Jordan Journal of Civil Engineering, Volume 10, No. 4, 2016
Analysis of Traffic Stream Characteristics Using Loop Detector Data
Hamid Athab Eedan Al-Jameel 1) and Mohammed Abbas Hasan Al-Jumaili 2)
1),2)
Assistant Professors, Civil Engineering Department, University of Kufa, Iraq.
ABSTRACT
Traffic congestion is one of the main problems in large urban cities. The evaluation of the performance of any
traffic facility, such as basic freeway segments, merging sections and diverging sections, depends mainly on
investigating the main relationships such as speed-flow and flow-occupancy. This study has focused on the
fundamental relationships of traffic stream, including flow-speed, flow-density, speed-density (Greenshield
relationships), headway-flow and flow-occupancy relationships. 24-hour data, each minute, from loop
detectors has been adopted to produce the above mentioned relationships. Field data has been collected from
two different sites in Manchester city in the UK. These are three-lane and four-lane sections. In some cases of
the current data, the behaviour has been investigated under 1min, 5min and 15min periods to show the
difference between various periods of data collection. The analysis of this data has revealed different
behaviours at different sections for each lane. The main use of this data is to provide the critical values which
are the basis for Intelligent Transportation System (ITS) applications, such as simulation models. This data
could be used for the calibration and validation of simulation models, such as S-Paramics or VISSIM, as well
as other developed models.
KEYWORDS: Field data, Occupancy-flow relationships, Speed-flow relationships, Simulation,
Calibration.
evaluation, design and planning. Therefore, getting
accurate data leads to accurate behaviour of the traffic
stream by the simulation models.
Among the important data related to the calibration
and validation processes are: speed-flow, flowoccupancy, flow-headway and flow-density data.
In addition to the well-known traffic relationships
(i.e., Greenshield relationships), the occupancy-flow
relationship has recently received a lot of attention.
Hall et al. (1986) stated that occupancy could be
defined as the percentage of time a traffic loop detector
embedded in the road pavement is occupied by
vehicles. The main importance of using occupancy lies
in the ease of measuring it from the loop detector.
Moreover, occupancy can be used to describe the
traffic conditions (i.e., normal or congestion) in the
same way as density (Hall et al., 1986).
INTRODUCTION
Road traffic assessment models depend mainly on
the cornerstone mathematical relationship between
speed and flow (Nielsen and Jorgensen, 2008).
Recently, a lot of simulation models have been
developed to represent different behaviours of traffic
characteristics, such as car-following models, lane
changing models, merging and diverging behaviours,...
etc. Among them are: (Zheng, 2003; Wang, 2006; Lee,
2008). The important point of using field data is to
calibrate and validate these models to verify whether or
not these developed models can mimic the reality.
Otherwise, these models can never be used in
Received on 17/1/2015.
Accepted for Publication on 3/3/2015.
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© 2016 JUST. All Rights Reserved.
Analysis of Traffic…
Hamid Athab Eedan Al-Jameel and Mohammed Abbas Hasan Al-Jumaili
Smaragdis et al. (2004) reported that the limit
between normal and congested traffic could be defined
as critical occupancy. The critical occupancy represents
the flow rate at capacity. Different values for critical
occupancy have been suggested by different
researchers. For example, a critical occupancy at loop
detectors located upstream of merge section, based on
data from Queen Elizabeth Way in Ontario, was found
to be 19% and 21% (Hall et al., 1986). The Minnesota
Department of Transportation used a value of 18% to
identify congested from normal conditions. Based on
simulation results, Sarintorn (2007) concluded that the
critical occupancy for the Pacific Motorway in
Australia ranged from 17% to 20%. Zhang and
Levinson (2010) used time occupancy to indicate the
occurrence of bottlenecks using data taken from loop
detectors in the USA. When occupancy is less than
20%, traffic is regarded as not congested; when
occupancy lies between 20% and 25%, the traffic is
regarded to be in the transitional phase, while the
congested phase is when occupancy exceeds 25%.
