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Merge branch 'ahmed' into 'main'

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This commit is contained in:
Nguyen Quy Anh
2026-05-08 11:04:20 +02:00
parent f74fbe46d7
commit ae1c64af05
10 changed files with 1194 additions and 157 deletions
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forces.cpp
+38 -44
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@@ -1,38 +1,28 @@
#include "forces.hpp"
#include "constants.hpp"
#include <math.h>
// # 2 ADDs, 5 MULTs, 1 SQRT
double w(Vector2d e, Vector2d f) {
if (e.dot(f) >= f.norm() * cos_phi)
return 1.0;
if (e.dot(f) >= f.norm() * COS_PHI)
return DT;
else
return c;
return C_TIMES_DT;
}
// # 1 DIV
double g(double v_max_alpha, double w_alpha_norm) {
// # Assumption for calculating W(n): The "if" statement always evaluates to false.
if (w_alpha_norm <= v_max_alpha) {
return 1;
}
return v_max_alpha / w_alpha_norm;
}
// # 6 ADDs, 2 DIVs
// # 4 ADDs, 4 MULTs
void add_acceleration_term(Pedestrian *p) {
// # 2 ADDs
// # 2 MULTs
Vector2d desired_velocity = p->e * p->desired_v0;
Vector2d actual_velocity = p->curr_vel;
// # 4 ADDs, 2 DIVs
p->f_i += (desired_velocity - actual_velocity) / tau_alpha;
// # 4 ADDs, 2 MULTs
p->f_i += (desired_velocity - actual_velocity) * DT_TIMES_TAU_ALPHA_INV;
}
// # 15 ADDs, 24 MULTs, 8 DIVs, 5 SQRTs, 1 EXP
// # (N - 1) * (14 ADDs, 23 MULTs, 1 DIV, 4 SQRTs, 1 EXP)
//
// $\vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta})$
//
@@ -51,51 +41,54 @@ void add_repulsive_effects_from_pedestrians(Pedestrian *pedestrians, Pedestrian
// $\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert$
double r_ab_norm = r_ab.norm();
// $\vec{e}_{\beta}$
Vector2d e_b = pedestrians[i].e;
// # 1 ADD, 3 MULTs, 1 SQRT
// $v_\beta \Delta t$
double s_b = pedestrians[i].curr_vel.norm() * delta_t;
// # 2 ADDs, 2 MULTs
// # 2 ADDs
// $\vec{r}_{\alpha\beta} - \vec{v}_{\beta}\varDelta_{t}\vec{e}_{\beta}$
Vector2d r_ab2 = r_ab - (e_b * s_b);
Vector2d r_ab2 = r_ab - pedestrians[i].s_b_e_b;
// # 1 ADD, 2 MULTs, 1 SQRT
// $\Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert$
double r_ab2_norm = r_ab2.norm();
// # 1 ADD
// $\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert$
double r_ab_norm_sum = r_ab_norm + r_ab2_norm;
// # 1 ADD, 2 MULTs, 1 DIV, 1 SQRT
// # 1 ADD, 1 MULT, 1 SQRT
//
// $2b = \sqrt{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert)^2 - (v_\beta \Delta t)^2}$
//
double b = sqrt(r_ab_norm_sum * r_ab_norm_sum - s_b * s_b) / 2;
double two_b = sqrt(r_ab_norm_sum * r_ab_norm_sum - pedestrians[i].s_b_sq);
// # 2 ADDs, 3 MULTs, 6 DIVs
// # 3 MULTs, 1 DIV
//
// $\grad_{\vec{r}_{\alpha \beta}}b = \frac{(\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert) (\frac{\vec{r}_{\alpha \beta}}{\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert} + \frac{\vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta}{\Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert})}{4b}$
