- Open Access
- Total Downloads : 184
- Authors : Ajaykumar Arjunbhai Amaliyar, Dr. H. R. Varia
- Paper ID : IJERTV6IS040494
- Volume & Issue : Volume 06, Issue 04 (April 2017)
- DOI : http://dx.doi.org/10.17577/IJERTV6IS040494
- Published (First Online): 20-04-2017
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
Traffic Flow Modeling for Heterogeneous Conditions on Urban Road – A Case Study of Selected Stretches of Ahmadabad City
A.A.Amaliyar
M.E. Student
Civil Engineering Department Tatva Institute of Technological Studies
Modasa, Gujarat, India
H. R.Varia
Principal
Tatva Institute of Technological Studies Modasa, Gujarat, India
Abstract Knowledge of fundamental traffic flow characteristics and vehicle behavior are essential for operation of transportation system. The fundamental characteristics of speed and flow have been studied. An appropriate methodology was adopted to collect data. The methodology for choice of best fitting curve to the observed data has also been described. The result of the study has shown that, the Speed- Flow-density of urban heterogeneous traffic can be modelled for vehicles over a wide range of traffic flow. Speed-flow-Density curves for selected roads were plotted.
Keywords Flow Modelling, Speed-Flow-Density Relationship
INTRODUCTION
In developing country like India, road traffic in general & urban roads traffic in particular, is highly heterogeneous include vehicles of widely varying characteristics the vehicles share the same road space without separation. Basic knowledge of traffic flow characteristics like traffic volume under such heterogeneous conditions is fundamental traffic volume is basic variable in planning, designing, and operation of roadway systems. The roads of India are a perfect example of the dominant economic difference and vehicle like motorcycle, auto rickshaw, bus, minibus, truck, moped, car, bicycle, tractor, non motorized can be seen sharing the same road space. The traffic condition of Ahmadabad city is highly heterogeneous in nature and vehicles do not follow lane discipline and not follow signal or sign, which makes it difficult to study and analyze traffic flow characteristics. To understand traffic flow relationships have been established between the main characteristics: speed, flow, density.
BASIC FORM OF SPEED-FLOW-DENSITY RELATIONSHIP
Knowledge of relationship between speed, volume and density is very important in traffic studies. Fundamental speed-Flow-Density graphs as shown in fig.1
-
Speed-density relationship
With increase in density the speed decreases. When there is no vehicle (density=0), the speed is maximum. This speed is called Free speed. At very high density, the vehicles approach zero speed. This density is called Jam density.
-
Speed-Flow relationship
At very low speeds the volume would also be low. With increasing speed, traffic volume also increases up to a certain limit, as headway initially decreases. But as the speed further increases the spacing between the vehicles increases and becomes so large that volume decreases. There is an optimum speed at which the flow is maximum.
-
Flow-density relationships
As the density increases from zero, volume increases up to the point of critical density . the density corresponding to maximum flow. It is called Optimum density. There after volume decreases as density continues to increases to a maximum value known as Jam density when all vehicles are stopped. As density increases the speed of vehicle is reduced, reducing the flow, till it reaches jam density when there is no movement or flow.
Fig.1: Fundamental diagram speed-flow-density
METHODOLOGY & DATA COLLECTION
The study has been conducted by the Department of Civil Engineering, Tatva Institute of Technological Studies, Modasa. For assessing the existing traffic condition in Ahmadabad City. To study the effect of moving vehicle on the traffic flow characteristics the traffic volume count survey are carried out with the help of video graphy on selected stretches of different stretch lengths during time period.
Fig.2: Methodology chart for study
-
Road Geometry
TABLE 2: TOTAL TRAFFIC VOLUME AT DIFFERENT STRETCHES
Road Name
2W
3W
CAR
BUS/ TRU
CK
L.
C.
V.
N.M.
Sakar Bazar To
Railway Station Kalupur
22723
17729
4092
1363
709
1601
Railway station
Kalupur To Sakar Bazar
21493
14192
4328
1280
564
1461
Kalupur Station To
Gangaram Tower
20080
8212
517
2
18
1000
Gangaram Tower
To Kalupur Station
18961
7854
540
6
14
983
Fig.3: Vehicle Category wise Traffic flow at Kalupur police station To Gangaram Tower
TABLE 1
Sr.
No.
