JOURNAL OF TRANSPORTATION
SYSTEMS ENGINEERING AND INFORMATION TECHNOLOGY
Volume 7, Issue 1, February 2007
Online English edition of the Chinese language journal
Cite this article as: J Transpn Sys Eng & IT, 2007, 7(1), 43−49.
RESEARCH PAPER
Urban Traffic Situation Calculation Methods Based on
Probe Vehicle Data
ZHANG Wei1,*, XU Jianmin1, WANG Haifeng2
1 College of Traffic and Communications, South China University of Technology, Guangzhou 510640, China
2 Guangzhou Traffic Information Investment Business and Management Limited Company, Guangzhou 510033, China
Abstract: Urban traffic situation information is the basis of effective traffic guidance and traffic control. It is usually expressed by
average speed and average travel time of the vehicles on the road. On the basis of the error analysis of the algorithms based on
average speed and average travel time, this article promoted the urban traffic situation calculation methods based on probe vehicle
data. And experiments were made based on probe vehicle data provided by the taxi management system of Guangzhou, China,
combined with the data by the method of vehicle license timing and vehicle following. The results proved that the method is quite
effective and practical.
Key Words: probe vehicle; urban traffic situation; average travel time; average speed
1
Introduction
With the development of the economy, the construction of
the road network can hardly meet the increasing traffic
requirements[1−4]. So, it is necessary to improve the service
level and transportation capacity by developing Intelligent
Transportation System (ITS). One of the important aspects of
service level is to guide the traffic flow properly. And
gathering information of urban traffic situation and forecasting
is the key problem[5].
Many researchers have focused on the urban traffic
situation calculation and gathering the information[6,7], but
they can hardly be implied in the urban traffic of China. From
the year 2003, Guangzhou began the construction of the Taxi
Management System, and now it has been applied on over
14,000 taxies in Guangzhou. The system can provide large
amount of probe vehicle data to support the urban traffic
situation evaluation.
Based on the construction of ITS demonstration project of
Guangzhou, this article has analyzed the errors of traffic status
expression using average speed and travel time, and advanced
the urban traffic situation calculation methods based on probe
vehicle data. Experiments have proved that the method is
quite effective and can be popularized.
2 The error analysis of the urban traffic situation
calculation methods
The traffic situation of a link in the road network can be
described by two factors. One is the average speed of the
probe vehicles on this link, and the other is the average
traveling time of probe vehicles.
2.1 Introduction of traffic situation calculation
Fig. 1
Vehicle positioning figure
As in Fig. 1, a probe vehicle sends two GPS data on A and
B. As map matching, its position can be got by the method
considering the distance and direction. For example, the
distance from point B to Jinzhong Road and Guangyuanzhong
Road are S2 and S3. Considering the direction of B, we know
Received date: 2006-12-06
*Corresponding author. E-mail: gzzhangwei@ tom.com
Foundation items: the National Natural Science Foundation of China (50578064).
Copyright © 2007, China Association for Science and Technology. Electronic version published by Elsevier Limited. All rights reserved.
ZHANG Wei et al. / J Transpn Sys Eng & IT, 2007, 7(1), 43−49
the probe vehicle is on the Jinzhong Road.
After completing the positioning, the traffic situation of the
road link can be described by the average speed of the probe
vehicles on it during certain time segment. But, as the speed of
probe vehicles has the characteristics of being instantaneous,
this method may lead to large error. And the average traveling
time can describe the traffic situation better.
Fig. 2
The method based on average time
As in Fig. 2, if a probe vehicle travels on the route SÆAÆB,
the traveling time of SÆA is RT1, the traveling time of AÆB is
RT2, and the total traveling time is T=RT1+RT2. If the probe
vehicle enters Guangyuanzhong Road at T0, and spends T1 as
traveling on Guangyuanzhong Road A, and gets to B after T2
as leaving Guangyuanzhong Road, then T=T0+T1+T2.
