... | ... | @@ -231,14 +231,14 @@ randomly distributed. |
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- `patience`: this parameter influences the route choice behavior when using the quickest path router.
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It basically defines how long a pedestrian stays in jams before attempting a rerouting.
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- `premovement_mean` and `premovement_sigma`: premovement time is Gauss-distributed $$\mathcal{N}(\mu, \sigma^2)$$.
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- `premovement_mean` and `premovement_sigma`: premovement time is Gauss-distributed $`\mathcal{N}(\mu, \sigma^2)`$.
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- Risk tolerance can be Gauss-distributed, or beta-distributed.
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If not specified then it is defined as $$\mathcal{N}(1, 0)$$:
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If not specified then it is defined as $`\mathcal{N}(1, 0)`$:
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- `risk_tolerance_mean` and `risk_tolerance_sigma`: $$\mathcal{N}(\mu, \sigma^2)$$.
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- `risk_tolerance_mean` and `risk_tolerance_sigma`: $`\mathcal{N}(\mu, \sigma^2)`$.
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- `risk_tolerance_alpha` and `risk_tolerance_beta`: $$Beta(\alpha, \beta)$$.
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- `risk_tolerance_alpha` and `risk_tolerance_beta`: $`Beta(\alpha, \beta)`$.
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- `x_min`, `x_max`, `y_min` and `y_max`: define a bounding box where agents should be distributed.
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... | ... | @@ -264,10 +264,12 @@ new agents in the system during the simulation. |
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- `group_id`: group id of the agents. This `id` should match a predefined group in the section [Agents_distribution](#agents_distribution).
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- `caption`: caption
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- `greedy` (default `false`): returns a Voronoi vertex randomly with respect to weights proportional to squared distances.
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For vertexes $$v_i$$ and distances $$d_i$$ to their surrounding seeds
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calculate the probabilities $$p_i$$ as
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For vertexes $`v_i`$ and distances $`d_i`$ to their surrounding seeds
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calculate the probabilities $`p_i`$ as
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$$p_i= \frac{d_i^2}{\sum_j^n d_j^2}.$$
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```math
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p_i= \frac{d_i^2}{\sum_j^n d_j^2}.
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```
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If this attribute is set to `true`, the greedy approach is used.
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That means new agents will be placed on the vertex with the biggest distance to the surrounding seeds.
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