a regular freight price, particularly during the winter
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season. The outcome points out the critical links that affect to freight markup
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price. The empirical studies have indicated a declined profit for trucking
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service, especially for Washington-Box Elder route in which a significant delay
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cost is imposed. The concept of delay cost is later applied to estimate the delay
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cost of truck in Thailand where containerized freight and five major routes in
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the eastern region of Thailand are considered. The Average Daily Traffic
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(ADT), free flow speed and route capacity are basically used as input data. The
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results of this study are primarily to support freight transport research and
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policies and to provide a more accurate cost of annual truck congestion for
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commercial vehicle operators on highways.
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Keywords: delay cost of truck, Average Annual Daily Truck Traffic (AADTT),
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markup pricing, delay cost estimation, seasonal adjustment factor
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Introduction
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A traffic delay by severe congestion, traffic problems, including weather
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condition can cutoff the opportunity of profit earning and markup in the trucking
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service firms. It does not only influence the increase of the operating cost but also
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involves with the penalty and a loss of repute of their business, benefits, and
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customers’ royalty. Therefore, the delay cost is an important factor for trucking
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service and the companies should in the pricing process. The seasonal delay cost
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for trucking should be calculated in a part of operating cost. The objective of this
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research is to present a practical approach for estimating the delay cost of truck and
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analyzing the markup of freight price using a case study of trucking service on
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Interstate 15 (I-15) in Utah, the United States. To calculate a benefit of congestion
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from traffic variation database, three majority sources of data: UDOT, FAF3 and
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ATRI are undertaken in an evaluation process. According to U.S. Department of
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Transportation (U.S.DOT, 2004), Utah is ranked the 15th among the states that has
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capacity bottlenecks on freeways which are used as intercity truck corridors in
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2004. The collecting data are the bottleneck locations and the essential information:
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number of lanes, Average Annual Daily Truck (AADT), Average Annual Daily
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Truck Traffic (AADTT) and the percentage share of truck traffic, and annual hours
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of delay by all trucks. The result points out that the area closed to Weber country is
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the most congested area, and 25% of traffic in that particular areas are trucks. The
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annual of delay caused by trucks is approximately 48,088 hours. Utah Department
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of Transportation (UDOT, 2007) provides the 2007 AADTT surveyed data and
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2040 estimated truck demand data are obtained from FAF. Each individual link of
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all 221 links provides a distance range, average speed, AADT, AADTT and
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Functional Class (FClass) according to the speed regulation design. The directed
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transport costs of truck are described by American Transportation Research
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Institute (ARTI, 2008). ATRI develops a survey and distributed to a cross-section
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of for-hire motor carriers represented the predominant industry sectors. The survey
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responses are aggregated and analyzed for the costs per mile (CPM) and then are
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converted to costs per hour (CPH) by using an industrial accepted average operating
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speed. The result shows a total marginal cost for the industry $1.73 per mile and
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$83.68 per hour (Trego, 2010). The vehicle’s value of time (VOT) has been widely
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evaluated for more than 40 years, since it was one part of the economic
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transportation analysis to the difference objectives (Bruzelius, 1979). Recently, the
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VOT for trucks has been estimated between $20 per hour to $190 per hour
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(Wheeler, 2010). In contrast to a value of freight travel time savings in congestion,
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the surveys of4 types of industrial freight carriers in the state of California The
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result estimates the value of travel time saving with the commodity time sensitive.
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The value was found in a range between $144.22 and $192.83 per hour (Small et
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al., 1999). Smallkoski and Levinson (2002) indicate the considerable importance of
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freight transit time and cost. The interview method survey is conducted by using an
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Adaptive Stated Preference (ASP) to estimate VOT in dollars per hour and the
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results indicate that VOT is about $49.42. In addition, the results show a marginal
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operating cost of commercial vehicles varied from seasonal timing of shipments.