If we want to get T1 from RT1 and RT2, we need to know the
speed and time as the probe vehicle is at point A, and
distribute RT1 and RT2 to Guangyuanzhong Road A according
to the traffic situation of Guangyuanzhong Road. This is a
logic-model problem.
To avoid calculation of the complicated logic-model
problem, we can calculate the average speed V, according to
the distance of SÆAÆB and T, and assume the average time
of the probe vehicle on Guangyuanzhong Road A as T, and
then get T1.
2.2 Error analysis of the method based on average
speed
The main errors of the method in using the average speed to
describe the traffic situation are as follows:
(1) Instantaneous speed error
The instantaneous speed of the probe vehicle is irregular. If
during certain time, only one probe vehicle travels through the
road link, the average speed is the instantaneous speed of the
probe vehicle. That will lead to the large error.
(2) Statistical speed error
At the traffic jam situation, different probe vehicles are at
different positions, and their states are various. Then the
average speed will be higher than the real value.
(3) Position error
If the road link is relatively long and the entrance is in jam
and the exit is normal, then the probe vehicles on entrance
have higher speed and smaller GPS data number, and the exit
is on the opposition. So the average speed from entrance to
exit will descend faster than real value.
2.3 Error analysis of the method based on average
traveling time
The errors of evaluating traffic situation using average
traveling time are caused by the following factors:
(1) As to the method based on traveling time, errors may be
caused by different vehicles’ running situation since it is
necessary to enlarge part time.
If the vehicle is in jam road link at detecting time, the
average traveling time will be enlarged because of the less
average speed.
If the vehicle is at free road link at detecting time, the
average traveling time will be reduced because of the larger
average speed.
If the road traffic condition is becoming free or jammed, the
calculating precision will be hard to achieve because of the
change of the length of free road link and jammed road link.
(2) As to the position errors of the method based on average
speed, different probe vehicle will lead to different average
speed because the average speed of whole road link is
considered as the average speed of middle part of road link
and the traffic situation of different part of the road vary. The
error of the method can be calculated as following.
As in Fig. 2, if the traveling distance before entering
Guangyuanzhong Road section A is S0, average speed is V0,
traveling speed is T0, target road link length is S1, average
speed is V1, and traveling time is T1. The distance after leaving
target road link is S2, average speed is V2, and traveling time is
T2. Set the traveling time of SÆB to be S and average speed to
be V1.
2.3.1 Error analysis part one
Because the traveling time is equal, we can get:
S
V1
=
S 0 S1 S 2
+ +
V0 V1 V 2
(1)
Eq. (2) can be deduced.
1 S1 ⎛ S 0V2 + S 2V0 1 ⎞
= ⎜⎜
+ ⎟⎟
S ⎝ S1V0V2
V1 ⎠
V1
(2)
The average speed of target link can be expressed by
S V + S 2V0
1
S
=
− 0 2
V1 S1V1
S1V0V2
=
1 ⎛⎜ S S 0 S 2 ⎞⎟
−
−
S1 ⎜⎝ V1 V0 V2 ⎟⎠
Æ
S
1 1 S − S1 1
1 ⎛S
−
=
⋅ − ⎜⎜ 0 + 2
V1 V1
S1
V1 S1 ⎝ V0 V 2
S + S2 1
1
= 0
⋅ − (T0 + T2 )
S1
V1 S1
⎞
⎟⎟
⎠
(3)
As Eq. (3), the difference between real speed and average
speed has important relation to S1. The methods to reduce
error include increasing the rate of S1 in S and increasing
target link distance and decreasing T0 and T2. We can study the
problem on three conditions:
1) If V0 is much larger than V2, and S2 is usually small, then
S V + S 2V0
1
S
=
− 0 2
S1V0V2
V1 S1V1
≈
S
1
S
− 2 = (T − T2 )
S1V1 S1V2 S1
(4)
ZHANG Wei et al. / J Transpn Sys Eng & IT, 2007, 7(1), 43−49
2) If the difference between V0 and V2 is small, then
S V + S 2V0
S
1
=
− 0 2
V1 S1V1
S1V0V2
≈
S V + α ⋅ S 2V2
S ⎞
S
1⎛
− 0 2
= ⎜⎜ T − T 2 − 0 ⎟⎟
S1 ⎝
α ⋅ S1V2V2
α ⋅ V2 ⎠
S1V1
(5)
3) If V0 is much smaller than V2, S0 is usually small, then
S V + S 2V 0
1
S
=
− 0 2
V1 S1 V1
S1V0V 2
S0
S
1
(T − T0 )
≈
−
=
S1 V1 S1V0 S1
Table 1
(6)
No
So when we design arithmetic, it is better to choose the
starting point and ending point for calculated average
traveling time, which are adjacent to the target link and not on
the target link. If the entrance or exit of the link is in jam, we
can choose the starting point and ending point for calculated
average traveling time which are adjacent to the two end of
the target link.
