Data Imputation Settings

These are the default values to be imputed when the data from OSM does not have these values. If you want to use different settings, you must change the settings first before downloading data from OSM.

Default Road Width (meter):

One Way Road Width (meter):

Two Ways Road Width (meter):

Gradient Capacity to Road Width (pcu/hour/meter):

Intercept Max Speed (km/hour) for the lanes:

Gradient Max Speed (km/hour/lane):

Gradient capacity to Number of Lane (pcu/hour/lane):

One Way Number of Lane (lane):

Two Ways Number of Lane (lanes):

Number of lanes: N/A 1 2 3 4 5 6 7 8 9 10
Road Width (meters): N/A 2.0 2.5 3.0 3.5 4.0 4.5 5.0 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0
One Way: N/A yes no

IFN Constraint

Set a constraint to the model

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 if you have one or several link flow data for the base scenario.
• Origin-Destination (OD) Flow as constant means you assume the observed origin-destination flow as as the ground truth to be used as the basis of comparison. This is useful for comparison with traditional traffic assignment methods. You need to convert the OD Flow matrix into the Real-World Flow matrix. Then you can optionally add or modify the computed Real World flow. The IFN computation would be based on the Real-World Flow matrix, not the OD Flow matrix.

Input: origin-destination flow using the following format:

Node1, Node2, ODFlow;

Travel Time Model

Set Travel Time Model:

Using Greenshield’s traffic model, we assume the speed-density relationship is linear and the congestion level $ g $ (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 $ t=t_{0}\left ( 1+\gamma g^{\eta } \right ) $ has two parameters, $\gamma$ and $\eta$, while the internal parameter $t_{0}$ depends on link maximum speed and link distance, which is already inside the network link matrix data. Greenshield model $ t=\frac{2l}{u_{f} \left ( 1+ \sqrt{1-g} \right )} $ and Modified Greenshield model $ t=\frac{2l}{u_{f} \left ( 1\pm \sqrt{\left| 1-g \right|} \right )} $ has no external parameter because the internal parameters are link maximum speed and link distance, which is already inside the network link matrix data. The $\pm$ in Modified Greenshield model depends on $ sign \left( 1-g \right ) $. 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.

Capacity to Stochastic Model

The flow in IFN is proportional to the capacity ratio.
You can select to use either simple proportional model without any parameter $ s_{ij} = \frac{c_{ij}}{\sum_{k=1}^{n} c_{ik}} $ or use power-exponential model with two parameters $ s_{ij} = \frac{c_{ij}^\alpha e^{\beta c_{ij}}}{\sum_{k=1}^{n} c_{ik}^\alpha e^{\beta c_{ik}}} $.

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.

Select Action Clear All Selections Find Node by ID Find Link by ID Find Link by Node IDs Find any Path Find Shortest Path Find All Paths Link Weight: -- Select Field -- Link Capacity Link Distance Link Max Speed scale: 10 50 100 250 500 1,000 5,000 10,000 25,000 50,000 75,000 100,000 500,000 cloud node: Include Exclude

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