Road Name
Number of
lane(m)
Width
(m)
Length
(M)
1
Railway station Kalupur To Sakar Bazar
Three lane undivided
one way
12.00
260
2
Sakar Bazar To Railway Station Kalupur
Three lane undivided
One way
12.00
240
3
Kalupur police Station To Gangaram Tower
Two lane undivided
Two way
12.00
400
4
Gangaram Tower To Kalupur police Station
Two lane
undivided Two way
11.70
420
GEOMETRY OF DIFFERENT STRETCHES
-
Traffic Volume count Survey
The most important data are generated through the modern survey techniques like traffic volume count at Different stretches. The extent of variation of traffic flow was as curtained by carrying out twelve hour (8:15:00 AM to 20:15:00 PM) working day counts on Study roads. The traffic volume is expressed as passenger car unit per hour (PCU/hour).Traffic Volume of different stretches are shown in Table no.2
Fig.4: Vehicle Category wise Traffic flow at Gangaram Tower To Kalupur police station
Fig. 5: Vehicle Category wise Traffic flow at Sakar Bazar To Railway Station Kalupur
Fig.6: Vehicle Category wise Traffic flow at Railway Station Kalupur To Sakar Bazar
-
ANALYSIS OF COLLECTING DATA
Data collecting from volume count survey are Analysis and measure Space mean speed on selected stretches through every 20 second Flow count continuously and Density is measured through the equation (1). After completed Analysis developed Relationship of Speed-Flow, Speed-Density and Flow-Density. And choice of best fitting curve to the observed data, and develop Speed-Flow, Speed-Density, and Flow-Density model.
Fig 8: Speed-Flow relationship at Kalupur railway station to Sakar Bazar
Where,
Q = K x V .. (1)
Fig 9: Speed-Density relationship at Kalupur railway station to Sakar Bazar
2.Sakar Bazaar To Kalupur Railway Station
Q = Traffic flow PCU/hour K = Density km/hour
V = Speed PCU/km
Classified Volume count and Space mean Speed is directly measured by video graphy and density measured from equation (1). Different stretches flow-speed-density relationship and its best fitting curves grahs are as under:
-
Kalupur Railway Station To Sakar Bazaar (Moti Bakery)
-
Fig 7: Flow-Density relationship at Kalupur railway station to Sakar Bazar
Fig 10: Flow-Density relationship at Sakar Bazaar To Kalupur Railway Station
Fig .11: Speed-Flow relationship at Sakar Bazaar To Kalupur Railway Station
Fig.12: Speed-Density relationship at Sakar Bazaar To Kalupur Railway Station
-
Kalupur Police Station To Gangaram Tower
Fig.13: flow-Density relationship at Kalupur Police Station To Gangaram Tower
Fig 14: flow-Speed relationship at Kalupur Police Station To Gangaram Tower
Fig 15: Speed-Density relationship at Kalupur Police Station To Gangaram Tower
-
Gangaram tower to kalupur police station
Fig. 16: Speed-Flow relationship at Gangaram tower to kalupur police station
Fig. 17: Speed-Density relationship at Gangaram tower to kalupur police station
Fig. 18: Flow-Density relationship at Gangaram tower to kalupur police station
Best fitting curve from above Relationships
-
Kalupur Railway Station To Sakar Bazaar
-
Sakar Bazar To Kalupur Railway Station
-
Gangatower To Kalupur Police station 4. Kalupur Police Station To Gangaram Tower
3 |
Kalupur police Station To Gangaram Tower |
y = -4E-06×2 + 0.007x + 61.07 |
0.896 |
y = 0.737e0.001x |
0.981 |
||
4 |
Gangaram Tower To Kalupur police Station |
y = -3E-06×2 + 0.008x + 60.05 |
0.983 |
y = 0.629e0.001x |
0.995 |
Sr. No. |
Road Name |
Speed(y) – Density(x) Model |
Co- efficient of Determina tion R2 |
1 |
Railway station Kalupur To Sakar Bazar |
y = -0.100x + 66.42 |
0.958 |
y = -0.075x + 54.73 |
0.986 |
||
2 |
Sakar Bazar To Railway Station Kalupur |
y = -0.103x + 66.83 |
0.965 |
y = -0.044x + 43.11 |
0.951 |
||
3 |
Kalupur police Station To Gangaram Tower |