// $\frac{-V^0_{\alpha\beta}}{\sigma} \frac{\Arrowvert \vec{r}_{\alpha \beta} \Arrowvert + \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert}{2b \Arrowvert \vec{r}_{\alpha \beta} \Arrowvert \Arrowvert \vec{r}_{\alpha \beta} - v_\beta \Delta t \vec{e}_\beta \Arrowvert}$
//
Vector2d b_grad = ((r_ab / r_ab_norm + r_ab2 / r_ab2_norm) * r_ab_norm_sum) / (4 * b);
double common_factor = NEG_V0_AB_DIV_TWO_SIGMA * r_ab_norm_sum / (two_b * r_ab_norm * r_ab2_norm);
// # 3 MULTs, 1 DIV, 1 EXP
// # 2 ADDs, 4 MULTs
// $2\grad_{\vec{r}_{\alpha \beta}}b$
// See: derivations.jpg
Vector2d A = (r_ab * r_ab2_norm + r_ab2 * r_ab_norm) * common_factor;
// # 4 MULTs, 1 EXP
// $-\vec{f}_{\alpha \beta}(\vec{r}_{\alpha \beta})$
//
// $\vec{f}_{\alpha \beta}(\vec{r}_{\alpha \beta}) = \frac{V^0_{\alpha \beta}}{\sigma}e^{-b / \sigma} \grad_{\vec{r}_{\alpha \beta}}b$
// $= \frac{-V^0_{\alpha \beta}}{\sigma}e^{-b / \sigma} \grad_{\vec{r}_{\alpha \beta}}b$
//
Vector2d f_ped = b_grad * (V0_AB_div_SIGMA * exp(-b / SIGMA));
//
// $= \frac{-V^0_{\alpha \beta}}{2\sigma}e^{-b / \sigma} 2\grad_{\vec{r}_{\alpha \beta}}b$
//
Vector2d neg_f_ped = A * exp(two_b * NEG_ONE_DIV_TWO_SIGMA);
// # 4 ADDs, 7 MULTs, 1 SQRT
//
// $\vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta}) = w(\vec{e}_{\alpha}, -\vec{f}_{\alpha\beta})\vec{f}_{\alpha\beta}(\vec{r}_{\alpha} - \vec{r}_{\beta})$
//
p->f_i += f_ped * w(p->e, f_ped.reverse_sign());
p->f_i -= neg_f_ped * w(p->e, neg_f_ped);
}
}
// # board.n_obstacles * (13 ADDs, 19 MULTs, 4 DIVs, 2 SQRTs, 1 EXP)
// # board.n_obstacles * (12 ADDs, 18 MULTs, 1 DIV, 2 SQRTs, 1 EXP)
//
// $\vec{F}_{\alpha B}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{B})$
//
@@ -108,23 +101,24 @@ void add_repulsive_effects_from_borders(Board &board, Pedestrian *p) {
Obstacle obstacle = obstacles[i];
// # 8 ADDs, 6 MULTs, 1 DIV
// # 7 ADDs, 5 MULTs
// $\vec{r}_{\alpha B}$
Vector2d r_aB = p->curr_pos - obstacle.find_nearest_obstacle_point(p->curr_pos);
// # 1 ADD, 2 MULTs, 1 SQRT
// $\Arrowvert \vec{r}_{\alpha B} \Arrowvert$
double r_aB_norm = r_aB.norm();
// # 4 MULTs, 3 DIVs, 1 EXP
// # 4 MULTs, 1 DIV, 1 EXP
//
// $\vec{F}_{\alpha B}(\vec{r}_{\alpha B}) = \frac{U^0_{\alpha B}}{R} e^{- \Arrowvert \vec{r}_{\alpha B} \Arrowvert / R} \frac{\vec{r}_{\alpha B}}{\Arrowvert \vec{r}_{\alpha B} \Arrowvert}$
// $-\vec{F}_{\alpha B}(\vec{r}_{\alpha B}) = \frac{-U^0_{\alpha B}}{R} e^{- \Arrowvert \vec{r}_{\alpha B} \Arrowvert / R} \frac{\vec{r}_{\alpha B}}{\Arrowvert \vec{r}_{\alpha B} \Arrowvert}$
//
Vector2d f_obst = (r_aB / r_aB_norm) * U0_AB_div_R * exp(-r_aB_norm / R);
Vector2d neg_f_obst = r_aB * (NEG_U0_AB_DIV_R * exp(r_aB_norm * NEG_R_INV) / r_aB_norm);
// # 4 ADDS, 7 MULTs, 1 SQRT
// # 4 ADDs, 7 MULTs, 1 SQRT
//
// $\vec{F}_{\alpha B}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{ B}) = w(\vec{e}_{\alpha}, -\vec{F}_{\alpha B})\vec{F}_{\alpha B}(\vec{r}_{\alpha} - \vec{r}_{ B})$
//
p->f_i += f_obst * w(p->e, f_obst.reverse_sign());
p->f_i -= neg_f_obst * w(p->e, neg_f_obst);
}
}