Journal of Transportation Technologies, 2012, 2, 267-276 Published Online July 2012 (
Modeling Motorization Development in China
Junlei Wang1,2, Xiaoduan Sun1,2, Yulong He1,2, Shuzhan Hou1,2
1Transportation Research Center, Beijing University of Technology, Beijing, China
2University of Louisiana, Lafayette, USA
Received April 16, 2012; revised May 14, 2012; accepted May 29, 2012
Entering the 21st century, China’s economic development has reached new heights and the country has ascended to the
world’s second largest economy. The 20 year unrelenting development in China also stimulates income growth. The
increased disposable income enables an ordinary Chinese family vehicle ownership which was unthinkable two decades
ago. The most populous country has started a love affair with automobile just like in the United States. Annual automobi l e
sales in China rose from 2.1 millio n in 2000 to 18.1 millio n in 2010 w ith a year ly growth rate of 24.3%, wh ich sp urs the
vehicle ownership increase from 18.1 million in 2000 to 78.8 million in 2010, a growth rate of 15.9% The unprece-
dented motorization development in China is making a huge impact on all aspects of society, including negative cones-
quences that cannot be ignored. Traffic congestion, air pollution, and dependency on imported oil are huge emerging
problems threatening Chinese sustainable development. Although these problems occurred and still exist in many other
developed and developing countries, they are more acute in China today. By collecting and analyzing the massive data
from various sources, this paper explores the relationship between economic development and level of mobility by
studying the historical developments from several developed counties and discusses the key issues in Chinese motorize-
tion development. The objective of the study is to predict the future level of motorization and its potential impacts.
Keywords: Motor and Society; Motorization; Gompertz Growth Function; Vehicle Ownership; Per Capita GDP; GDP
Elasticity; Forecast
1. Introduction
Entering the 21st century, China’s economic development
has reached new heights and the country has ascended to
the world’s second largest economy. Based on published
statistics, GDP growth in China has remained above 8%
from 2000 to 2010, which is from 1203.0 billion US
Dollars (current value) in 2000 to 5848.8 billion US
Dollars (current value) in 2010 based on the China
Statistic Bureau [1,2] as shown in Figure 1. At the same
time, per capita GDP increased from 949.2 US Dollars
(current value) in 2000 to 4382.0 US Dollars (current
value) 10 years later. China has reached the category of
middle-low income countries from low-income coun-
Since the 1990s, China has accelerated transportation
development. After more than 20 years of construction,
the national roadway infrastructure has emerged as one
of the largest highway transportation systems in the
world. By the end of 2010, total roadway mileage
reached 4.0 million kilometers and national highway
density is 41.75 kilometers/100 square kilometers. Free-
way mileage has reached 74.1 thousand kilometers in
2010, as shown in Figure 2. Total road mileage and total
freeway mileage rank second in the world following the
United States.
The unrelenting 20 year development in China also
stimulates income growth. The increased disposable in-
come enables an ordinary Chinese family vehicle owner-
ship which was unthinkable two decades ago. The most
populous country has started a love affair with automo-
bile just like in the United States. In recent years, the
growth momentum in automobile sales seems unstoppa-
ble. Annual automobile sales rose from 2.1 million vehi-
cles in 2000 to 18.1 million vehicles in 2010 with a
yearly growth rate of 24.3%, which spurs the vehicle
ownership increase from 18.1 million in 2000 to 78.8
million in 2010 with a grow th rate of 15 .9%, as shown in
Figure 3. The number of vehicles per 1000 people rose
from 12.7 in 2000 to 60 in 2010 resulting in an annual
growth rate of 16.6%. Only passenger cars and comer-
cial vehicles are considered as vehicles in all statistics
cited by this paper. Motorcycles and three-wheeled vehi-
cles are not counted.
After China became number one in the world in annual
automobile production and sales in 2009, another mile-
stone was reached when more than 18 million vehicles
were sold in 2010, a 32.3% increase from the last year’s
opyright © 2012 SciRes. JTTs
Figure 1. Annual GDP and GDP growth rate in China.
