## Step 1: Define the symbolic representation of the problem

Let's denote:
- $x_1$ as the number of premium class seats sold
- $x_2$ as the number of regular class seats sold

The objective is to maximize profit, which is $50x_1 + 30x_2$.

## Step 2: Identify the constraints

1. The bus carries at most 100 passengers: $x_1 + x_2 \leq 100$
2. The bus reserves at least 30 seats for premium class: $x_1 \geq 30$
3. At least twice as many passengers prefer regular class than premium class: $x_2 \geq 2x_1$

## 3: Symbolic representation in JSON format

```json
{
    'sym_variables': [('x1', 'premium class seats'), ('x2', 'regular class seats')],
    'objective_function': '50*x1 + 30*x2',
    'constraints': [
        'x1 + x2 <= 100',
        'x1 >= 30',
        'x2 >= 2*x1'
    ]
}
```

## Step 4: Convert the problem into Gurobi code

To solve this linear programming problem using Gurobi, we will use the Gurobi Python API.

```python
import gurobi

def solve_bus_seating_problem():
    # Create a new model
    model = gurobi.Model()

    # Define variables
    x1 = model.addVar(name='premium_seats', lb=0, ub=100, vtype=gurobi.GRB.INTEGER)  # Number of premium class seats
    x2 = model.addVar(name='regular_seats', lb=0, ub=100, vtype=gurobi.GRB.INTEGER)  # Number of regular class seats

    # Objective function: Maximize 50*x1 + 30*x2
    model.setObjective(50*x1 + 30*x2, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(x1 + x2 <= 100, name='total_passengers')  # Total passengers do not exceed 100
    model.addConstr(x1 >= 30, name='premium_seats_reserved')  # At least 30 premium seats
    model.addConstr(x2 >= 2*x1, name='regular_vs_premium')  # At least twice as many regular as premium

    # Optimize
    model.optimize()

    # Print solution
    if model.status == gurobi.GRB.OPTIMAL:
        print(f"Optimal solution: {model.x[0].varName} = {model.x[0].x}, {model.x[1].varName} = {model.x[1].x}")
        print(f"Max Profit: ${model.objVal:.2f}")
    else:
        print("No optimal solution found.")

solve_bus_seating_problem()
```