Description
COURSE PROJECT TOPIC-
Traffic simulation at Toll road section using PTV Vissim Software • Group Members- Shrikrishna Kesharwani (22CEM3R23) Abhishek Singh Baghel (22CEM3R02) Transportation Division Department of Civil Engineering NIT Warangal Academic Year-2022 1
FLOW OF PRESENTATION
LITERATURE REVIEW
INTRODUCTION
RESULTS
METHODOLOGY FOLLOWED
ISSUES
C O N C L U S I O N
22
INTRODUCTIONOBJECTIVES-
• To create a traffic simulation model that properly simulates a toll road stretch using PTV Vissim software. • To verify the model's correctness by comparing the simulation results with actual traffic data, if any is available SCOPE-
• The goal of this research is to simulate traffic flow on a segment of a toll road using PTV Vissim software by incorporating driver behaviours. • The outcomes of the simulation like Volume, delay etc. will be used to determine LOS of toll plaza as well as to compare the field and simulated result values.
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LITERATURE REVIEW TITLE
AUTHOR
SUMMARY
• Use of Microscopic Traffic Simulation Software to Determine Heavy-Vehicle Influence on Queue Lengths at Toll Plazas
Mahdi et al. (2019)
•
• Simulation of Traffic Operation and Management at Malaysian Toll Plazas using VISSIM
Hilmy & Hamid (2011)
•
The toll plaza model was constructed by using desired speed and service time as a key parameter and after comparing model MOE (Measure of Effectiveness) to the existing MOE. T test Analysis was done was done and the same desired speed and service time parameters were used to calibration of the model.
In order to obtain outputs like total delay, average delay, average number of vehicles processed per booth, and total number of vehicles processed at toll plazas. The study evaluated a number of input parameters, including vehicle volumes, the number of toll booths, the size of the waiting area, the types of payment systems, and traffic access arrangements.
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LITERATURE REVIEW TITLE
Examining the effect of Electronic Toll collection system on queue delay using microsimulation approach at toll plaza: A case study of Ghoti toll plaza , India
AUTHOR
SUMMARY
• Bari et al. (2021)
• •
• Analysis of Toll Station Operations in SriLanka using a Micro-Simulation Technique
Vidanapathirana & Pasindu (2017)
• •
Explores the potential impact of an Electronic Toll Collection (ETC) system on queue delay at a toll plaza in India. For calibration of the model Average Standstill Safety distance was used. Wiedemann 74 vehicle following model was used.
The data collected was AADT and Vehicle composition during the peak hour For System calibration, Speed, Traffic flow, Routing choice and Geometry were calibrated For operational calibration Car following, Lane change behavior and Lane change distance were used..
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LITERATURE REVIEW TITLE
AUTHOR
SUMMARY
• Optimizing and Modelling Tollway Operations Using Microsimulation.
A simulation Based study for the Optimization of Toll Plaza with Different Lane Configuration: A Case Study of Ravi Toll Plaza Lahore, Pakistan
Bains et al. (2017)
Ahmad et al. (2021)
•
•
CALIBERATION PARAMETERS
Scenario using NPRT help in decreasing queue length and also reduce delay and increase volume per hour. While scenario 2 result was not good it was based on segregating lanes for HV and car for improving level of service and decreasing conflicts but due to segregation of lanes volume decrease and queue length increased.
• • • •
Average standstill safety distance Keep lateral distance from vehicle Minimum lateral distance Minimum lateral distance
Result shows that using E-tag in lanes gives improvement of 75.9 %, 93.6% and 57.7% in throughputs, waiting time & queue length respectively.
• • •
Maximum speed of the vehicle Average standstill safety distance The actual speed and acceleration of the vehicle in the road network
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LITERATURE REVIEW TITLE
Operational Optimization of Toll Plaza Queue length Using Microscopic Simulation VISSIM Model.
AUTHOR
Mittal & Sharma (2022)
SUMMARY
•
The model's application as toll plaza designing is also studied after evaluating the number of toll lanes depending on minimum queue length and minimum waiting time criteria.
CALIBERATION PARAMETERS
• • • •
Average standstill safety distance Keep lateral distance from vehicle Minimum lateral distance Minimum lateral distance
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METHODOLOGY-
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DATA COLLECTIONay w A n- era o cti m ri e Ca D om Fr n- he o cti T re ards i D w ra To me Ca
• There are 8 toll booths in the model through which vehicles are passing as can be seen in the CCTV footage data.
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VEHICLE COMPOSITION
Vehicle composition (Direction- Away from Camera)
2%
17%
CAR LCV TRUCK BUS
7%
74%
Vehicle composition (Direction- Towards the Camera)
9%
48%
34%
CAR LCV TRUCK BUS
9%
10
TOTAL VOLUME
SERVICE TIME
Total Number of vehicles in one hour
Average Service Time
Service Time (Sec.)
