The Analysis of Parking Problems at Huaxi Hospital
Xue-dong Liang1, Chao Ji2, Qi-gang Ran3, Li Liu4
1, First Author, Corresponding Author
Business School, Sichuan University, Chengdu 610065, China
Business School, Sichuan University, Chengdu 610065, China
3
West China Hospital, Sichuan University, Chengdu 610041, China
4
West China Hospital, Sichuan University, Chengdu 610041, China
(1 liangxuedong@scu.edu.cn, 2815481560@qq.com,
3
W85259717@163.com,4yjhll@163.com)
2,
Abstract - A systematic analysis of factors that affect
parking in Huaxi hospital is proposed. The relative
importance of improvable factors is ranked by Grey
Relevancy Theory. It demonstrates that the parking demand
of employees, the efficiency of parking and traffic order are
the key factors that limit the hospital’s parking capability.
Parking demand and supply situation are estimated and
different characterization of each crowd of hospital travelers
is also analyzed in order to provide valuable information to
address the problems.
Keywords - hospital; parking; Grey Relational Analysis
I. INTRODUCTION
The problem of insufficient parking facilities is a
problem that plagues many urban areas in North America,
Europe, and Asia [1]. Due to the fast development of
China’s economic and the rapid growth of motorization,
parking problems at big cities are becoming more acute in
China. On one hand, the parking resource do not increase
much as time pass by; on the other hand, the demand for
parking resource has been continuously growing these
years. Between 8% and 74% of traffic is generated by
cruising for parking and the average time to find a curb
space can vary between 3.5 and 14 minute [2]. The
imbalance between supply and demand of parking
resource has become distinct. Cars cruising for parking
would further exacerbate traffic congestion and noise
problems, originate accidents, waste fuel and other
resources, pollute the air, degrade the pedestrian
environment, and restrain levels of accessibility. This is
not only because the distance traveled, but also frequent
stopping and starting of cars [3].
Most Chinese super hospitals are centralized in big
cities. And these hospitals were usually developed from
their former buildings, whose layout lack of advanced
concerning about parking or flow line of cars [4]. It is
common to see cars queuing on the road to park,
encumbering traffic around the general hospital in China.
West China Hospital of Sichuan university is a super
hospital with 4 300 beds [5]. Although the hospital covers
an area of 7.8 million square meters in urban of Chengdu,
the road around the hospital seems to be over crowed with
both people and cars. Parking has been a headache for
patients and visitors of the hospital. The difficulty of
parking not only causes the serious traffic jam around
hospitals at peak hours, but also damages the experience
of patients going to the hospital and gains the risk of
traffic accident [6]. Improving the parking situation has
been listed in the agenda of the hospital’s administrators.
This paper intends to analysis the parking system of
Huaxi hospital and find out the key factors that affect the
parking problems. The result may make it possible that
some targeted measures can be taken to ease the parking
difficulty of the hospital.
II. PARKING DEMAND AND SUPPLY ANALYSIS
A. The Supply of Parking Places
The capacity of parking lots in Huaxi hospital is 2225
in total, including 269 extended parking places. The
extended parking places were planned by taking full use
of the road in the parking lots to meet the growing parking
demand. The extended parking places often need skill and
sufferance to park successfully. Concerning the special
need of emergency patients and the ability to response to
some emergency situations, an on the ground parking lot
