This document presents a queueing analysis of two intersections in Bangalore, India using VISSIM microsimulation software. The methodology involved collecting field data on traffic volumes, speeds, vehicle classifications and signal timings. This data was used to calibrate the VISSIM model and compare simulated delays and queue lengths to observed field measurements. The results showed that VISSIM was able to accurately replicate existing conditions and could be used to test potential improvements like modified signal timings.

1. A presentation on
QUEUEING ANALYSIS USING VISSIM
SOFTWARE
Under the guidance of
Internal guides :
Rahul L Kadam
Assistant professor
Dept. of Civil Engineering, RITM, Bengaluru.
by
Ramkrishna P Jagali
USN : 1RE14CTE12
P S Reddy
P.G Coordinator
Dept. of Civil Engineering, RITM,
Bengaluru.
1

2. Contents
• Introduction
• Methodology
• Literature review
• Study location
• Data collection
• Data analysis
• Results
• Conclusions
• References
2

3. Introduction
The growth in urban traffic has been recognized as serious problem
in metropolitan areas in the country, with significant effect on
economy, travel behavior, land use and cause of discomfort for
millions of motorists.
Bangalore today is obviously one of the most sought after cities in
the country what with the rapid growth in the IT industry and the
rise in the number of job opportunities in the city.
With the rising population there is also a corresponding increase in
number of vehicles in the city and huge increase in the demand in
land.
What adds to the traffic pressure in Bangalore in particular is that
there is very little scope for expansion of roads and the need to use
existing roads for smooth movement of vehicles is even more
pronounced.
3

4. Continued..
 It thus becomes mandatory for the administration to ensure better
parking facilities.
According to BTRAC-2010 website rapid population growth
because of IT and other associated industries in Bangalore has led
to an increase in the vehicular population to about 1.5 million,
with an annual growth rate of 7-10%.With the increase in
population and the expansion of the city, the problem of
connectivity of the populace has arisen.
 Quite obviously personalized modes of transport have grown at a
tremendous rate and two wheelers along with the cars almost
comprise 90% of the total registered vehicular population in the
city. Two wheelers constitute more than 70% of the total volume,
while cars comprise 15%, autos 4% and the remaining 8%
includes other vehicles such as buses, vans and tempos.
4

5. V/C ratios of different roads of Bangalore (Source: BTRAC
website)
5

6. Composition of vehicles in Bangalore City (Upto 31-12-2009)
In peak hours, travel speed will be below 15 kmph.
On street parking is more because lack of parking space.
Immense increase of Private Vehicles on road, reducing the space
for Public Vehicles.
6

7. Objectives
 To obtain the PCU values at selected intersections.
 To Understand the driver behavior by measuring the Discharge
speed in the field
 To measure saturation flow of the approaches.
 To compare the delays obtained using micro simulation software,
VISSIM with the observed field delays.
7

8. Methodology
Intersection
geometry study
Signal cycle
study
Volume
study
Driver
behavior
study
Delay study
8

9. Literature review
 Sarna and Malhotra (1967) have developed the relationship
between the saturation flow and the approach road width at
signalised intersection. The results had showed that the
saturation flow increases with the increase in approach
volume.
 Gopal patil et.al (2007) have developed regression models in
his study to estimate saturation flow at signalized intersections.
The model was developed and validated on the basis of data
collected from Mumbai, India. They remarked that PCU
calculation is uneven at the selected intersections.
 Shuguo Yang et.al (2014) have sets up the queuing model,
analyses the traffic flow of Shenzhen intersection through
analyzing the queuing theory deeply, and uses the model to
analyze the settings of the lane that based on the certain degree
of accuracy. 9

10. Study Location
Signalized intersections are important crossing
points in transportation network and their
productivity of operation greatly influences the
entire transportation network performance.
Following are the intersection selected for the
study;
Vijayanagar TTMC Intersection
Attiguppe Metro Station Intersection
10

