ValueError: failed in converting 9th argument `a' of _slsqp.slsqp to C/Fortran array & ValueError: 0-th dimension must be fixed to 378 but got 360

Question

I use scipy.optimize.minimize to obtain the optimal lane-change duration when planning the trajactory. the following is my code:

    def laneChangePlanning(self, x_0, v_x0, a_x0, adjLeader, adjFollower, curLeader, y_0, v_y0, a_y0, y_t, laneIndex):

        v_yt, a_yt = 0, 0
        args = (x_0, v_x0, a_x0, y_0, v_y0, a_y0, y_t, v_yt, a_yt, adjLeader, adjFollower, curLeader, laneIndex)
        cons = ({'type': 'ineq', 'fun': self.constraints(args), 'jac': self.jacs(args)})
        bounds = Bounds([3.0], [7.0])
        x0 = np.array([4.0])
        res = minimize(fun=self.calObject(args), x0=x0, method='SLSQP', constraints=cons, bounds=bounds)
        t_plan = res.x[0]

the self.constraints is a little complicated, so i just put the output:

       res = np.concatenate((np.array(distCurLeader), np.array(distAdjLeader),
                              np.array(distAdjFollower), np.array(vx_ego), np.array(ax_ego),
                              np.array(ay_ego)))

the shape is {tuple:1} 360: enter image description here

Also, i just put the output of self.jacs(args):

       res = np.concatenate((np.array(jac_distCurLeader), np.array(jac_distAdjLeader),
                                np.array(jac_distAdjFollower), np.array(jac_vx_ego),       np.array(jac_ax_ego), np.array(jac_ay_ego)), axis=0)

the shape is {tuple:2} (360, 1), as follows:

enter image description here

however, the exceptions are:

ValueError: 0-th dimension must be fixed to 378 but got 360


The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\chong\PycharmProjects\sumo_test\test.py", line 35, in <module>
    obs, reward, done, _, info = env.step(action)
  File "C:\ProgramData\Anaconda3\envs\stableBaseline\lib\site-packages\gymnasium\wrappers\order_enforcing.py", line 56, in step
    return self.env.step(action)
  File "C:\ProgramData\Anaconda3\envs\stableBaseline\lib\site-packages\gymnasium\wrappers\env_checker.py", line 51, in step
    return self.env.step(action)
  File "C:\Users\chong\PycharmProjects\sumo_test\sumo_env\test_env.py", line 700, in step
    vx_ego, xy_ego, delta_ts = self.laneChangePlanning(0, egoState[1], egoState[2], adjRightLeader,
  File "C:\Users\chong\PycharmProjects\sumo_test\sumo_env\test_env.py", line 406, in laneChangePlanning
    res = minimize(fun=self.calObject(args), x0=x0, method='SLSQP', constraints=cons, bounds=bounds)
  File "C:\ProgramData\Anaconda3\envs\stableBaseline\lib\site-packages\scipy\optimize\_minimize.py", line 719, in minimize
    res = _minimize_slsqp(fun, x0, args, jac, bounds,
  File "C:\ProgramData\Anaconda3\envs\stableBaseline\lib\site-packages\scipy\optimize\_slsqp_py.py", line 422, in _minimize_slsqp
    slsqp(m, meq, x, xl, xu, fx, c, g, a, acc, majiter, mode, w, jw,
ValueError: failed in converting 9th argument `a' of _slsqp.slsqp to C/Fortran array

Through the source code, it seems that the 0-th dimension of 'a' should be 378, rather than 360. The 0-th dimension of 'a' is obtained through the dimension of 'fun' and 'jac'. But I can't figure out how the '378' is calculated.

I really appreciate it if someone could debug this error.