The aim of this study is to provide the main
relationships of traffic characteristics (field data), such
as speed-flow-density, occupancy-flow, flow-headway
relationships for each lane for different sections in each
1min and 5min periods. These relationships obtained
from field data may be suitable parameters for
calibration and validation of traffic simulation models,
which are nowadays widely used in evaluation,
analysis and planning for transportation system.
Data Collection
In this study, data from loop detectors located in the
UK have been collected. Two types of data were
obtained. The first source is from the Highway Agency
called Motorway Incident Detection and Automated
Signalling (MIDAS) data. This source provides
continuous data for each 1 minute. This data includes
flow rate, average speed, average headway and average
occupancy for each lane. Two sets of MIDAS data
have been collected from two loop detectors
(M60/9034B and M60/9030B), which are located on
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M60 in Manchester city on the first of October 2009.
The second source is the data taken from loop
detectors, which provide similar data to the MIDAS
data, but each second. This set of data has been
collected from M25 surrounding London city in May
2002. This raw data is from the M25 (four lanes) at one
point for both directions.
Speed-Flow Relationship
Before starting with investigating the speed-flow
relationship from MIDAS data for M60 J2-J3, it is
important to give more details about data at least for
one section. This section is a 3-lane section. Figure 1
demonstrates the total flow with heavy vehicle flow
(HGV). This figure indicates similar behaviour for the
rest sections. Speed and flow data for the same site
each 5min have been illustrated in the Appendix.
From Figure 1, one could draw a conclusion of how
the spread of vehicles with the flow is. For the first
lane and the second lane, the reduction in flow occurs
under 2000veh/hr; whereas for the third lane, the
relationship of speed-flow is more obvious than for
other lanes and no reduction in the flow occurs under
less than 2000veh/hr. In addition, the range of speed
variation in the first lane is the highest among the other
lanes; whereas for the third lane it is the lowest.
This interprets the normal behaviour due to the
variation of vehicle speeds using each lane. This
behaviour is similar to the fundamental relationship
suggested by Greenshield. This data was collected each
1 minute; therefore, it may be slightly higher than the
actual values. Moreover, the minimum observed speed
before reaching capacity is 100km/hr for the third lane,
but this value may be 60km/hr in the first and second
lanes. Figures 2, 3 and 4 indicate the field data for the
same section (M60). The capacity for the first lane is
up to 2200veh/hr for 1min, 2000veh/hr for 5min and
1800veh/hr for 15min. This is a good indicator that the
15min capacity value is the closet value to the
reasonable value without overestimation due to short
time period of calculation. However, the 1min and
5min calculations could be more suitable for
Jordan Journal of Civil Engineering, Volume 10, No. 4, 2016
calibration and validation of simulation models.
Having reported the capacity of the first lane, the
capacity of the second and third lanes at 15min
calculations
respectively.
is
1900veh/hr
and
2500veh/hr,
Figure (1): Flow for HGV and total flow for M60 in the UK
A.Three‐ lane section‐First lane
B. Three‐ lane section ‐Second lane 160
160
140
140
120
Speed (km/hr)
Speed (km/hr)
120
100
100
80
60
40
20
80
60
40
20
0
0
500
1000 1500 2000 2500 3000 3500
Flow (veh/hr)
0
0
500 1000 1500 2000 2500 3000 3500
Flow (veh/hr)
Figure (2): Speed-flow relationships for three-lane section (M60)
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Analysis of Traffic…
Hamid Athab Eedan Al-Jameel and Mohammed Abbas Hasan Al-Jumaili
Figure (3): Speed-flow relationship for three-lane section (M60) based on 5min calculations
The speed-flow relationship for the three-lane
section is similar to that of the four-lane section as
shown in Figures 5 and 6. However, the variations in
speed and flow in the first, second and third lanes are
more than those observed in the three-lane section.