11. Intersection at Vijayanagar TTMC
11

12. Intersection at Attiguppe Metro Station
12

13. Data collection
Types of surveys conducted
Road inventory survey
Road width, carriageway width, footpath width
No of Lanes, Lane width, Approach width
Traffic survey
Classified volume count
Spot speed study
Traffic signal survey
13

14. Classified volume count
Video camera was used to do the classified traffic
volume count on the field. Video based method
minimizes the human errors and overcomes the
difficulties in collecting traffic information.
Advantages of Video graphic method;
 It is unobtrusive and requires small labour power
 It produces permanent, complete record of the
traffic scene
 Recording may be re-analysed at any stage
14

15. Spot speed study
Stop watch method is used.
15

16. Data analysis
Geometric and signal cycle details
Intersection Study Approaches Area type Carriagew
ay width
(m)
Cycle time (sec) Green excluding
amber (sec)
Vijayanagar TTMC
Intersection
From Vijayanagar CBD 7.5 167 45
From Attiguppe
Metro Station
CBD 7.5 167 35
From RPC Layout CBD 6.0 167 20
From Marenahalli CBD 6.0 167 25
From TTMC CBD 7.0 167 27
Attiguppe Metro
Station
From Vijayanagar CBD 7.5 120 40
From
Deepanjalinagar
CBD 7.5 120 40
From Chandra
Layout
CBD 7.0 120 95
16

17. Signal Phase details at Vijayanagar TTMC
intersection
Phase
Study Approach 1 2 3 4 5 Cycle
time
From Vijayanagar R L S
167
From Attiguppe Metro
Station
R L S
From RPC Layout R L S
From Marenahalli R L S
From TTMC R S
27 25 45 35 20
17

18. Signal Phase details at Attiguppe Metro
Station intersection
Phase
Study Approach 1 2 3 Cycle time
From Vijayanagar R L S
120
From Deepanjalinagar R L S
From Chandra Layout R L S
40 40 31
18

19. Vehicle composition and turning movements at
Vijayanagar TTMC intersection
19

20. Vehicle composition and turning movements
at Attiguppe Metro Station intersection
20

21. Estimated PCU Values
TYPE OF
VEHICLE
MEAN SPEED
(kmph) Vs
Vs/Vi As/Ai PCU PCU
Car 41.43 1 1 1 1
Two wheelers 35.04 1.182363014 4.491666667 0.263234808 0.3
Truck 37.78 1.096611964 0.305902384 3.584842821 3.6
Bus 38.94 1.06394453 0.217865804 4.883485654 4.9
LCV 33.47 1.237824918 0.420765027 2.941843636 2.9
Auto 32.56 1.272420147 1.203125 1.057595967 1.1
Cycle 13.32 3.11036036 6.341176471 0.490502098 0.5
Mini Bus 35.23 1.175986375 0.331081081 3.551958848 3.621

22. Vehicle dimensions Considered for PCU
Calculation
Category of vehicle Average dimensions (m)
Projected area on
ground (m2)
Length width
Car 3.72 1.44 5.39
Two wheelers 1.87 0.64 1.2
Truck 7.5 2.35 17.62
Bus 10.1 2.43 24.74
LCV 6.1 2.1 12.81
Auto 3.2 1.4 4.48
Cycle 1.9 0.45 0.85
Mini Bus 7.4 2.2 16.28
22

23. Queue delay
23

24. 24

25. Saturation flow
25

26. Continued..
26

27. Saturation flow measured flow
Name of Intersection Lane Group Average
Saturation
Flow in
veh/hr
Width in m Volume in
veh/hr
Vijayanagar TTMC
intersection
From Vijayanagar
3196
7.5 3292
From Attiguppe Metro Station 3196 27277.5 3256
From RPC Layout 2604 6.0 525
From Marenahalli
2692
6.0 527
From TTMC
104
7.0 76
Attiguppe Metro Station
intersection
From Vijayanagar
2966
7.5 2611
From Deepanjalinagar
2978
7.5 2649
From Chandra Layout
2890
7.0 2150
27

