Realization of an Active Society that Supports International Competitiveness

zResearch Trends and Results

Relationship between
Characteristics of Freight andFreight Truck Expressway UseRatio

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SEKIYA Hirotaka, Senior Researcher KOBAYASHI Masanori, Researcher
NANBU Hiroyuki, Guest Researcher UESAKA Katsumi, Head
Traffic Engineering Division, Road Department
1. Introduction
The Traffic Engineering Division is conducting
research to develop a “route selection model” to be
used to predict how freight flow on road networks will
be changed by freight truck traffic measures
introduced to strengthen international competitivenessand improve living environments in residential
districts. This report introduces an outline of ananalysis of the relationship between “characteristics offreight” and “expressway use ratio”, which is the mostfundamental freight truck route selection behavior inorder to obtain basic information for the model.
2. Outline of the analysis
We set hypotheses, “the ratio of expressway use,which ensures rapid delivery, is high in the case of thetransport of perishables such as raw fish, for which
express transport is preferred,” and “delivery
time-specified freight is highly likely to be transported
via expressways, which are known to be more travel
time reliable, as any delay in the delivery of such
freight is not allowed,” and verified the hypotheses
using data from the Commodity Flow Census (2005).
A Z-test performed as shown in Figure 1 confirmedthat the ratio of expressway use is higher in the case ofrefrigerated and frozen freight and delivery time
specified freight than it is for other kinds of freight at
a significance level of 0.1%.
11
a: Freight shipped fromrefrigerator warehouses (Pa)

80%

60%

40%

20%

b: Freight shipped fromother facilities (Pb)significant)
Z=14.8 (0.1%(0.1%有意）
0%0100 200 300 400 500
Transport distance (km)100%Ratio of expressway use

100%Ratio of expressway use

Research Trends & Results(Keywords) Freight truck traffic, Route selection, Expressway use ratio

1Table 1. Parameter Estimation Result011 12 23 3

4 4

Estimated coefficients
Coefficients

Estimate

Std. Error

Z valueSignif.

(Intercept)-0.5182

0.0522-9.92***

X1: Transport distance

0.00500.0002

31.47***

X2: Freight refrigeration status

0.7231

0.0536

13.50***

X3: Delivery time specification

0.20720.0513

4.04***

X4: Freight lot-0.15310.0200-7.66***

0.1% confidence level

Change in expressway use ratio accompanying
improvement of commercial practices was simulatedusing the above equation. As shown in Table 2, it isconfirmed that the rise of the just-in-time transport
ratio increases the expressway use ratio by 2.6 points.
Table 2. Description and Results of the Simulation
Case 1

Change of commercial practiceIncreasing transport distanceCase 2

Increasing just-in-time transport

Case 3

Reducing lot size

Description of SimulationfChange50% increase in transport 74.3%+7.4
distance
Delivery time specification 69.6%+2.6
ratio of 100%
Average lot size decrease of 67.7%
+0.8
50%

a: Delivery time specified freight (Pa)

80%
60%
40%

b: Not-specified freight (Pb)20%
0%time specification dummy(x3) and lot (x4)) obtained
an equation which estimates the expressway use ratio
according to characteristics of freight (Table 1).
Coding conditions conform, and a significance level of
0.1% was satisfied. This suggests that all of the above
four parameters are factors which explain freight truck
route selection behavior.

significant)Z=10.6 (0.1%(0.1%有意）0100 200 300 400 500
Transport distance (km)Figure 1. Significant Difference Test

Regressing the Logit converted expressway use
ratio f to four parameters (transport distance (x1),refrigerated, frozen freight dummy (x2), and delivery

3. Conclusion
This report has shown that it is possible to estimate“change of expressway use ratio caused by future
improvement of commercial practices” by applying
the resulting relational equation.
It is anticipated that the “relationship between roadstructure specifications and route selection
characteristics” will be studied to further improve theroute selection model, and that this knowledge andmodel will be applied to evaluate freight truck traffic
measures.