In light of the relationships between speed and flow
for the 4-lane section close to the diverging section, the
same relationship is shown for the 4-lane section and
the normal section. Although the two sections are
different in characteristics, the relationship between
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speed and flow is still the same.
Flow-Occupancy Relationship
As previously mentioned, there is a range of
different values for critical occupancy according to site
conditions. The value of critical occupancy is 23% for
the first lane of the three-lane section as shown in
Figure 7; whereas the critical occupancy for the second
lane is 17%. The critical occupancy for the third lane is
20%. Fig. 8 shows the flow-occupancy relationship for
Jordan Journ
nal of Civil Eng
ngineering, Vollume 10, No. 4,, 2016
four-lane secction (M60) based on 1 minn calculations. It
is clear that there is a diffference in the critical valuues
or each lane.
fo
Figure (4): Speed-flow
S
reelationship forr three-lane section
s
(M60)) based on 155min calculattions
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Analysis of T
Traffic…
Hamid
d Athab Eedan
n Al-Jameel an
nd Mohammeed Abbas Hasa
an Al-Jumaili
Figure (5): Speed-flow relationship
r
foor four-lane section
s
(M60) based on 1m
min calculatio
ons
r
foor four-lane section
s
(M25) based on 5m
min calculatio
ons
Figure (6): Speed-flow relationship
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Jordan Journ
nal of Civil Eng
ngineering, Vollume 10, No. 4,, 2016
Figu
ure (7): Flow
w-occupancy relationship
r
f three-lanee section (M660) based on 11min calculattions
for
clear that the thhird lane carryying high flow
w rate has thee
lo
owest minimuum headway (around 1.2 sec),
s
whereass
th
he minimum headway
h
for thhe first lane is around 2 sec.
Based on thhese data, sevveral equation
ns have beenn
deerived for eachh lane as show
wn in Figures 9 and 10.
Theses equuations could be used forr comparisonn
with the equatiions producedd from simulaation models..
Moreover,
M
thee comparisonn could be implementedd
grraphically bettween the figuure produced by field dataa
an
nd that producced by simulattion data.
d
thhe critical occcupancy for the
t
Having determined
three-lane seection, the criitical values for
f the four-laane
section are 15%, 25%, 17%
1
and 22%
% for the firrst,
second, thirdd and four lannes, respectivvely (see Figuure
8). The variaation in the crritical values is
i clear for eaach
lane in the four-lane
f
secttion. These vaalues have beeen
determined from
f
data for each
e
1min.
Flow-Headw
way Relationsship
Figure 9 indicates that
t
as flow increases, the
t
correspondinng headway deecreases. Morreover, it sounnds
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Analysis of Traffic
T
…
Hamid
d Athab Eedan
n Al-Jameel an
nd Mohammeed Abbas Hasa
an Al-Jumaili
Figure (8): Floow-occupancyy relationship
p for four-lan
ne section (M
M60) based on
n 1min calcula
ations
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Jordan Journal of Civil Engineering, Volume 10, No. 4, 2016
Figure (9): Flow-headway relationship for three-lane section (M60) based on 1min calculations
Figure (10): Flow-headway relationship for four-lane section (M60) based on 1min calculations
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Analysis of Traffic
T
…
Hamid
d Athab Eedan
n Al-Jameel an
nd Mohammeed Abbas Hasa
an Al-Jumaili
Flow-Densitty Relationships
The flow
w-density reelationship iss one of the
t
fundamental relationshipss in traffic engineering. Looop
detector dataa revealed thhat the relatioonship betweeen
flow and density
d
has a similar beehaviour to the
t
Greenshield relationships. The critical density
d
could be
defined as thhe optimum value
v
of densiity at which the
t
flow rate reaches the maaximum valuee. According to
t critical values
v
of dennsity determinned
Figure 11, the
from loop deetector data are higher thann those reportted
by the Highhway Capacitty Manuals HCM
H
2000 and
a
HCM 2010 for the basic freeway seegment. This is
because the overestimatioon values aree: 36veh/km for
f
the first lanne, 34veh/km
m for the seecond lane and
a
35veh/km foor the third lanne. Consequently, there is no
direct data for
f density whhich could bee obtained froom
the loop deetectors. Thee relationshipps indicated in
Figure 11 haave been obtaained from dividing flow by
speed accordding to the Greenshield relationship for
f
each lane. Moreover,
M
gettting a density from field daata
is a difficult task and is noot practical.