28. VISSIM Inputs
Geometric features of road
Vehicle category
Traffic volume
Vehicle routing
Vehicle composition
Signal time
28

29. Signal time
29

30. Results
Vijayanagar TTMC Intersection - Existing
30

31. Vijayanagar TTMC Intersection – Proposal
31

32. Queue delay Results
Count
Time
Interval
Data Collection
Measurement
Accelera
tion
Distance Length
Queue
Delay
Speed
Queue
Delay
Speed
1 0-3600 Marenahalli-1 0.11 527.08 4.42 442.36 38.07 146.92 36.41
1 0-3600 Marenahalli-2 0.09 544.66 2.96 423.81 38.73 138.85 36.59
1 0-3600 RPC Layout-1 0.15 473.04 7.86 226.22 42.76 161.51 38.22
1 0-3600 RPC Layout-2 0.13 539.98 3.68 357.51 38.56 188.34 38.36
1 0-3600 Vijayanagar-1 0.54 758.84 5.83 278.48 38.21 127.72 36.36
1 0-3600 Vijayanagar-2 0.42 784.80 3.02 346.43 34.07 182.90 32.84
1 0-3600 Attiguppe-1 0.40 735.95 2.83 429.81 34.99 166.49 36.02
1 0-3600 Attiguppe-2 0.60 771.38 3.93 467.33 35.98 213.35 36.17
32

33. Queue delay Results
0.00
100.00
200.00
300.00
400.00
500.00
600.00
700.00
800.00
900.00
Acceleration
Distance
Length
Vehicles
QueueDelay
Speed
Linear (Distance)
0.00
100.00
200.00
300.00
400.00
500.00
600.00
700.00
800.00
Series1
Series2
Series3
Series4
Series5
Series6
33

34. Queue length results
Table 4.8 TTMC Intersection Existing – Queue length results
Count Time Interval Queue Counter Queue
Length
Queue Length
Max
Queue
Length
Queue
Length
Max
1 0-3600 Attiguppe 314.09 355.49 54.49 161.68
1 0-3600 Vijayanagar 424.71 476.63 118.63 255.48
1 0-3600 TTMC 54.57 152.22 12.95 67.69
34

35. Queue length results
0
500
1000
1500
2000
2500
3000
1: Attiguppe 2: Vijayanagar 3: TTMC
Q_Length
Q_LengthMax
Q_Stops
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Attiguppe Vijayanagar TTMC
Q_Length
Q_LengthMax
Q_Stops
35

36. Travel time results
Table 4.9 Vijayanagar TTMC Intersection Existing – Travel time results
Coun
t
Name Distance (m) Distance
Travel Time
(sec)
Speed (m/s)
Travel Time
(sec)
Speed (m/s)
1 0-3600 Attiguppe BX 343.13 435.40 0.79 135.21 2.54
1 0-3600 Attiguppe AX 465.06 76.79 6.06 67.66 6.90
1 0-3600 Vijayanagar BX 466.52 603.85 0.77 311.89 1.49
1 0-3600 Vijayanagar AX 345.12 53.22 6.49 45.71 7.55
36

37. Travel time results
0.00
50.00
100.00
150.00
200.00
250.00
300.00
350.00
400.00
450.00
500.00
Attiguppe BX Attiguppe AX Vijanagar BX Vijayanagar
AX
Distance
TravelTime (sec)
Speed (m/s)
0.00
100.00
200.00
300.00
400.00
500.00
600.00
700.00
Attiguppe BX Attiguppe AX Vijayanagar BXVijayanagar AX
Distance
TravelTime (sec)
Speed (m/s)
37

