Particles and Vicsek models. This approach allows us to disentangle the role played by velocity-alignment and volume exclusion interactions, bridging together the aggregation phenomena discussed in the context of isotropic and polar active particles. After the definition of the model in section \[sec:Model\], we perform a systematic computational study of its phase behavior. In section \[sec:PhD\] we summarize our findings in a phase diagram. We first describe the emergence of flocking in the system in section \[sec:flock\], to then move to the characterization of the patterns in section \[sec:cluster\]. Finally, section \[sec:conclusion\] is devoted to a general discussion of our results.

Model {#sec:Model}
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The system consists on a two-dimensional assembly of $N$ Active Brownian Particles (ABP) in a square box of size $L_x\times L_y$, subjected to periodic boundary conditions (PBC). The dynamics of the system is governed by the over-damped stochastic equations: $$\dot{\mathbf{r}}_i (t) = v_0\mathbf{n}_i(t) + \mu\mathbf{F}_i \, ,
\label{r_dot}$$ $$\dot \theta _i (t) = \frac{K}{\pi R_{\theta}^2} \sum_{j \in \partial_i} \sin(\theta_j - \theta_i) + \sqrt{\gamma}\eta_i(t) \, .
\label{theta_dot}$$ Here $\mathbf{r}_i(t) = (x_i,y_i)$ denotes the spatial position of the $i$-th particle at time $t$, $v_0$ the constant magnitude of the self-propulsion velocity along its orientation $\mathbf{n}_i(t)=(\cos \theta_i,\, \sin \theta_i)$, 