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Haning and McFarland (1963) address that an increasing speed can be contributed
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more profit of vehicle movement overall. The difference between the based
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condition and the improved speed condition is the value of time saving. Two
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additional methods for estimating cost of time are determining the cost of providing
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time saving and the willingness to pay methods (Adkins, Ward and Mc Farland,
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1967). The Puget Sound Regional Council (PSRC, 2008) study route choices of
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truck drivers corresponding to operating costs.. The result reveals that VOT is in a
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range of $28 to $73 per hour. Brownstone and Small (2005) study on two projects
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of California road pricing in areas of I-15 High Occupancy Toll (HOT) Lanes, San
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Diego and the State Route 91 (SR91) facility in Orange County. The estimated VOT
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saving is improved by travel time reliability. The empirical results indicate that
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VOT is between $20-$40 per hour. The important factors for computing drivers’
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cost of road transportation are: distance, vehicle speed, type of road, drivers’
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characteristics (driving behavior, experience, speeding), traffic speed and volume,
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time of day (day/night) and interaction with weather conditions (ERSO, 2006).The
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directed transport costs of truck are described by American Transportation
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Research Institute (ARTI, 2008) The details based on the result of the analysis are
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shown in Table 1. This ARTI estimate will be applied to calculate the delay cost on
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I-15 in this study.
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Table 1 The motor carrier expenses in the United States
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Motor Carrier Marginal Expenses
Costs per
mile
Percentage
per mile
Costs
per
hour
Vehicle-based
Fuel-oil costs
0.634
36.65
$33.00
Truck/trailer lease or purchase payments
0.206
11.91
$10.72
Repair and maintenance
0.092
5.32
$4.79
Fuel taxes
0.062
3.58
$3.23
Truck insurance premiums
0.06
3.47
$3.12
Tires
0.03
1.73
$1.56
Licensing and overweight-oversize permits
0.024
1.39
$1.25
Tolls
0.019
1.10
$.99
Driver-based
Driver pay*
0.441
25.49
$16.59
Driver benefits
0.126
7.28
$6.56
Driver bonus payments
0.036
2.08
$1.87
Total marginal costs
$1.73
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$83.68
* CPH figures are based on respondents’ actual driver hourly pay rates
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Congestion cost affected to transportation is a one part of the external costs. Motor
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carriers could not take that cost to the accounting record. But congestion cost is
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helpful for decision making of business operation especially price quotation which
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related to businesses’ profit or loss. In addition, the estimated congestion cost also
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benefits the government policy. Congestion due to the capacity and density of
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transport system depends on mode of transportation, type of users, infrastructure
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characteristics, local travel time, and activity alternatives. An increase in travel time
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is a major factor of congestion. The standard valuations of travel time show 90% of
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total economic congestion costs. With congestion, vehicles consume 10%
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additional fuel costs under stop-and-go conditions (IMPACT, 2008). The
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estimation of congestion fee is computed by total delay or access costs (INFRAS,
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2004). The best estimation practice of congestion costs is based on speed flow
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relations, value of time and demand elasticises. The Marginal External Congestion
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(MEC) cost represents a current traffic volume in vehicle per hour. MEC cost
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depends on the price elasticity of demand and the slope of speed flow function.
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Speed flow variation describes the effect of the additional vehicles on the transport
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system due to the transport cost. Speed flow curves depend on infrastructure
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characteristics, topography, whether conditions, the network arrangement, available
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travel alternatives, regulations (speed control, ramp metering, etc.) and driving
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habits. The result fulfils the condition that the demand or willingness to pay curve
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equals the average time cost plus the MEC costs. University Transportation Center
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for Mobility (UTCM, 2011) evaluates the Value of Delay (VOD) for commercial
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vehicle operator due to highway congestion. The VOD is a primary information of
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construction and tolling policy, composing of several factors, such as direct
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operational cost, travel length, travel time variation, inventory holding and
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warehouse management. Two methods are used to estimate VOD: Stated
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Preference (SP) survey and the carrier fleet operational simulation. The congestion
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reveals a range of VOD from $94 per hour to $121 per hour in a case of central
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depot and $80 per hour to $84 per hour in a case of two depots. Gillett (2011)
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calculates a delay cost for long haul single unit and combination trucks to assess
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the highway performance by identifying the congested locations where current or
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future delay are likely to occur. An Interstate-75, 160 miles from Macon to the
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Georgia-Florida border is studied. The delay cost is calculated by taking speed,
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volume, distance, types of truck, and types of commodity into account. In order to
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obtain the value of freight by truck and commodity types, the FAF3 is used as the
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data source together with the average truck speed surveyed by ATRI and traffic
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volume collected by Georgia Department of Transportation (GDOT).