y = -0.319x + 69.28 |
0.991 |
y = -0.073x + 32.74 |
0.857 |
||
4 |
Gangaram Tower To Kalupur police Station |
y = -0.284x + 69.73 |
0.979 |
y = -0.063x + 32.08 |
0.872 |
Sr. No. |
Road Name |
Speed(y) – Flow(x) Model |
Co-efficient of Determination R2 |
1 |
Railway station Kalupur To Sakar Bazar |
y = -8E-07×2 + 0.006x + 48.23 |
0.943 |
y = 1.817e0.00027x |
0.995 |
||
2 |
Sakar Bazar To Railway Station Kalupur |
y = -7E-07×2 + 0.006x + 49.62 |
0.969 |
y = 1.222e0.000307x |
0.989 |
FLOW-SPEED-DENSITY MODELING
Sr. No. |
Road Name |
Flow(y) – Density(x) Model |
Co- efficient of Determina tion R2 |
1 |
Railway station Kalupur To Sakar Bazar |
y = -0.131×2 + 76.92x – 502.0 |
0.999 |
y = -0.062×2 + 42.13x + 2871. |
0.943 |
||
2 |
Sakar Bazar To Railway Station Kalupur |
y = -0.119×2 + 71.85x – 192.2 |
0.997 |
y = -0.006×2 – 5.072x + 12875 |
0.975 |
||
3 |
Kalupur police Station To Gangaram Tower |
y = -0.348×2 + 72.23x – 38.84 |
0.998 |
y = -0.004×2 – 5.905x + 4338. |
0.976 |
||
4 |
Gangaram Tower To Kalupur police Station |
y = -0.315×2 + 72.79x – 33.4 |
0.998 |
y = -0.002×2 – 5.048x + 4227 |
0.933 |
CONCLUSION
From the survey we find out that our Indian traffic is heterogeneous traffic. It is concluded that existing equation of traffic stream are suitable for these Heterogeneous traffic. According to our complete analysis we found the traffic stream parameters. We get standard relationship between traffic stream parameters. We get a equation for heterogeneous traffic of Ahmadabad city.
REFERENCES
-
Rao A. M. and Rao K. R. (2014). Free Speed Modeling for Urban Arterials A Case Study on Delhi, Periodica Polytechnica Transportation Engineering, 43(3), pp. 111-119, 2015 DOI: 10.3311/PPtr.7599 .
-
Doshi R. H. (2015) Influence of Vehicles on Traffic Flow Characteristics in an Urban Area, government engineering collage, modasa.
-
Patel H. V. and Gor V. R. (2013). Capacity Determination of an Arterial Roa – A Case study of Modasa Town (Bus station to Malpur cross road), IJSRD – International Journal for Scientific Research & Development, Vol. 1, Issue 2, 2013 | ISSN.
-
Yamuna R. (2014) Study of Traffic Flow Characteristics for Heterogeneous Traffic IOSR Journal of Engineering (IOSRJEN) in Gandhi Memorial College of Engineering and Technology, Nandyal Andhra Pradesh
-
Thakor D. K.and Zala L. B. and Amin A. A. (2014) Traffic Flow Characteristics For Heterogeneous Traffic On Urban Road-A Case Study Of Selected Stretch Of Anand City Journal Of International Academic Research For Multidisciplinary.
-
Patel V. J. and Kumavat H. R. (2014) Modeling of Speed- Flow Equations on Four- Lane National Highway-8 International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075.
-
Dhapudkar R. S.(2014) Analysis and Development of Traffic Stream Parameters of Heterogeneous Traffic at Signalized Intersection The International Journal Of Engineering And Science (IJES).
-
Bainsa M. S. and Balaji P., Shriniwas S A. (2012) Modeling of Traffic Flow on Indian Expressways using Simulation Technique, 8th International Conference on Traffic and Transportation Studies Changsha, China.
-
Joshi G. J. and Patel C. R. (2014). Mixed Traffic SpeedFlow Behavior under Influence of Road Side Friction and Non-Motorized Vehicles: A Comparative Study of Arterial Roads in India, World Academy of Science, Engineering and Technology, International Journal of Civil, Environmental, Structural, Construction and Architectural Engineering Vol:8, No:11, 2014.
-
IRC: 106-1990, guidelines for capacity of urban roads in plain areas
-
KHANNA S. K. and .JUSTO C.E.G., VEERAAGAVAN A.Highway Engineering Book Revised 10th Edition.
-
Saxena book of Highway Engineering
-
Kadiyali, L.R. (2000), Traffic Engineering and Transport Planning, Khanna publishers.