Figure 2. Length of roadway and expressway in China by year based on China statistic bureau [1] and ministry of transport
of the people’s republic of China [3].
Figure 3. Automobile production and sales of China by year based on China automotive technology and research center [4].
Copyright © 2012 SciRes. JTTs
J. L. WANG ET AL. 269
record. Considering the vehicle ownership rate (number
Se were conducted on the motorization de-
Japan USA Germany France Brazil ChinaWorld
of vehicles per 1000 people) is still 10 to 20 times lower
than the rates of Japan and United States, as shown in
Table 1, this demonstrates a great potential for future
motorization development in Chin a.
2. Economic Development and Level of
veral studies
velopment in China in the past, which can be summa-
rized in three groups based on the methodology. The first
group uses the linear regression to model the motorize-
tion process in China [5], which has very limited applica-
tions since the relationship between influential variables
and level of motorization is basically not linear. The
second group models the situation by system dynamic
model, which is only suitable for short-term mobility
development prediction such as the GM automobile
market prediction model and State Information Center of
China automobile market prediction model [6]. The th ird
group utilizes Gompertz model [7-9] for the long-term
prediction as in this study. Previous studies in this group
used the data before 2009, which did not account for the
spike in vehicle ownership in 2010. For instance, the
maximum vehicle ownership in 2020 predicted by pre-
vious studies is 0.15 billion. But it is certain now that this
number will be reached in 2015.
Automobiles are considered durable goods and the
consumption of the good is closely related to the level of
per capita income. Based on studies from Dargay, Qi,
Wang, the World Bank, and International Road Federa-
tion [4,7-10], the development experience of many de-
veloped countries shows that a higher level of per ca-
pita income always stimulates a higher vehicle ownership
rate, as shown in Figure 4.
According to Figure 4, the positive increasing trend
between per capital income and level of motorization is
not simply a linear form but rather an S-shaped curve.
The demand for automobiles can be seen in four stages;
in stage 1, vehicle ownership increases slowly as income
increases; vehicle ownership increases fastest in stage 2
able 1. Vehicles per 1000 population from selected coun- T
2005 592 683 597 596 124 24 137
2006 594 829 530 598 128 28 140
2007 593 833 533 598 136 33 143
2008 591 822 536 598 143 38 145
2009 578 817 544 601 154 47 144
Figure 4. Relationship between economic development and
level of mobility.
with increasing income; and the rate of increase slow
nership no longer increases as income
creases. Since the motorization process is similar to the
down in stage 3 followed by a stable state in stage 4
when vehicle ow
Gompertz growth function curve, the Gompertz model
[4,7] was used in this study to model the relationship
between economic development and the level of mo-
Letting V denote the long-run equilibrium level of
the vehicle/population ratio, and G denote per-capita
income, the Gompertz model can be written as:
VG e
is the saturation level,
are nega-
tive parameters.
Taking the logarithm on both sid
becomes: es twice, the model
 
The elasticity of the vehicle/population ratio with re-
spect to per-capita income is defined as:
 
Exx xx y
fx fG
 
lim lim
Ey yy yx
 
Ge Ge
fGe eee
 
 
 (4)
be written as: The elasticity can
Ge G
ee Ge
 
Source: World motor vehicle statistics-2011 [10].
Copyright © 2012 SciRes. JTTs
By taking derivative of the Equation (5) with respect
to and letting it be 0, we can identify the inflexion
point where the elasticity is at maximum:
InflexionPoint 1G
 (6)
capita GDP is developed. The
B using the data from eight countries, the United
States, Japan, France, Britain, Italy, Brazil, India and
China, the relationship between ownership rate and per
value for developed
countries is the maximum value of the vehicles/1000
population. Because developing countries have bigger
populations than developed countries, the vehicle own-
ership saturation generally is lower than developed coun-
tries, which results in a
value of 333 (1 vehicle/3
persons). Table 2 lists the result of regression modeling.