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Materials and Methods
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To calculate the delay cost and markup price, AADTT, FClass and average speed
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on each link from UDOT, 43 Standard Classification of Transported Goods (SCTG)
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commodity flow survey moved by truck from FAF3 are used. For our study,
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approximately 401 mile-corridor is used to estimate the delay cost, combining
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multiple data sources from USDOT, ARTI, and FAF. The methodological
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framework is given in Figure 1.
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155
156
157
158
159
160
161
162
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167
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169
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175
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* According to American Transportation Research Institute (ATRI) estimated truck operation cost for one
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hour travelling is $83.68 (Reference year 2008)
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** The AADTT traffic volume from November to February 2007 survey data by UDOT are used to calculate
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seasonal adjustment factors in winter condition
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Figure 1 Experimental method
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FAF3 and AADTT database on I-15
Delay time cost calculation:
- Average travel time and free flow travel time (mins.) = distance/speed*60
- Average delay (mins.) = Average travel time – Free flow travel time
- Average delay per mile (mins./mile) = Average delay / Distance
- Total link delay (mins.) = Average delay* Truck volume
- Annual average daily delay traffic cost ($) = (VOT(83.68*)* Total link delay/60)
Calculate number of trucks by truck trip
allocation factors
Result:
Annual average daily delay cost
of total 221links
Absorb delay cost in winter season with
speed adjustment factors by selected
traffic count station**
Choose routes on I-15 which are
the top ten average freight price
by Uship
Markup pricing analysis
Calculate freight cost each route
Absorb delay to
freight cost
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Truck traffic volume
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According to the input data for calculating delay cost of truck, FAF3 and UDOT
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data; AADT and AADTT 2007 surveyed base and are collected for analyzing traffic
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volume on each links.
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The AADTT by truck types, body types and commodity types is estimated using
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the FAF3 freight analysis framework. The VIUS 2002 with Truck Payload
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Equivalent (TEP) is also used for model calibration as:
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9
11 12 13 19 1
11
11 12 13 19 1
........ k
i i i i i i i i i i k
jk
i i i i i k
X X X X X
Y
(1)
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Where
j
Y
is the number of trucks in type
j
, where
j
=1, 2,...,5,
i
X
is tonnage of
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commodity
i
, where
i
=1, 2,…,43,
ijk
is fraction of commodity
i
moved by truck
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type
j
with body type
k
, where
k
= 1, 2,…,9,
ijk
is mean payload of moving
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commodity
i
by truck type
j
with body type
k
,
i ijk
X
is tonnage of commodity
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i
X
carried by truck type
j
and body type
k
, and
/
i ijk ijk
X
is the number of
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trucks
j
with body type
k
required to move
i ijk
X
tons. From the formulation, it is
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found that about 12.90% are single unit (SU) trucks and 87.10% are the
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combination unit (COM) trucks.
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Seasonal Factor: Case of I-15 Corridor
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Intermountain winter storms have adverse impact to Salt Lake county where is the
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area of growing of population and economy (Schultz et al., 2002). Figure 2 shows
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monthly average snowfall in Utah. It can be seen the severe of weather condition in
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Utah between November and February. The winter storms could affect the
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serviceability of I-15 as they potentially reduce the reduction of roadway capacity
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or even the closures.
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Figure 2 Monthly average snowfall for Salt Lake City international airport
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(source: wikipedia.org)
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Truck drivers have to pay more attention and to reduce the speed driving on the
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slippery road surface especially on snow and ice. To calculate the speed adjustment
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factor to the delay cost in the winter condition on I-15, the climate capturing by
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average snowfall is chosen, and the level of snowfall is correlated to the traffic
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volume during the considered period.