2.3.2 Error analysis part two
According to the relation among speed, distance and time,
we can calculate the absolute difference between target link
speed and calculated link speed as mentioned below:
S1 S 0 + S1 + S 2 S1 (T0 + T2 ) − T1 (S 0 + S 2 )
−
=
T1 T0 + T1 + T2
T1 (T0 + T1 + T2 )
⎛ T0 + T2 S 0 + S 2 ⎞
⎜⎜
⎟
−
S1 ⎟⎠
⎝ T1
T (V − V0 ) + T2 (V1 − V2 )
= 0 1
T
=
S1
T0 + T1 + T2
(4) If the entrance and exit of the link are both free, V0 and
V2 are both large.
If the target link is free, the general error is small.
If the target link is in jam, the general error is negative, and
the absolute value is large. The average speed is smaller than
the real value.
Table 1 lists the effects of adjacent link speed difference on
(7)
As in Eq. (7), the difference between real speed and average
speed of the road link has direct relation to the error on the
adjacent link. There are several conditions:
(1) If the entrance and exit of the link are in jam, the
difference between V0 and V2 is not large, the error is mainly
affected by the average speed of the target link.
If the target link is in jam, error is small.
If the target link is free, the general error will be large, error
will be positive, and the average speed is smaller than the real
value.
(2) If the entrance of the link is in jam and exit is free, V0 is
much smaller than V2.
a) If the target link is free, the average speed is smaller than
real value because V1 is large and the error is mainly caused
by the jam.
b) If target link is in jam, the absolute value of V1－V2 is
big and the error may be negative, and the average speed is
smaller than the real value.
(3) If the entrance of the link is free and the exit is in jam,
V0 is much bigger than V2.
a) If the target link is free, the general error is small.
b) If the target link is in jam, the general error is negative,
and the average speed is larger than the real value.
The effects of adjacent link speed difference on average
speed and real value
Error of calculated value
and real value
Entrance link
Target link
Exit link
1
slow
slow
slow
small
2
slow
slow
fast
slightly large
3
slow
fast
slow
slightly small
4
slow
fast
fast
slightly small
5
fast
slow
slow
slightly large
6
fast
slow
fast
slightly large
7
fast
fast
slow
slightly small
8
fast
fast
fast
small
average speed and real value.
As in Table 1, affected by the adjacent link, the target link
traffic situation and calculation result will have accordant
error because the link traffic situation changes slowly. The
relation of links on intersection is hardly defined and the error
is hard to avoid.
The method is not sensitive to the continuity of the traffic
situation data. If the time estimation is carried out before
entering the target link, the veracity will be higher.
2.3.3 Error analysis part three
If the first sampling point is moved from entrance link to
target link, the absolute error between the speed of target link
and calculated link speed can be calculated according to the
relation of speed, distance and time.