The va lu e of R2 is bigg er th an 0.8. Th e last column of the
Table 2. Reg
Countries γ α β
table lists the F value used for model inspection. It is
demonstrated that most countries’ long-term relationship
between ownership rate and per capita GDP is similar to
the average development curve, which is derived in
Equation (7). The GDP Elasticity Inflexion point is $4626.
557 G
VG e
Figure 5 shows that the curve basically fits to the
curves derived for the majority of the countries.
3. Economic Development and Highway
Unlike vehicle ownership, highway infrastructures are
public property managed by governments at different
levels. The size of a highway network is closely related
ression result.
R F GDP elasticity inflexion point (USD)
U.S.A. 829 –0.76304634 –0.00009398 0.908 206.988 10,641
Japan 593 –1.92095842 –0.0009399
5 –1.52916 –0.00423 0. 149
10639 0.881 128.432
France 977580148869.726933
U.K. 575 –1.46723562 –0.00013075 0.947 354.555 7648
Italy 668 –2.25896832 –0.00018335 0.841 99.326 5454
Brazil 333 –2.26956154 –0.00016990 0.820 89.721 5886
India 333 –0.55660547 –0.00086406 0.950 381.877 1157
China 333 –4.65366855 –0.00025840 0.932 204.452 3870
verage 557 –1.92720418 –0.00024388 - - 4100
Note: for Uand Ja60 to 2 Chin 197 d ata for other countries 1963 to 2005.
The data.S.A. pan are from 19005, the data fora is from8 to 2010, the are from
Figure 5. Relationship of per capita GDP and vehicles/1000 population in selected countries (Source: references [11,12]).
Copyright © 2012 SciRes. JTTs
J. L. WANG ET AL. 271
to a country’s territory, economic development, popula-
tion, income and population density. Generally speaking,
a country’s highway infrastructure is not as closely re-
lated to the economic development as its motorization
[13]. Figure 6 illustrates the data collected by this study
from I.R.F. World Road Statistics [12], which shows the
size of highway infrastructure remains constant after
economic development reaches a certain level based on
the developed country’s history. Highway mileage still
increases as economic development increases in deve-
loping countries. Since rural highway system develop-
ment generally keeps pace with the country’s economic
development, excessive and persistent traffic congestion
would not occur on highways outside urban and subur-
ban areas.
The relationship between economic development and
highway infrastructure development is different in urban
and suburban areas. Because of the high population den-
sity and high construction costs, the impact of economic
tween the elastic coefficient defined by Equation (5) and
per-capital GDP. In general, the lower level of motorize-
tion, the higher influence of GDP, as in China and Brazil.
It is also clear that the higher level of economic deve-
lopment correlates to the higher GDP elasticity inflexion
point. Although the Chinese economy rose sharply in
recent decades, its GDP per capita still lags far behind
the GDP per capita in developed countries as well as its
automobile ownership. From the regression results, the
GDP elasticity inflexion point for China is 3870 US
Dollars (current value). By 2010, China’s per capita GDP
was about $4382, right on the inflexion point. In 2009
and 2010, in order to deal with the international financial
crisis, the Chinese government developed a plan to adust
and rvitalize the Chinese auto industry with four trillion
dollar investment projects, The plan greatly stimulated
the consumption of automobiles. The growth of automo-
bile market is obviously higher than the GDP growth rate,
1979, Japan in the year 1981, France in the year 1979,
U.K. in the year 1980, Italy in the year 1979, Brazil in
the year 2009, and India in the year 2006. I t is interesting
to see that most developed countries reached the inflex-
ion point in and around 1970’s, and developing countries
reached the inflexion point in and around 2010.
Macroscopically speaking, vehicle ownership affect by
the elasticity of GDP will lessen after 2011, and the
Chinese auto market will enter a slower growth time pe-
riod. How ever , due to th e ev er increasing oil prices in the
world, road congestion, insufficient traffic management
and policies, motorization in China presents a huge chal-
lenge to society in many aspects.