38. Attiguppe Metro Station Intersection – Existing
38

39. Attiguppe Metro Station Intersection - Proposal
39

40. Queue delay results
Coun
t
Time
Interval
Data Collection
Measurement
Acceleration Distance Length
Queue
Delay
Speed
Queue
Delay
Speed
1 0-3600 Chandra Layout-1 0.593372 538.8475 2.676744 171.84 32.00 173.46 31.99
1 0-3600 Chandra Layout-2 0.534684 493.5409 2.649289 168.14 31.88 166.52 31.85
1 0-3600 Deepanjalinagar-1 0.515374 499.4688 2.819426 153.93 32.46 153.05 32.49
1 0-3600 Deepanjalinagar-2 0.529792 659.033 2.915383 180.59 32.15 0.01 46.47
1 0-3600 Vijayanagar-1 0.511549 665.4033 2.553224 172.77 32.04 0.24 32.04
1 0-3600 Vijayanagar-2 0.5496 528.4226 2.986568 163.71 31.49 161.48 31.49
40

41. Queue delay results
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Acceleration
Distance
Length
Vehicles
QueueDelay
Speed
0
100
200
300
400
500
600
700
Acceleration
Distance
Length
Vehicles
QueueDelay
Speed
41

42. Queue length results
Count Time Interval Queue Counter Queue
Length
Queue Length
Max
Queue
Length
Queue
Length
Max
1 0-3600 Vijayanagar 258.68 316.03 0.23 74.39
1 0-3600 Deepanjalinagar 284.96 342.69 0.00 0.00
42

43. Queue length results
0
10
20
30
40
50
60
70
80
Vijayangar Deepnajalinagar
Q_Length
Q_LengthMax
Q_Stops
0
200
400
600
800
1000
1200
1400
1600
1800
2000
Vijayangar Deepnajalinagar
Q_Length
Q_LengthMax
Q_Stops
43

44. Travel time results
Count Name Distance (m) Distance Travel Time (sec) Speed (m/s)
Travel Time
(sec)
Speed (m/s)
1 0-3600
Deepanjalinagar
BX 303.61 229.43 1.32 66.53 4.56
1 0-3600
Deepanjalinagar
AX 332.73 57.88 5.75 60.95 5.46
1 0-3600 Vijayanagar BX 331.09 244.14 1.36 37.40 8.85
1 0-3600 Vijayanagar AX 302.90 52.41 5.78 33.04 9.17
44

45. Travel time results
0
50
100
150
200
250
300
350
Deepanjali BX Deepnajali AX Vijayanagar BX Vijayanagar AX
Distance
TravelTime (sec)
Speed (m/s)
0
50
100
150
200
250
300
350
Deepanjali BX Deepnajali AX Vijayanagar BX Vijayanagar
AX
Distance
TravelTime (sec)
Speed (m/s)
45

46. Conclusions
 The field delay measured shows that all the approaches
considered for the present study have a level of service F.
The v/c ratios of the approaches are also less than one
and good progression is observed during green cycle.
 The field delay measured shows that all the approaches
considered for the present study have a level of service B.
The v/c ratios of the approaches are also less than one
and good progression is observed during green cycle.
 Queue delay, Queue length and Travel time have been
reduced and level of service also increased from F to B.
46

47. References
• Shuguo Yang, Xiaoyan Yang., “The Application of the Queuing
Theory in the Traffic Flow of Intersection”, World Academy of
Science, Engineering and Technology International Journal of
Mathematical, Computational, Physical, Electrical and Computer
Engineering Vol:8, No:6, 2014
• Anusha, C. S., Ashish Verma, and G. Kavitha. "Effects of Two-
Wheelers on Saturation Flowat Signalized Intersections in
Developing Countries", Journal of Transportation Engineering,
2013.
• Ahmad Sadegh and A. Essam Radwan, (1988) “Comparative
Assessment Of 1985 Hcm Delay Model” Journal of
Transportation Engineering, Vol. 114, No. 2, March, 1988.
• Ragab M. Mousa (2002), “Accuracy of Stopped Delay Measured
by Stopped-Vehicle Counts Method” Journal of Transportation
Engineering, Vol. 128, No. 5, September 1, 2002. ©ASCE.
47