Due to 1min
1
calculatiions as previoously discusseed,
the relationship based onn 5min calculations has beeen
s
in Figuure 12. Therefore, the criticcal
obtained as shown
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ond lane andd
vaalues of denssity for the fiirst lane, seco
th
hird lane are: 29veh/km, 26veh/km an
nd 30veh/km,,
reespectively. These
T
values are close to
t the valuee
reeported by the HCM, whichh is 28veh/km for the upperr
lim
mit of the capacity level.
m
Another traaffic behaviouur could be noticed from
Fiigures 11 andd 12. This behhaviour repressents how thee
diissipation in fllow with denssity will be beefore and afterr
th
he optimum density. For example, th
he differencee
beetween flow for
fo the first lanne ranges from
m 2100 veh/hrr
to
o 900 veh/hr; whereas
w
for thhe second lanee the range off
flo
ow is from 24400 veh/hr to 540veh/hr. Finally, for thee
th
hird lane, thiis vale rangees from 290
00 veh/hr too
84
40veh/hr. The dissipation at 1min period increases
i
from
m
lan
ne 1 to lane 3.
3 This could bbe attributed to
t the level off
sp
peed and flow
w at each lanee. According to
t speed-flow
w
daata as in Figurres 2 and 3, thee main interprretation of thiss
ph
henomenon is that the disrup
uption in trafficc occurs moree
seeverely at the lane which caarries high flo
ow and speed..
To
o obtain moree accurate behhaviour from the
t field data,,
5m
min data analyysis has beenn adopted to find
f
the flow-deensity relationnships as demoonstrated in Figure
F
12. Thee
saame behaviourr is observed fo
for 1min data analysis.
a
Jordan Journ
nal of Civil Eng
ngineering, Vollume 10, No. 4,, 2016
A..Three-lane section-First
s
llane -5min
3500
B.Three-lan
ne section -Second lane - 5min
35500
3000
30000
Flow (veh/hr)
Flow (veh/hr)
Figgure (11): Floow-density reelationship foor three-lane section (M600) based on 1m
min calculations
2500
2000
1500
1000
25500
20000
15500
10000
500
5
500
0
0
0
10
20
30 40 50
5
60
D
Density
(veh//km)
70
80
0
10
20
30
4
40
50
60
70
Density ((veh/km)
Figgure (12): Floow-density reelationship foor three-lane section (M600) based on 5m
min calculations
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80
Analysis of Traffic
T
…
Hamid
d Athab Eedan
n Al-Jameel an
nd Mohammeed Abbas Hasa
an Al-Jumaili
On the other hand,, Figure 13 indicates the
t
relationship of flow- denssity for the foour-lane sectioon.
There is a cllear dissipatioon in the flow data, especiaally
or the fourth lane, which is the higheest differencee
fo
beetween the maaximum and m
minimum valu
ues (i.e., from
m
31
100 veh/hr to 600veh/hr).
6
Fiigure (13): Fllow-density reelationship foor four-lane section
s
(M60)) based on 1m
min calculatio
ons
DISCUSSION
The relattionships indiccated in Figurres (2-12) couuld
be used as calibration annd validation parameters for
f
simulation models, likke S-Param
mics, VISSIM,
AIMSUN annd other deveeloped modelss, such as thoose
models deveeloped by Bennkohal (1986)), Zheng (20003)
and Wang (22006). In thesse models, thee calibration and
a
validation paarameters are flow-speed, flow-occupanncy
and flow-heeadway relatiionships. Othher parameteers,
such as vehiccle trajectoriees, lead gaps and
a lag gaps are
a
also includedd.