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Noted that an accident, depreciation and fuel cost are also increasing during the
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winter season. FHWA’s road weather management program summarizes the
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various weather events affected to driver capabilities and traffic flow. The reduction
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of road way capacity can be caused by snow accumulation and wind-blow. The
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weather events can reduce the mobility on arterial routes, speed reductions can
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range from 10-25 percent on wet pavement and from 30-40 percent with snowy or
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slushy pavement. The average arterial traffic volumes can decrease by 10 to 30
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percent depending on road weather conditions and time of day. The saturation flow
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0
2
4
6
8
10
12
14
Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Avg. snowfall
inchs
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rate reductions can range from 2-21 percent. Travel time delay on arterials can
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increase by 11- 50 percent (Goodwin, 2002). Kim et al. (2008) study the spatial and
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temporal analysis of urban traffic volume explores traffic patterns in the Twin cities
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metropolitan area from 1997-2006. In terms of the monthly traffic volume pattern,
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the month of August usually has the highest traffic volume whereas January has the
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lowest traffic volume. The difference in monthly fluctuation is mainly due to
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weather conditions. The traffic volume in the winter season (November-February)
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is relatively lower than traffic in other seasons. The average traffic volume in the
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winter season is 0.5 percent lower than average of other seasons. The Iowa
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Department of Transportation and Iowa Highway Research Board (IIHR, 1998)
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collect the storm data from I-29 and I-80 by hourly traffic counts over two days of
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storm event and for one week after the event to understand the impact of the storm
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to the local traffic. The hypothesis is approved when traffic volume data is reduced
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in the number of trip and also the decreasing of the traffic speed because of the
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decreased friction on the road surface. Due to the assumption of this study, the
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traffic volume between November and February 2007 by using UDOT’s traffic
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count on I-15 are applied for calculating speed adjustment factors and hence the
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delay cost. According to traffic count data, the average daily vehicle is calculated
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by using 3 ATR stations on I-15 in Utah shown in Figure 3. The result in Table 2
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shows the percentage of speed adjustment for these stations.
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Figure 3 The traffic station counters which are chosen (source: UDOT)
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Table 2 Speed adjustment factor
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Station
Mileage Range
County Area
Speed
Adjustment
Factors (%)
From
To
From
To
401
0
42.170
Washington
Iron
12.72
403
42.171
242.460
Beaver
Juab
17.90
349
242.461
400.592
Utah
Box Elder
12.75
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Truck speed
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To calculate delay time of each link, ATRI’s average traffic speed is used as the
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input data. The average speed was recorded using the inductive loop embedded
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under the roadway. ATRI coordinates working with the Federal Highway
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Administration (FHWA), the individual truck speed is recorded by hour and by
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direction daily over the year of 2009.The available average speeds compared with
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the speed limit by regulation are used to analyze the delay or congestion. The speed
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limit of I-15 in Utah is 65 mph. in the urban area and 75 mph. in other areas.
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Recently, the speed limit in some rural areas along I-15S is 80 mph. Functional
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Class (FClass) data is used to determine the speed limit area on each link; they also
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provide county route name, route number, total miles of route, type of area (Urban
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or Rural) and number of lanes. There are only 2 types of FClass; FClass 1 for speed
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limit 65 mph. and FClass 11 for speed limit 75 on I-15.
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Average freight price
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The delay cost of truck computed from the previous section is compared to freight
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price by the internet pricing website, UShip. Shippers can compare and reserve the
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upfront quotes by posting their name and proposed price or receive auction-style
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bids from 300,000 customer-reviewed transportation service providers. The auction
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system matches independent shippers-tuckers with the largest freight carriers and
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brokers by ranking. Freight price with full truck load (FTL) and weight 40,000 lb
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are used in this study in order to estimate price between ten O-D pairs county by
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country, and zip codes are used to define the locations of counties along I-15 route.
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Table 3 shows the freight price and distance provided from the online freight price
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quotation.
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276
277
278
279
280
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Table 3 FTL average freight price and distance between 10 counties
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County
Average Freight Price (U.S. dollars per truck trip)
1
2
3
4
5
6
7
8
9
10
Washington
Iron
Beaver
Millard
Juab
Utah
Salt
Lake
Davis
Weber
Box
Elder
Average Distance (miles)
1
Washington
189
580
956
953
1,058
903
864
864
920
2
Iron
64
232
841
836
777
1,003
920
920
877
3
Beaver
116
52
463
566
751
851
971
855
957
4
Millard
208
146
96
253
538
598
811
777
874
5
Juab
230
167
118
49
197
395
606
588
645
6
Utah
276
224
164
96
45
194
378
448
502
7
Salt Lake
310
247
198
116
79
45
297
235
206
8
Davis
344
293
229
160
110
76
38
186
420
9
Weber
345
294
245
176
126
92
52
14
272
10
Box Elder
371
307
259
190
140
106
69
31
29
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Results and Discussion
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The result of annual average daily delay cost of truck compared with the average
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speed from 221 links is shown in Figure 4-A. The top three links which have the
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most delay are link number 186, 181 and 185, which are close to Salt Lake City,
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the capital city of Utah. The total length is only 0.87 mile but the amount of AADTT
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delay cost is 3.18 million of dollars. When we compare the FClass 11 with the
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average speed, the speed limit is 65 mph. While the average speed on those links is
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only 0.5 mph. It can be shown the traffic congestion caused by seasonal effects.