Many predictions about vehicle ownership in China
d velopment on urban roadway infrastructure is smaller which results in a higher elasticity peak value. In tha
than it is on vehicle ownership in metropolitan areas. The
increase rate of roadway infrastructure is generally
slower than the rate of population growth while the de-
mand for vehicle travel grows much faster than the rate
of roadway construction. Additionally, lack of efficient
traffic management strategies in restricting car use, rapid
construction of high-rise residential units, and insuffi-
cient public transport services have all contributed to
traffic congestions in most urban areas of China.
4. Predicting Future Motorization
In order to predict the future of motorization develop-
ment in China, it is important to review the history of
some developed countries’ developments. For that pur-
pose, Figure 7 was created to show the relationship be-
perspective, it is reasonable to claim that the Chinese
auto market is shifting from stage 2 to stage 3. The in-
flexion point happened in the United States in the year
Figure 6. Relationship of per capita GDP and per capita road length by selected countries.
Copyright © 2012 SciRes. JTTs
Figure 7. Per capita GDP elasticity.
were made based on the data collected before 2009. The
spike in vehicle ownership in 2010 made all previous
predictions irrelevant. For instance, the maximum vehi-
cle ownership in 2015 was predicted as 0.15 billion by
China Motorization trend. But it is certain that this
number will be reached in 2015.
In addition to GDP, other factors also affect the future
motorization level in China, such as gasoline cost, poten-
tial taxes, policy on restricted vehicle usage, culture,
characteristics of Chinese consumers and etc., which in
turn would affect the GDP growth. To better predict the
future motorization level, two scenarios were developed
with different GDP growth rate. The targeted GDP
growth rate is seven percent based on the “National 12th
Five-Year Plan”
capita GDP growth rates, nine and seven percent (in-
cluding price factor), were used in predicting future ve-
hicle ownership rate to reflect the potential fluctuations
in GDP development by the equation:
The nine percent growth rate scenario results a owner-
ship rate of 146.9 vehicles per 1000 population in 2015,
which indicates that the total number of vehicles will
reach 196 million, and a ownership rate of 241.6 vehicles
per 1000 population in 2020, which indicates that the
total number of vehicles will reach 322 million. The
seven percent growth rate scenario results in an owner-
ship rate of 128.2 vehicles per 1000 population in 2015,
which indicates that the total number of vehicles will
reach 171 million, and an ownership rate of 201.1 vehi-
cles per 1000 population in 2020, which indicates that
the total number of vehicles will reach 268 million. Fig-
ure 8 illustrates both scenarios.
5. Critical Issues
The unprecedented motorization development in China is
making a huge impact on all aspects of the society, in-
cluding negative consequences that can’t be ignored.
Traffic congestion, air pollution, and dependency on im-
ported oil are huge emerging problems threatening
Chinese sustainable development. Although these prob-
lems occurred and still exist in many other developed and
developing countries, they are more acute in China today.
5.1. Dependency on Imported Oil
orts by year. In
ed 56.6 million
tons of gasoline (84.4% by highway transportation) and
61.0 million tons of diesel oil (44% by vehicles) [14].
The consumption of gasoline and diesel oil rise with the
increasing number of vehicles. However, the production
of crude oil does not increase, remaining at about 200
million tons. The imported petroleum exceeded more
than 50 percent in 2009. With the increase of vehicle
ownership, China must import more and more petroleum
from other countries. Dependency on imported oil is con-
sidered a threat to a nation’s security. The demand for oil
has already put tremendous pr ess ur e on the g overnm en t.
5.2. Predicted Future Demand for Oil
The future demand for gasoline will be based on several
factors, such as vehicle fuel efficiency, urban transporta-
tion policy, transportation tax, and residence travel be-
(2011 to 2015). In this paper, two per Figure 9 illustrates the need for oil imp
2009, Chinese civilian vehicles consum
333 G
VG e
Copyright © 2012 SciRes. JTTs
J. L. WANG ET AL. 273
Figure 8. Predicting the vehicle ownershi
p in China (Indicate curve by 9% and 7%).
Figure 9. Annually oil consumption and production in Chin
ferences [15,16]; Note: one ton of c
a and the contries expported oil to China in 2010 (Source: re-
rude oil 7 barrels of crude oil).
