def test_100_4_greedy(self): result = dynamic_simulation(GreedyPlatooning(), folder='./testroutes/test100-4/') fuel_saving = sum([x.current_fuel_consumption() for x in result]) / sum([x.default_plan.fuel for x in result]) print fuel_saving self.assertAlmostEqual(0.94887673735, fuel_saving, delta=10 ** -10)
def test_100_3_sub_stochastic(self): result = dynamic_simulation(SubModularityPlatooning(False), folder='./testroutes/test100-3/') fuel_saving = sum([x.current_fuel_consumption() for x in result]) / sum([x.default_plan.fuel for x in result]) print fuel_saving self.assertAlmostEqual(0.970021555973, fuel_saving, delta=10 ** -10)
def test_100_2_sub_deterministic(self): result = dynamic_simulation(SubModularityPlatooning(), folder='./testroutes/test100-2/') fuel_saving = sum([x.current_fuel_consumption() for x in result]) / sum([x.default_plan.fuel for x in result]) print fuel_saving self.assertAlmostEqual(0.968308771047, fuel_saving, delta=10 ** -10)
def test_100_3_random(self): result = dynamic_simulation(RandomPlatooning(0), folder='./testroutes/test100-3/') fuel_saving = sum([x.current_fuel_consumption() for x in result]) / sum([x.default_plan.fuel for x in result]) print fuel_saving self.assertAlmostEqual(0.948770385621, fuel_saving, delta=10 ** -10)
"start_pos": {"i":0, "x":0}, "t_s": 1000 }, 1: { "arrival_dline": 150000, "path": np.array([1, 3, 4, 5]), "path_set": {1, 3, 4, 5}, "path_weights": np.array([80000, 1000000, 157100]), "start_pos": {"i": 0, "x": 0}, "t_s": 1500 } } routes = get_routes(TEST_FOLDER) # route_info = get_route_info(TEST_FOLDER) result = dynamic_simulation(GreedyPlatooning(), folder=TEST_FOLDER) # result = simulation(TEST_FOLDER, GreedyPlatooning()) # routes = { # 1: {"lat": 0, "lon": 500}, # 2: {"lat": 0, "lon": 0}, # 3: {"lat": 500, "lon": 0}, # 4: {"lat": 5000, "lon": 0}, # 5: {"lat": 5500, "lon": 500}, # 6: {"lat": 5500, "lon": -500}, # } start([result, routes]) # route_data = {} # route_data["node_coords_lat"] = np.array([100, 200, 300]) # route_data["node_coords_lon"] = np.array([100, 100, 200])