with the only access of emergency patients was planed.
Besides, the standard of charge for parking in the
hospitals was set officially which is lower than parking in
other areas of the urban city.
The capacity of different types of parking lots in
Huaxi hospital was displayed in Table 1. These data show
that 34.6% of the parking places (PA) were planned for
employees of the hospital and 60.2% of the parking places
were planned for patients and their visitors.
B. The Survey of Demand for Parking in Huaxi Hospital
1) Objective:
The aim of the survey is to figure out the
characteristics of different crowds of people parking in
the hospital. Different arriving time of each crowd of
travelers was taken into consideration in the survey.
2) Results of the Survey
The travelers parking in the hospital can be sorted as
employees, patients and visitors. The arriving time of
different populations is identical. The distribution of each
crowd of travelers’ parking demand on time was
illustrated in Figure 1, based on the data provided by the
security section of the hospital.
Characteristics of each crowd parking in the hospital
are as follow:
 Employees: The peak period of staff’s parking
demand is between 7:00-8:00 a.m. Parking places for
employees (PA) are likely to be fully occupied
between 09:00-10:00 and 14:00-15:00. The parking
demand of employees is mainly centered between
7:00-8:00 a.m. The parking period of employees is
always their working time, which is usually fixed. So
the turnover rate of employees’ parking is low.
 Common Patients: The peak time of outpatients’
parking demand is between 8:00-9:00 a.m. Parking
places for common patients (PB) are likely to reach the
saturation point between 09:00-10:00 a.m., which is
usually the most jamming period of the day.
 Visitors: There are a considerable portion of cars
parking in the hospital to visit the patients. Most of
these visitors usually come between 09:00-10:00 a.m.
The parking demand of visitors should have no
significant peak time due to the flexibility of their
arriving time.
 Emergency Patients: There is no regular pattern
about the arriving time of emergency patients. But it is
definitely troublesome for them to arrive on time when
the traffic jam is severe during peak periods.
C. Conclusions of the supply-demand analysis about
parking places
Although the capacity of parking places in Huaxi
hospital is higher than that the existing index system for
construction of supporting parking lots for hospital
buildings has prescribed, total supply of parking places in
Huaxi hospital is not enough to meet the demand in peak
hours of the day. The distinct imbalance between supply
and demand often leads to serious traffic jam between
09:00-11:30 and 14:00-15:00 of the day. The parking
demand of patients is usually considered to be “rigid”,
which means that if there is no parking place available,
they will queue on the road or cruising in the area until
they successfully parked [7]. As the hospital is always
crowed with people during daytime and drivers of cars
trying to park in the area are likely to have an anxiety
mood [8], large quantity of cars jamming on the road or
cruising in the area could be a big risk for traffic accident.
Bad traffic situation of hospitals leads to serious noise and
air pollution, which damaged the quiet and harmony
atmosphere of the hospital [9].
TABLE I.
PARKING LOTS OF HUAXI HOSPITAL
Types
Allocation
PA
PB
PC
PD
Capacity of extended
parking places
39
22
46
0
0
Summary
PA1
PA2
PA3
PA4
PB1
Capacity of standard parking
places
100
88
271
204
62
62
2.8%
PB2
PB3
PB4
PD1
summary
182
317
699
33
1956
0
71
71
20
269
1340
60.2%
53
2225
2.4%
100%
770
% of total
supply
34.6%
Objectives to serve
Employees
Figure 1. Distribution of parking demand
Emergency patients
only
Common patients and
their visitors
Others