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Map in Figure 4-B identifies the location of congested areas using MapwindowGIS
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program.
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Figure 4-A Average speed and AADTT delay cost by links on I-15
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295
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Figure 4-B AADTT delay cost and area of congestion on I-15
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Figure 5 shows the number of single and combination unit type of trucks from the
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percentage of truck trip allocation by our previous study. Top five commodities
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moved in Utah including coal, nonmetal mineral products, gravel, waste and scrap,
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and gasoline are summarized and shown in Figure 6 using the majority combination
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unit type of truck transported within Utah. Considered with valuation of product
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based on their perishability potential and/or use (Small et al., 1999), almost of all
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top ten commodities moved in Utah are classified as the moderate time sensitive
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products except cereal and grains, and mixed freight, which are categorized in a
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highly time sensitive. The moderate time sensitive products are the construction and
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energy products using bulk and liquid vehicle body types; coal, nonmetallic
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minerals, gravel, gasoline, fuel oils, crude petroleum and coal-not elsewhere
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classified. It can be seen that 9 out of 10 commodities moved in Utah are the time-
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sensitive products. The delay cost by seasonal adjustment factors has play the major
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role on these products.
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312
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Figure 5 Single and combination unit type of trucks by FAF3 truck type
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allocation factors
315
316
0
2000
4000
6000
8000
10000
12000
1
8
15
22
29
36
43
50
57
64
71
78
85
92
99
106
113
120
127
134
141
148
155
162
169
176
183
190
197
204
211
218
AADTT Combination Unit
AADTT Single Unit
Link number
17
317
Figure 6 FAF3 top 10 Commodity flow survey by year 2007
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Figure 7 shows top ten O-D routes by freight price, freight cost is calculated by
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$1.73 per mile according to ATRI cost estimation. A highest percentage markup is
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O-D Washington-Millard 208 mileages length accounted for 62.36% of markup. In
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contrast to O-D Washington-Box Elder 371 mileages length is the less markup with
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30.24%.
323
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Figure 7 Top ten O-D routes by Uship freight price on I-15 in Utah
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0
5
10
15
20
Million of tons
0
10
20
30
40
50
60
70
0
200
400
600
800
1000
1200
Price Cost (%)Markup
Dollars per trip
(%) Markup
18
Continued with cost absorbed delay time in Figure 8, the result shows the
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Washington County-Box Elder County is a critical O-D pair.
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Because of this O-D pair has the longest distance and is located close to the
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mountainous area along I-15 combining with the number of vehicles transported in
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Salt Lake City and vehicles passed through Utah from other states, resulting in an
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increase of delay cost over freight price.
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332
Figure 8 Price and cost absorbed delay
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0
200
400
600
800
1000
1200
1400 Price
Cost absorbed delay
Dollars per trip
19
334
Figure 9 The percentage markup comparison
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The result in Figure 9 shows the comparative percentage of markup pricing
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in the situations of; regular cost, absorbed delay cost, and absorbed delay cost and
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a seasonal adjustment factor in winter condition. The delay time and seasonal factor
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effect to the reducing trend of markup all O-D routes especially the route
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Washington-Box Elder, moreover O-D Washington-Salt Lake City, Iron-Weber
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and Iron-Davis get loss from the affect of seasonal adjustment factor.
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Freight pricing practice in Thailand
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To estimate the delay cost of trucks in Thailand, the specific provinces are chosen
343
by the location of Industrial Estates, which are: Rayong, Chonburi, Samut Prakan,
344
Chachoengsao, and Phra Nakhon Si Ayutthaya. The average freight price of five
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O-D routes between Industrial Estates to Leam Chabang container port is estimated
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from our previous studies. The Average daily traffic (ADT) is obtained from the
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Office of Transport and Traffic Policy and Planning (OTP, 2012), and the truck
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-60
-40
-20
0
20
40
60
80
Markup without delay
Markup absorbed delay cost
Markup absorbed delay cost and seasonal factor
(%) Markup
20
speed limit (i.e. 70 kph) is used as a free-flow speed. Then, the average travel time
349
is estimated by using the Bureau of Public Roads (BPR) formula (Bovy, el al.,
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2006).
