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])