Simulation of Traffic Flow - Density
Download as PPTX, PDF12 likes2,359 views
The document discusses the simulation of traffic flow, focusing on the relationship between vehicle density and flow characteristics. Key concepts include various definitions of density, flow, jam density, and their impact on traffic congestion, particularly in critical segments like bridges and tunnels. The study aims to model and control traffic flow using input data to optimize road capacity and improve level of service under different conditions.
Simulation of Traffic Flow - Density
- 1. Simulation of Traffic Flow - Density PhD Candidate: Azdeen Najah Asst.Prof.Dr. Altan Ozkil 1
- 2. 2
- 4. Density (k): The number of vehicles (n) occupying a given length (l) of a lane or roadway at a particular instant. Unit of density is vehicles per kilometer (vpkm). u q l n k 4 Keywords Definitions:
- 5. Free-flow speed (uf) The speed at which vehicles will travel unimpeded Jam density (kj) The density of vehicles in stopped traffic Capacity (qm) The maximum flow a section of roadway can maintain 5 Keywords Definitions:
- 6. Density (veh/mile) Flow(veh/hr) kj Jam Density Highest flow, capacity, qm km Optimal densityUncongested Flow Congested Flow 6 Flow vs. Density:
- 7. 1. When density is zero, flow will also be zero, since there are no vehicles on the road. 2. When the number of vehicles gradually increases, the density as well as flow increases. 3. Increases in density beyond the point of maximum flow (qmax) results in reduction of flow. 4. When more and more vehicles are added, it reaches a saturation level where, vehicles can't move. 5. The relationship is normally represented by a parabolic curve 7 Some characteristics of flow vs. density relationship: This is referred to as the jam density or the maximum density (kjam). At jam density, flow will be zero because the vehicles are not moving.
- 8. LOS Max. Density Pc/km/ln Average speed Km/hr Max. v/c Max. Service flow rate Pc/hr/ln A 7 100.00 0.32 700 B 11 100.00 0.50 1100 C 16 98.40 0.72 1575 D 22 91.50 0.92 2015 E 25 88.00 1.00 2200 Source: Transportation Research Board Highway Capacity Manual. Washington, DC. National Research Council, 2010. 8 Level of Service: Undivided Multilane Hw, LOS C, FFS = 100 km/hr
- 9. Standard Parameters Highway Functional Classification = Multilane Undivided Free-Flow Speed (Uf) = 100 km/hr. Level of Service (LOS) = C Density (K) = 16 Veh./km/ln Source: Transportation Research Board Highway Capacity Manual. Washington, DC.National Research Council, 2010. 9 Input Data:
- 10. To solving traffic congestion problem in highway section specially at critical highway segment such as bridge, viaduct or tunnel etc. By using Microsoft Excel program to simulate and model Flow- Density relationship using random input data (Density) to get ideal output (Flow) to moderate and control uncongested flow on the specific highway segments with Level of service B or C by using the flex lanes system. 10 The Aim :
- 11. Density (k), Veh./hr./ln. (Ranked) INPUT Flow (q), Veh/km. OUTPUT 0 0,000 1 93,750 1 93,750 2 175,000 3 243,750 3 243,750 4 300,000 4 300,000 5 343,750 6 375,000 7 393,750 7 393,750 8 400,000 9 393,750 9 393,750 10 375,000 11 343,750 12 300,000 12 300,000 13 243,750 14 175,000 15 93,750 15 93,750 16 0,000 11 Control data:
- 12. Densıty (k),Veh./hr./ln. (Random) INPUT Flow (q), Veh./hr. OUTPUT 7 406,419 12 320,243 7 385,076 15 88,488 6 357,869 5 358,359 9 363,341 12 299,284 13 262,198 4 325,378 1 88,572 11 349,589 12 310,900 3 262,264 8 403,690 10 355,819 7 415,173 15 97,981 0 0,000 13 243,434 5 320,385 5 334,416 9 378,600 16 0,000 12 Random Inputs vs. Simulated Outputs:
- 13. According to: the system parameters and the desired outputs the inputs can be verified and validated. Compare with Control Parabolic chart with following characteristics: At k=0, q=0 At kj=16, q=0 At km=Kj/2=8, qm=400 13 The Verification & Validation:
- 14. 14 Example for Flex lanes system Application with this simulation
- 15. Image Processing Vehicle Detector: This device detects vehicles and outputs traffic flow information such as volume, occupancy, presence, speed, classification, and queue length in multiple lanes by processing images taken by a monitoring camera installed over roads. 15 Data Collection: “Traffic Density” k, veh./km/ln.
- 16. For Determine the traffic flow and capacity for any road segment we should know its functional classification, LOS, FFS and Number & width of lanes. By using Simulation and modelling we can solve the traffic congestion problems by moderate and control the critical highway segments such as viaducts, bridges and tunnels. 16 The Conclusion:
- 17. Transportation Research Board Highway Capacity Manual. Washington, DC. National Research Council, 2010. Principles of Highway Engineering and Traffic Analysis. 3dh. Edition. 17 The References:
- 18. 18