351
4
01 0.15 a
aa a
q
tt C
(2)
352
Where
a
t
is travel time of route
a
(minute),
0
a
t
is free flow travel time
353
of route
a
(minute),
a
q
is average daily traffic (ADT) of route
a
, and
a
C
is
354
capacity of route
a
355
Once the travel time has been estimated, the speed reduction (delay) is
356
applied to adjust the operating cost of truck. The effect of the delay on the markup
357
price is shown in Table 4. In general, the longer distance, the less freight markup
358
price would be. Since the Rojana has a large amount of traffic, it imposes a
359
significant effect of cost absorbed delay to the markup (-17.94%).
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361
Table 4 The precentage markup without delay and absorbed delay
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Route
Distance
Percentage
markup
without delay
Percentage
markup
absorbed
delay
Thailand
1.
Eastern Seaboard
38
71.18
70.07
2.
Amata Nakorn
45
67.41
62.31
3.
Lad Krabang
90
47.45
33.18
4.
Gateway City
120
39.15
34.15
5.
Rojana
170
31.66
-17.94
363
21
364
Figure 10 The structure of freight price in Thailand and Utah
365
To compare the structure of freight price, Thailand and Utah, the average freight
366
price in percentage is shown in Figure 10. The total cost in both countries are similar
367
accounted for 48.63% and 49.43% respectively; however, the markup and delay
368
cost are somewhat different. In Thailand, the markup may relate to other (hidden)
369
costs while the delay cost is only accounted for 15.01%, which is less than the Utah
370
(26.14%). The difference indicates that the delay cost in Utah has more effect to the
371
freight price than Thailand.
372
373
Conclusions
374
Traffic congestion is recognized in transportation cost and significant factor in
375
transport network system. Various methods are used to quantify congestion costs;
376
consumers’ willingness to pay, the marginal impacted vehicle entering the traffic
377
on the road, the speed flow relationship of each road segment. This study is a unique
378
study area and provides cost explained economic evaluation techniques and how to
379
Total
cost
48.63%
Mark
up
36.35%
Delay
cost
15.01%
Total
cost
49.43%
Mark
up
24.43%
Delay
cost
26.14%
Thailand freight price
Utah freight price
22
apply them. The result represents delay cost on I-15 in Utah and the eastern region
380
of Thailand it can be seen the critical routes on the roadway. To absorb the vehicle
381
operating cost by delay and compared with freight pricing specific critical route,
382
the markup price is derived. The weather condition is also represented the
383
interaction of traffic delay by weather on I-15. The empirical studies have indicated
384
that a trucking company could lose a profit on the Washington-Box Elder route in
385
Utah and Rojana route in Thailand because a significant delay cost is imposed. On
386
the Washington-Salt Lake City, Iron-Davis and Iron-Weber routes in Utah, a truck
387
operator takes an opportunity cost by cutting or providing limited services during
388
the winter season.
389
The concept of delay cost can be applied in the others area to points out the critical
390
routes which risk of getting loss and provides a more accurate cost of annual truck
391
congestion for commercial vehicle operators. In addition the concept of delay cost
392
and markup analysis specific area for trucking in this study, the finding will be
393
benefit for the transport policy to find out a way for reducing the logistics cost in
394
the macro system which cannot be reduced by the businesses themselves. Then the
395
recurrent of pushing delay cost to the end consumer will be solved and improved
396
the national maximize welfare. The delay cost can be the guideline for applying this
397
practice in transport planning to improve the efficiency of infrastructure for the
398
traffic flow and control the delay cost within the reasonable level. The study
399
outcome can be the benefit for trucking policy such as the time permit for trucking
400
on highway to manage the road capacity, and tolling policy for trucking. According
401
to the delay cost for trucking in Thailand might be more accurate in the future work
402
23
if we can get more updating data of ADTT and specific roadway capacity each route
403
for calculating speed adjustment factor for trucking.
404
405
Acknowledgments
406
The Authors would like to thank the Department of Civil and Environmental
407
Engineering Utah State University in U.S.A., Faculty of Logistics Burapha
408
University in Thailand for giving data and technical support.
409
410
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