Online IFN Transport

Select Example Triangle Triangle with a two-way Two triangles with real world flows Square Square-Diagonal Square-Diagonal with a two-way Square with Cross Square-Cross with a two-way 2-Block numbers 2-Block alphabet 2-Block Weakly Connected Ateneo Microscopic T Junction Microscopic + Junction

Link matrix

Each row in the input Link Matrix consists of the following data:

LinkID, startNodeID, endNodeID, linkCapacity, linkDistance (km), linkMaxSpeed (km/h);

End each row by a semicolon. Separate each data in one row by comma or a space.

• Link ID is useful number for your own identification.
  Each link is one directional traffic stream.
  If the road is two ways, in macroscopic level, you need to create two links, one for each direction.
  In microscopic level, each turning direction is one link such that there is no ambiguity of the directional traffic stream
  (see examples of Microscopic T or + Intersections).
• Start Node ID is the beginning node identification number of the link
• End Node ID is the ending node identification number of the link
• Link capacity is either given based on standard (such as HCM) in pcu/hour/link/direction,
  or approximated based on road width (in meter/link/direction)
  or number of lanes per link per direction (See: Setting tab)
• link distance is the road length per link, in km.
• link max speed (to be precise: free flow speed) is in km/hour.

Make sure your link data produces a strongly connected network. You can test it using button above.

Node matrix

Node matrix is useful for drawing the network. The link distance is not computed based on nodes data.
Each row in the input Node Matrix consists of the following data:

NodeID,X-Coordinate, Y-Coordinate;

Coordinate Transformation:

Set the parameters, then use the Node Coordinate Transformation buttons (Rotation, Shift, Scale, Flip) for better drawing of the network.
Undo every time back to the original data before you do te next transformation

Cloud Node Reporting

IFN requires the network to be strongly connected. If it happens that your network is weakly connected, then you need to create a cloud node and connect each of the source node (or source component) in the network into the cloud node through dummy links and connect the cloud node to each of the sink node (or sink component) in the network using dummy links.

Specify the cloud node ID (if exists):

Do you want to include or exclude all dummy links related to cloud node from the display of network? Include Exclude

In most practical purposes, you want to exclude the links related to the cloud nodes from the computation of network performances. For theoretical purposes, the inclusion of links related to the cloud node would guarantee that the ideal flow matrix is premagic.

Display Network

Press button below to redraw, especially after uploading or transforming your data.
You can also zoom in or zoom out through mouse wheel and pan the drawing by dragging the network.

Constraint

Set a constraint to the model total flow maximum flow maximum congestion level real world flow

Input: total flow, kappa

Input: max flow, psi

Input: maximum congestion level, xi

Input: real world flow using the following format:

LinkID, Node1, Node2, ActualFlow;

In any model, we need to have invariant, something that we assume to be constant.
Using IFN, you could calibrate the results based on one of the following assumptions.

• Total flow as constant means you assume the total demand in the entire network does not change. This is useful for modeling short-term effect by comparing scenarios on the same invariant
• Max flow as constant means you assume the maximum demand on certain links would be used as the basis of comparison. This is useful for modeling medium-term effect by comparing scenarios on the same invariant
• Max congestion level as constant means you assume the maximum congestion level on certain links would be used as the basis of comparison. This is useful for modeling long-term effect by comparing scenarios on the same invariant
• Real-World Flow as constant means you assume the observed real world flow as the ground truth to be used as the basis of comparison. This is useful for if you have one or several link flow data for the base scenario.

Travel Time Model

Set Travel Time Model: BPR Modified Greenshields Greenshields

Using Greenshield’s traffic model, we assume the speed-density relationship is linear and the congestion level (which is equal to the flow/capacity) is set to be between zero and one. Since the congestion level is normalized to be between zero and one, it is easier to interpret the meaning of congestion level. Congestion is just flow/capacity and capacity is the maximum flow. The Greenshield tends to have higher speed than BPR (for the same congestion level) and only operates when the traffic is not so congested (i.e., uncongested region of the fundamental diagram of traffic flow model).

BPR model and Modified Greenshield produces better variation of speed and travel time even when the traffic is congested. However, the congestion level (which is equal to the flow/capacity) can go beyond 1, which make the definition of capacity somewhat confusing because "practical capacity" is no longer the maximum flow. For Modified Greenshield, the max congestion must be less than 2.0. There is no limit of congestion value if you use BPR model. Transportation engineers is often using BPR model in conjunction with the practical capacity derived from Highway Capacity Manual (HCM).

Capacity

Set the values in link capacity to represent pcu/hour number of lanes road width in meter
Optional input: set capacity multiplier

You can set the link capacity is either given based on standard in passenger car unit per hour (pcu/hour). Alternatively, it is sometimes easier to approximate the link capacity based on road width (in meter) or number of lanes per link per direction.

Capacity multiplier is used when the link capacity unit is not in pcu/hour. The capacity multiplier would change as you change the meaning of link capacity. You can change the default value of capacity multiplier.

Run the Scenario

If you upload or change your data or your model, you need to press Calculate button to recalculate.

Output:

Export Result to Excel