peloton_step.jl

function update_desired_rank!(agent::Agent, position_mean)
    if rand() > agent.energy
            agent.desired_rank = agent.desired_rank - 0.01 * rand()
    else 
        if rand() > 0.99
            agent.desired_rank = agent.desired_rank + max(0, (0.5 - position_mean[1])) * rand()
        end
    end
end


function step!(model::Model)
    postions = [ agent.position for agent in model.peloton ]
    
    postion_mean = mean(postions)
    for agent in model.peloton
        # random movement
        random_move =  0.001 *(rand(2) .- 0.5)

        # bias towards center of the road
        bias = [0 ; 0.05 * (model.road_center - agent.position[2])]

        # bias to desired rank
        bias[1] = 0.05 * (agent.desired_rank - agent.position[1])
        
        # flocking algorithm
        velocity = flocking(agent, model) + random_move + bias
        agent.position += velocity
        
        # energy component
        agent.energy -= energy_usage(agent, model)
        agent.energy = max(0, min(1, agent.energy))
        
        update_desired_rank!(agent, position_mean)
    end
end