S1 S1 − S 0 + S 2 S1 (T2 − T0 ) − T1 (S 2 − S 0 )
−
=
T1 T1 − T0 + T2
T1 (T1 − T0 + T2 )
⎛ T2 − T0 S 2 − S 0 ⎞
⎜⎜
⎟
−
S1 ⎟⎠
⎝ T1
T ⋅ V 1 − V1 + T2 ⋅ (V1 − V2 )
= 0 1
T1 − T0 + T2
=
S1
T1 − T0 + T2
(
(8)
)
V11 denotes the average speed from starting point to sampling
point. Table 2 can be obtained by the similar analysis method.
Because the connection between the front target link and
average speed of target link, we can assume that the general
speed of target link is slow if the speed of front target link is
slow, but the opposition is uncertainly true.
Table 2 The effects of exit link traffic condition on calculated result
No Front target link
Target link
Exit link
slow
fast
The error between real
value and calculated value
small
slightly large
slightly small
1
2
slow
slow
slow
slow
3
fast
slow
slow
4
fast
slow
fast
small
5
fast
fast
slow
slightly small
6
fast
fast
fast
small
ZHANG Wei et al. / J Transpn Sys Eng & IT, 2007, 7(1), 43−49
if T0 and S0 are both negative in Eq. (3).
The method requires that the data is continuous. If the data
of entrance link or exit link are absent, the error may be
obvious.
As in Table 2, exit link has relative stable effects on the
speed of the target link. As in Eq. (8), with the increasing
number of samples, T0 and T2, S0 and S2 will be balanced. In
fact, the speed at the entrance link is usually higher, and the
method can apply well. That is to meet the analysis of Eq. (3)
Get the No.i GPS data
not to be processed
Put GPS into save
queue
If status of GPS
is waiting for
pasengers
Yes
set process
queue empty
set the beingprocessed
GPS to be −1
No
i=i+1
set Gt to be
processed startpoint
GPS map matching
If the processing queue is
full and the first
unprocessed GPS is not null
Set the last-enteringqueue GPS to be the
first unproceesed one
(count:−1)
Yes
No
If the processing
queue is full
set the being-processed
GPS to be next one
Yes
No
Put Gi into processing
queue as Gt
If Gt is the first element
of queue
Yes
No
If time between Gt and Gt-1 is greater than
preset max time inteval
Yes
set the previous
GPS to be
processed GPS
No
Yes
If Gt and Gt-1 are on the same
road
set the same-road
flag of previous
GPS to be 1
Yes
If Gt-1 is the beingprocessed startpoint
set the current
GPS to be
processed GPS
Yes
No
No
No
work out the path
between Gt and Gt-1
and put that into Gt
If the previous GPS is
the original beingprocessed GPS
Update the road status of
path between Gt and Gt-n
If found the shortest path
No
Calculate the average
speed
Yes
Calculate the time inteval
between Gt and Gt-n
find the startpoint of
process
If there is another GPS
between current GPS and
the GPS being processed
Calculate the distance
between Gt and Gt-n
No
No
Yes
If there are several roads
between the being
processed GPS and the
one next to it
No
If the road of current
GPS and that of the
previous GPS are not
the neighbor
If the road list is
empty
No
put path into the
list
Yes
Yes
Put the roads
into update
list
other GPSs must be on the
same road where the one
next to processing GPS, so
put this road into update list
Fig. 3 Urban traffic situation model arithmetic
Yes
ZHANG Wei et al. / J Transpn Sys Eng & IT, 2007, 7(1), 43−49
According to the analysis above, the following problems
need to be solved to calculate the traffic situation based on
many probe vehicles’ data.
(1) Define the starting point: record the last GPS point
before entering the target link, including time T1, longitude
and latitude (x1, y1), and speed S1. This point is the starting
point.
(2) Define the ending point, which needs to meet the
following requirements: a) The distance between it and the
starting point is longer than target link. b) It is the first point
which meets the requirement a). In addition, it is necessary to
deal with some special conditions, for example, the vehicle is
waiting the passengers.