- 414 -
The currentt study demoonstrates the basic speed-flo
ow relationshhip. This relattionship has been
b
stated att
1m
min, 5min and 15min periods. The variiation in timee
peeriod will helpp more in testiing a develop
ped simulationn
model.
m
Moreovver, field daata for each lane is alsoo
im
mportant in terms of caalibration an
nd validationn
prrocesses to make
m
sure that a tested simu
ulation modell
mimics
m
the reaal data. In soome relationsh
hips, such ass
flo
ow-occupancyy and flow-density relationships, thee
crritical values are the mainn important points.
p
Flow-heeadway relattionship is calibrated as
a graphicall
beehaviour.
Jordan Journal of Civil Engineering, Volume 10, No. 4, 2016
behaviour. However, there is a difference in the
minimum headway across the different lanes. The
minimum value for the right lane is around 1.2sec;
whereas it is about 2.0sec for the left lane.
4. The resulting relationships from this study could be
used for calibration and validation in terms of
microscopic and macroscopic levels, such as flowheadway, speed-flow, flow-occupancy and flowdensity relationships.
CONCLUSIONS AND RECOMMENDATIONS
In light of the previous results and discussion, the
study arrived at the following conclusions and
recommendations:
1. Field data revealed that the speed-flow relationship
obtained from the highest speed lane is more close
to the Greenshield relationships than those obtained
from the lower speed lanes.
2. The critical values of occupancy for different
sections vary from 19% to 25% as reported by
previous studies.
3. The headway-flow relationships obtained from the
different sections show approximately the same
Acknowledgement
The authors would like to thank the Iraqi Ministry
of Higher Education and Scientific Research for giving
the opportunity to get the current data from the UK.
Appendix
Speed and flow data each 5min for M60 J2-J3 (1st October 2009)
Time
00:00
00:05
00:10
00:15
00:20
00:25
00:30
00:35
00:40
00:45
00:50
00:55
01:00
01:05
01:10
01:15
01:20
01:25
01:30
01:35
01:40
01:45
01:50
01:55
02:00
02:05
02:10
02:15
02:20
02:25
02:30
First lane
Second lane
Flow
Speed
Flow
Speed
(veh/hr) (km/hr) (veh/hr) (km/hr)
120
82.4
204
115.6
264
99.4
264
116.4
180
101
252
110
240
96
276
123
252
100.2
240
112.2
204
99.8
192
110.6
264
98.8
192
111.2
216
97
228
86.6
180
93.4
132
111.8
312
102.2
108
92.2
264
98
204
113.6
192
103.2
84
115.4
204
96.4
192
110.4
120
96.2
168
110.4
228
90.2
156
107.4
108
92.8
24
44.8
144
101.8
120
88.2
168
99.2
72
93
216
96.4
156
113
204
97.8
120
111.4
144
93
84
100.6
192
103.2
120
91.8
144
98.8
156
98.2
132
82.4
60
94.4
84
81.4
36
74.6
108
69
48
100.4
84
99
60
38.4
96
90.2
60
61.8
108
83.4
12
24
180
103.8
108
85.4
180
101.2
108
117.4
Third lane