In 2009 the 73% of vehicles using gasoline consumed
about 1.17 tons gas per vehicle per year. Considering
future demand of private vehicles that use gasoline,
gasoline consumption vehicles will increase to 78% in
2015 and 83% in 2020 . Th e an nual g aso lin e consumption
per vehicle will be reduced because of several reasons.
First, the government has requested the consumption of
gasoline for 100 kilometers must be decreased from the
current 8 liters to 5.9 liters for all new vehicles, resulting
a 26% improvement in fuel economy.
The government promoting public transit polices also
encourages more commuters to choose mass transporta-
tion options during rush hours, which reduces the use of
private vehicles. Increased taxes on gasoline and parking
fees along with res
eekdays (by vehic
duce vehicle use. Another factor contributing to the
lower usage of vehicles is that the majority of vehicles
are sold to private citizens, not to companies or govern-
ment agencies; private vehicles are driven less than
business owned vehicles. Because of the above stated
factors, it is predicted that the average vehicle gasoline
consumption per 100 kilometers will decrease about 26%
by 2015. It is predicted that technology improvement in
fuel economy will result in a 5% decrease annually in
gasoline consumption, and reduced vehicle travel would
result in a 2% decrease in gasoline consumption.
Similar to vehicles using gasoline, the annual average
diesel consumption will also decrease significantly for
vehicles using diesel oil because: 1) the proportion of
higher fuel efficiency heavy trucks will increase; 2)
mileage; and 3)
. It is predicted the
average diesel oil consumption per vehicle will drop 30%
trictions on the use of vehicles during
le’s license plate number) would also technology improvement increase gas
lighter trucks reduce fuel consumptionw
Copyright © 2012 SciRes. JTTs
in 2015 from the 2009 level.
The predicted fuel consumptions are summarized in
Table 3, which shows that the percentage of fuel con-
sumption increase will be smaller than the increase in
With 90% of total gasoline consumption for automo-
biles and 45% of total diesel consumption for diesel ve-
hicles, the demand for crude oil with the 9% growth rate
scenario will be 0.70 billion tons in 2015 and 0.79 billion
tons in 2020. The demand for crude oil with the 7%
growth rate scenario will be 0.61 billion tons in 2015 and
0.66 billion tons in 2020. If crude oil production in China
will only increase by 20 million tons each year, the total
production of domestic crude oil will be 0.22 billion tons
in 2015 and 0.24 billion tons in 2020, which makes
China heavily reliant on imported oil. China will need
68.6% of oil imported from other countries in 2015 and
015 and 63.4% in 2020 with the 7% growth rate sce-
The speed of economic development is much faster in
large cities that attract an influx of laborers to cities,
which worsens the traffic situation. Based on the data
from four large cities administrated directly by the na-
tional government, the roadway mileage per person is
either status-quo or decreases while the vehicle owner-
ship increases rapidly, as shown in Figures 10 and 11.
This trend will continue for the near future in China.
5.4. Traffic Safety
According to statistics from Ministry of Public Security,
in 2010 there were 3,906,164 recorded roadway traffic
accidents, up 35.9% from the last year, and 65,225 traffic
fatalities, down 3.7% from the last year. At present,
China is number one in recorded traffic fatalities. The
oped countries, as shown in Figure 11 [17] .
ment will expectedly in-
as 4.8
million tons, and particulate
. Most pollutants are emitted
69.5% in 2020 with the 9% growth rate scenario. China
will need 64.1% of oil imported from other countries in
2rio. It is clear that the motorization development forces
China heavily depend on imported oil, which puts the
country in a very vulnerable and uneasy position.
5.3. Traffic Congestion
At the present time, severe traffic congestion has already
become a way of life in most urban areas throughout
China. Because of the income gap between urban and
rural, regional income gaps are very big, most vehicles
are running in big cities where population densities are
high. Roadway construction in urban areas is far behind
the vehicle growth rate; meanwhile, Chinese city plan-
ning, transportation planning and traffic management
lack forward-thinking and long-term planning. Most of
the plans have underestimated automobile growth, which
partly explains why traffic congestion is so bad in the
cities. Traffic congestion greatly extends travel time, in-
creases travel cost, pollutes air quality, and induces noise
Table 3. Predicted fuel consumption in 2015 and 2020.