Urban traffic situation information is the key information of
ITS, and its calculation is the hot issue in ITS research field.
Based on the analysis of traffic factor errors, this article has
advanced the Urban Traffic Situation Calculation Methods
Based on Probe Vehicle Data, and promoted a new way to
collect and process urban traffic information. The method has
been applied in Guangzhou ITS demonstration project for two
years, and practice has proved that the method is quite
practical and applicable.
Jian she da ma lu
60
50
40
speed(km/h)
3 The urban traffic situation arithmetic based on
probe vehicle data
30
20
10
0
9:57:36
time
10:12:00
10:26:24
10:40:48
sample status
4 The traffic situation calculation and result
verification
processed status
Fig. 5-a Verification by vehicle following method part 1
dong fang zhong road
speed(km/h)
60
50
40
30
20
10
0
9:57:36
10:12:00
10:26:24
10:40:48
sample status
10:55:12
time
processed status
Fig. 5-b Verification by vehicle following method part 2
huan shi dong lu
speed(km/h)
To investigate the arithmetic above, authors have
considered two methods to do the experiment on some kinds
of roads of Guangzhou. One is vehicle license timing method,
the other is vehicle following method. And the experiment
result and calculated result were compared and later decided
whether they are coherent.
Because the jam has important effects on driving and
drivers, the deciding standards are various according to the
various traffic situation. Here, the region-dividing method is
adopted and various regions take different coherent coefficient.
The traffic situation evaluation standards in different speed
regions are shown in Fig. 4.
10:55:12
60
50
40
30
20
10
0
14:09:36
15:21:36
sample status
16:33:36
processed status
time
Fig. 5-c Verification by vehicle following method part 3
Fig. 4 Traffic situation evaluation standard
4.1 Verification result
According to the above evaluation standard, we compare
the traffic situation data obtained by vehicle following method
and model process. The result is: accordant records take 82.4
%, almost accordant records take 10.9 %, in accordant records
take 6.7, and acceptable records take 93.3 %. Fig. 5 illustrates
the comparison of the traffic situation data obtained by vehicle
following method and model process.
The result of verification by vehicle license timing method
is: acceptable records take 92.6 %, as illustrated in Fig. 6.
5
Conclusion
Speed(km/h)
Guang Zhou Da Dao Bei
60
50
40
30
20
10
0
14:24:00 14:52:48 15:21:36 15:50:24
sample status
time
16:19:12 16:48:00 17:16:48
processed status
Fig. 5-d Verification by vehicle following method part 4
Fig. 5-e Verification by vehicle following method part 5
ZHANG Wei et al. / J Transpn Sys Eng & IT, 2007, 7(1), 43−49
60
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xian lie zhong lu road
Forum, 2001, 12.
Speed(km/h)
50
40
[2] Xie Z D, Xu J M. ITS and urban construction of Guangzhou.
30
Electronic Technology Engineering, 2002, 1: 40−45.
20
10
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0
time
10:04:48 10:12:00 10:19:12 10:26:24 10:33:36 10:40:48 10:48:00 10:55:12 11:02:24 11:09:36 11:16:48
sample status
information
processed status
Fig. 6-a Verification by vehicle license timing method part 1
60
xian lie zhong lu road
in
Systems
Guangzhou
city.
Journal
Engineering
and
Information
of
Technology, 2006, 6(4): 119−24.
[4] Wang X J, Shen H F, Wang L. The study on China’s ITS
Development Strategy.
50
Spedd(km/h)
platform
Transportation
40
[5] Zhang Z, Xu J M. Dynamic route guidance using GPS equipped
30
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Conference on Electronic Measurement & Instruments, 2005,
0
time
14:16:48 14:24:00 14:31:12 14:38:24 14:45:36 14:52:48 15:00:00 15:07:12 15:14:24 15:21:36 15:28:48
sample status
8: 546−552.
processed status
Fig. 6-b Verification by vehicle license timing method part 2
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