III. FACTORS AFFECT THE PARKING PROBLEM IN
HUAXI HOSPITAL
r ( x0 , x1 ) 
A. Introduction about Grey Relational Analysis (GRA)
Grey relational analysis was pioneered by Deng Julong in
1984, which aims at analyzing the relationships among things,
having incomplete running mechanism, lacking of behavior
data, devoid of experience in treatment, being naked to
inherent connotation [10]. The basic steps and algorithms of
GRA are as follow[11]:

Step one, to define data series.
Assume X 0 = {X 0 (k) | k = 1,2, ^ , n} is a sequence of
data representing a system’s characteristics, and are
comparative series;

Step two, dimensionless treatment for data series.
X j (k ) 

x j (k )
x1 (1)
, k  1,2,, m
(1)
Step three, to calculate the grey relational coefficients.
By taking differences as Δ i (k) = | x 0 (k) - x1 (k) | , we thus
have the following difference series Δi (k). So the grey
relational coefficients are:
r ( x0 (k ), xi (k )) 
Step four, to calculate the grey relational grades.
min i min k  i (k )   max i max k  i (k )
(2)
 i (k )   max i max k  i (k )

1 n
 r ( x0 (k ), xi (k )), k  1,2,, n (3)
n k 1
Step five, to rank grey relational grades basing on the
size of r(x0, xi).
B. Factors Affect the Parking Problem of Hospital
The construction of supporting parking lots for hospitals
was restricted by the available land, cost, and location of the
hospital and has to take humanism landscapes into
consideration. While continuously increasing the supply of
parking resource is not the only or best way to solve the
problem [12]. The scale of parking lots of hospitals should be
fixed by taking a systematic investigation of the problem and
figure out the key factors. Figure 2 gives the analysis of the
factors concerning the parking problem of hospitals by using
fishbone chart [13] [14] [15].
Most of these factors should be considered at the
building’s planning and construction period to figure out the
appropriate capacity of parking places the hospital should
provide. According to the actual situation of Huaxi hospital,
factors change at the different period of the day are as fellow:
x1 parking demand of employees, x2 quantity of outpatients,
x3 cars on the road, x4 visitors of patients, x5 parking
efficiency, x6 traffic order, x7 level of supply saturation, x8
use turnover of parking lots.
Facilities Planning
Demand for Parking
Scale of Parking Lots
Barrier-free design
Quantity of Outpatients
scale of hospitals
Quantity of Visitors
Entrance and Exit
of Parking Lots
Humanism
Landscapes of Buildings
Building layout
and streamline design
Temporal Distribution
of Parking Demand
Rational Use
of Parking Places
Traffic Order
Public Transportation
Parking Problems
of Hospitals
Arriving Pattern of Patients
Cars on the Road
Charge
Efficiency Of Parking
Process for Parking
Quantity of cars kept
by residents in the area
Pedestrians in the area
Demand for
Parking of Employees
Management
Others
Figure 2. Factors concerning parking problems of hospitals
Guidance Measures
C. Grey Relational Analysis of Parking Problems
According to the survey in part II and the opinions of
the administrators, 7 typical periods of a specific day was
selected to analyze the parking problems using GRA. Ti (i
= 1, 2… 7) was defined to represent time period 07:0008:00, 08:00-09:00, 09:00-10:00, 10:00-11:00, 14:0015:00, 17:00-19:00, 20:00-21:00. Quantified data was
showed in table 2. Row x0 represents the level of difficulty
to park.
Fundamental Research Funds for the Central Universities
in Sichuan University.
REFERENCES
[1]
[2]
TABLE II.
RAW DATA OF PARKING ISSUE
[3]
T1
T2
T3
T4
T5
T6
T7
x0
1
0.8
0.6
0.4
0.8
1
1
x1
1
0.8
0.6
0.4
0.8
0.4
0.4
x2
0.4
1
1
1
1
0.8
0.4
x3
0.8
0.8
1
1
0.8
0.6
0.4
x4
0.2
0.4
1
0.8
0.8
0.4
0.2
x5
1
0.8
0.6
0.6
0.8
1
1
x6
1
1
0.6
0.2
1
1
1
x7
0.57
0.85
0.97
1
0.95
0.31
0.19
x8
0.5
0.5
0.8
1
0.8
0.5
0.5
[4]
[5]
The results of the calculation were listed in table 3,
including the ranking.
[6]
[7]
[8]
TABLE III.
GREY RELATIONAL GRADES
x0
x1
x2
x3
x4
x5
x6
x7
x8
r(x 0 ,x i ) 0.880 0.494 0.499 0.602 0.676 0.658 0.591 0.629
ranking
1
8
7
5
2
3
6
4
[9]
IV. CONCLUSIONS AND DISCUSSION
[10]
Because of the centralization and overlapping of
parking demand, the supply of parking places in Huaxi
hospital cannot meet the demand in peak hours. The
characteristics of different kinds of parkers are not
identical.
According to the calculation in part III, the most
significant factor affecting the parking issue of Huaxi
hospital is x1 (parking demand of employees), following
with x5 (parking efficiency) and x6 (traffic order). The
results of this paper may help administrators take some
targeted actions to make an optimization of the hospital’s
traffic situation. The affecting factors listed in the
fishbone chart may also provide a reference for architects
when they planning parking places of hospital buildings.
ACKNOWLEDGMENT
This research is funded by the National Nature
Science Foundation of China (71131006; 71020107027;
71192197), the Foxconn Technology Group’s Talent
Selection Research Program (11F81210101) and the
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