512
Direction
Towards the camera
Away from Camera
632
20 18 16 14 12 10 8 6 4 2 0
17.67 15.296 13.16 8.64 3.7692 4.40
CAR 0
100
200
300
No. of vehicles
400
500
600
700
7.75
3.636
LCV
TRUCK
BUS
Vehicle type AVERAGE SERVICE TIME (AWAY FROM CAMERA) AVERAGE SERVICE TIME (TOWARDS THE CAMERA)
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BASE MODEL DEVELOPMENT
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DATA INPUT
13
on ti lec
Node
ol c ta s Da int po
ed c du Re eas ar
ed e sp
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SIMULATION
15
CALIBRATION PARAMETERS
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RESULTSTotal volume 700
632 570.16
12
579.7
539.3
533.03
512
500 400 300 200 100 0
% Error (Absoulte value)
Vehicles per hour
600
% Error in volume 10
9.78481012658227 8.27531645569619
8 6
5.06211755979973 3.94536892857812
4 2 0
away from camera
towards the camera
Direction total volume before caliberation
total volume after caliberation
away from camera
towards the camera
Direction total input volume
total % error before caliberation
total % error after caliberation
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VOLUME (AFTER CALIBERATION) One hour Volume (After caliberation) 350
One hour Volume (After caliberation)
329.74
250
244
200
176 144.92
150 100
31.38
50
48
26.99
0 car
hgv
bus
Type of vehicles towards the camera simulated
towards the camera observed
lcv
44
No. of Vehicle
No. of Vehicle
300
500 450 400 350 300 250 200 150 100 50 0
444.7
468
96.97 108 5.94 car
hgv
12
bus
32.09 44 lcv
Type of Vehicle away from camera simulated
away from camera observed
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QUEUE RESULT (AFTER CALIBERATION) QSTOPS
TOLL E
toll booth
•
TOLL F
TOLL G
TOLL A
TOLL C
TOLL D
24
25
25 TOLL B
27
39 TOLL H
23
17.86 TOLL D
20
TOLL C
queue stops
28.77
29.43 23.21
TOLL B
20
TOLL A
29.94
27.85
Maximum queue length
35.42
40.81
QLENMAX
TOLL E
TOLL F
TOLL G
TOLL H
TOLL BOOTH
AVERAGE QUEUE LENGTH IS - 29.16125 , AVERAGE QUEUE STOPS IS - 25.375
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DELAY AND LOS-
LOS_B
LOS_A
TOLL C
LOS_A
LOS_A
TOLL D
LOS_B
LOS_B
TOLL E
LOS_A
LOS_A
TOLL F
LOS_A
LOS_A
TOLL G
LOS_C
LOS_C
TOLL H
LOS_C
LOS_B
COMBINED
LOS_B
LOS_B
VEH. DELAY(AFTER CALIBERATION)
TOLL A
15.6 14.12
TOLL B
VEH. DELAY(BEFORE CALIBERATION)
21.25 20.59
LOS_A
TOLL B TOLL C TOLL D Away from camera
TOLL E
6.25 6.03
LOS_A
7.86 7.79
TOLL A
Vehicle Delay
10.3 10.87
CALIBERATION)
10.75 8.12
CALIBERATION)
5.17 4.85
Towards the camera
TOLL COUNTER-
6.11 5.82
Away from camera
LOS (AFTER
Delay (in seconds)
Direction
LOS ( BEFORE
TOLL F TOLL G TOLL H To ward s th e cam era
Tolls-
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PRACTICAL ISSUESData Availability Calibration and Validation
Human Factors Accuracy of the Simulation Model
Computational Resources
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CONCLUSION• This study has effectively shown the value of include driver behaviour in traffic simulation models and the necessity of calibration to provide reliable findings. • To boost the model's capacity for traffic flow and improve its accuracy, the parameters CC0 and CC1 were modified. • The simulation findings demonstrated that after modifying the driving behaviour settings, the total volume input and level of service both improved. • After the model calibration, the vehicle delay was also decreased. The model's accuracy was raised as a consequence of the calibration process's decrease of error values. • Overall, the findings of this work may be applied to enhance the precision of traffic simulation models and optimise toll plaza operations. 21
THANKS
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REFERENCES•
Bari, C., Gupta , U., Chandra, D., antoniou, c., & dhamaniya, a. (2021). Examining effect of electronic Toll collection (ETC) System on Queue Delay Using Microsimulation Approach at toll plaza - A case study of ghotitoll plaza, India.
•
Mahdi, M. B., Leong, L. V., & Sadullah, A. F. (2019). Use of Microscopic Traffic Simulation Software to Determine Heavy-Vehicle Influence on Queue Lengths at Toll Plazas.
•
Hilmy, A., & Hamid, A. (2011). Simulation of Traffic Operation and Management at Malaysian Toll Plazas using VISSIM. doi:10.13140/2.1.2633.8249
•
Vidanapathirana, C., & Pasindu, H. (2017). Analysis of Toll Station Operations in Sri Lanka using a Micro-Simulation Technique.
•
Manraj Singh Bains, K.S Anbumani, Shriniwas S. Arkatkar and Siva Subramaniam (2017) Optimizing and Modelling Tollway Operations Using Microsimulation.
•
Shakir Ahmad, Shahid Ali, Nazam Ali, Muhammad Ashraf Javid (2021) A simulation Based study for the Optimization of Toll Plaza with Different Lane Configuration: A Case Study of Ravi Toll Plaza Lahore, Pakistan
•
Himanshu Mittal and Naresh Sharma (2022) Operational Optimization of Toll Plaza Queue length Using Microscopic Simulation VISSIM Model.
•
Umitcan Ozdemir, Mustafa Gursoy and Goker Aksoy (2022) Examination of Delay and Travel Time at Highway Toll Booth Using A Micro Simulation Program: Example of Northern Marmara Highway Kurnakoy Toll Booth
•
PTV VISSIM 7 user manual.
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