Flow
Speed
(veh/hr) (km/hr)
24
52
24
49.2
24
59
36
25
36
71
36
52.6
36
76.8
36
46.6
0
0
0
0
12
27
0
0
24
48.4
12
25
12
25
12
27
12
24
0
0
12
25
0
0
0
0
12
24
12
26
12
26
0
0
0
0
12
23.2
12
21
12
25
12
25
12
27
Time
04:50
04:55
05:00
05:05
05:10
05:15
05:20
05:25
05:30
05:35
05:40
05:45
05:50
05:55
06:00
06:05
06:10
06:15
06:20
06:25
06:30
06:35
06:40
06:45
06:50
06:55
07:00
07:05
07:10
07:15
07:20
- 415 -
First lane
Flow
Speed
(veh/hr) (km/hr)
312
97.6
252
95
312
97.4
288
91
360
91.6
324
100.2
348
91
384
90.8
528
93.6
492
96
540
99.8
408
100
492
96.2
468
92.2
504
91
576
92.4
576
96.8
552
94
696
96.8
720
92.8
756
89.2
864
91
948
89.4
876
88.2
1140
87
1296
88.2
1104
86.4
1272
87.4
1368
83.2
1644
83
1512
82.2
Second lane
Flow
Speed
(veh/hr) (km/hr)
96
69
108
94.2
120
90.4
108
67.6
168
92.4
108
91.8
204
91.6
372
112.2
420
115.4
276
113.8
480
116
288
119.4
336
114.8
396
116.6
432
111.2
504
111
648
111
540
113.8
744
114.6
756
107.4
912
107.2
996
107
1188
106.4
1380
99.6
1224
101.8
1296
101.6
1488
101.4
1608
99.8
1740
96.6
1668
94.4
1740
94.2
Third lane
Flow
Speed
(veh/hr) (km/hr)
36
48.2
0
0
12
28.2
0
0
0
0
0
0
24
46.4
48
48.2
60
76
12
22.4
60
45.4
96
77
24
51.4
48
78
84
46.6
108
120
276
96.2
192
127
192
123.4
372
120
492
119.4
624
120.6
804
117.4
972
113.2
1224
115.8
1116
115.2
1476
114.4
1680
110.6
1872
108.4
1944
108
2172
104
Analysis of Traffic…
Hamid Athab Eedan Al-Jameel and Mohammed Abbas Hasan Al-Jumaili
02:35
02:40
02:45
02:50
02:55
03:00
03:05
03:10
03:15
03:20
03:25
03:30
03:35
03:40
03:45
03:50
03:55
04:00
04:05
04:10
04:15
04:20
192
132
180
108
120
180
252
192
192
144
72
96
132
144
168
168
120
216
288
180
204
204
97.2
97.4
78.2
98
97.6
102
94.2
96.4
97.2
100.8
75.4
66.8
94.8
95.8
98.4
92.6
104
96.4
96
101.6
96.6
97.8
72
36
84
96
72
48
36
120
84
84
84
48
180
48
60
60
60
72
72
84
96
108
84.2
38.2
68.8
71
67.6
64.6
48.6
86
121.6
46
91.6
70.2
94.2
66.6
84.8
64.6
70.2
92.2
89.6
63.8
89.6
114.8
12
12
0
12
12
0
0
12
24
12
0
0
12
12
12
0
0
0
0
0
12
12
24
26
0
24
24
0
0
24
53.2
27
0
0
23.2
25
27
0
0
0
0
0
21.6
29.4
04:25
120
92.6
60
41.6
12
25
04:30
252
103
168
94.2
12
26
04:35
300
101.2
132
124.8
0
0
04:40
312
100.2
72
96
0
0
04:45
252
99
120
95.2
12
21.6
07:25
07:30
07:35
07:40
07:45
07:50
07:55
08:00
08:05
08:10
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- 416 -
1308
1644
1656
1740
1896
1836
1644
1584
1536
1716
83
82.4
78
54.6
66
60.8
71.4
78.2
79.8
63.2
1848
1884
1932
1896
1896
1956
1992
1716
1824
1908
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85.6
57.2
72
65.2
78
87
89.2
69.8
2136
2244
2520
2112
2532
2520
2520
2244
2280
2544
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93.4
60
75.4
67.4
85.8
95.2
98
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