Year Vehicles
10,000 tons
10,000 ton
2009 6281 4617 5400 1663 5822
The first scenario
2015 19603 15290 9727 4313 10567
2020 32241 26760 11907 5481 11415
The second scenario
2015 17110 13346 8490 3764 9223
2020 26836 22275 9911 4562 9502
fatality rate in terms of number of fatalities per 10,000
vehicles is three to five times higher than the rates of
Rapid motorization develop
crease traffic accident frequency in China although the
accident rate may be reduced with massive government
highway safety improvement projects. The challenges in
highway safety come from not only the rapid motorize-
tion development, but also poor safety awareness, over-
loaded trucks, and so metimes insufficient road way d esig n
If the current fatality rate is used to predict future ac-
cident frequencies, the situation is very worrisome. The
fever for automobile ownership is shifting from major
cities, such as Beijing and Shanghai, to other medium
(population is between 10 and 15 million) and small ur-
ban areas (population less than five million). Safety
awareness is much weaker in these cities along with
weak safety education programs and other roadway de-
sign and traffic control problems. Accidents on rural
highways crossing the country are also increasing in
number in recent years.
5.5. Environmental Protection
In 2009, pollution by motor exhaust was 51.4 million
tons, in which CO was 40.1 million tons, HC w
million tons, NOx was 5.8
matter was 0.6 million tons
by automobiles. In many cities, especially large and me-
dium-sized cities, air pollution presents a characteristic
that the combined pollution of coal smoke and automo-
bile exhaust makes it very difficult to control atmos-
pheric pollution. Meanwhile, some areas of China often
experience atmospheric pollution problems, such as acid
rain, gray haze and light chemicals, with one area ex-
periencing more than 200 days of gray haze weather.
These problems are directly related to vehicle emissions
Copyright © 2012 SciRes. JTTs
Copyright © 2012 SciRes. JTTs
ap o
ita R
are M
ad Area
200405 20062007 2008
per C
Beijing Tianjin ShanghaiCho n gqin g
2004 2005
Vehicles/1, ersons
2006 2007 2008
idFigure 10. Average roadway length per res
ent in four cities (Source: reference [18]).
Figure 11. Fatalities rate per 10,000 vehicles from selected countries.
producing the nitrogen oxides and fine particulate pol-
lutants. As pointed out by the Ministry of Environment
Protection [19], with the increase in motor vehicle quan-
tities, motor vehicle emissions impact on the environ-
ment is more serious, adding to the pressure of city and
regional air quality.
6. Discussion
After three decades of high speed development, China is
at a critical point in history in many aspects, including
transportation development. Using the data collected
from various published sources, this paper predicts the
motorization development for the next decade in China
and reviews the emerging critical issues because of the
motorization development. The negative impact of high
speed motorization in energy conservation, traffic con-
gestion, traffic safety, environmental protection needs
urgent attention and must be dealt with seriously.
It is imperative for China to fully recognize the
emerging challenges of growing global energy demands,
the socio-economic implications, stresses of domestic
motorization development, and urgent environmental
protection needs. The gravity of the situation calls for
immediate action. The emission standards must be im-
proved for traditional vehicles currently operating in
China whose emission performance would not be ac-
ceptable in the U.S. and other developed countries. Being
a newly modernized country, China is and should be al-
ways thinking forward to the development of new energy
efficiency vehicles. With increasing urban population in
the next decade, the country needs new and innovative
ways to reduce traffic congestion through a combination
of actions in city planning, mass transportation networks,
and new traffic control techniques. As for traffic safety,
China needs to establish sustainable objectives on how to
reduce crash rates, not just to concentrate on crash num-
bers, since the crash numbers may still increase with the
mobility surge in the next few years. Excessive emphasis
on crash numbers would lead to less accurate crash data
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