Transport (road)

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Road transport model for Great Britain.

Inputs

description	name	unit	dims	dtype
Population	population	people	[‘lad_gb_2016’]	float
Regional Gross Value Added (rGVA)	gva	GBP	[‘lad_gb_2016’]	float
Fuel prices	fuel_price	£/l	[‘transport_fuel_type’]	float
Fuel price (electricity)	fuel_price_electricity	£/kWh	nan	float
Link travel time	link_travel_time	h	nan	float
Vehicle fleet composition (engine type proportion per vehicle type)	engine_type_fractions	nan	[‘vehicle_type’, ‘engine_type’]	float

Parameters

description	name	unit	dims	dtype
Population elasticity for passenger demand	POPULATION_ETA			float
GVA elasticity for passenger demand	GVA_ETA			float
Time elasticity for passenger demand	TIME_ETA			float
Cost elasticity for passenger demand	COST_ETA			float
Population elasticity for freight demand	POPULATION_FREIGHT_ETA			float
GVA elasticity for freight demand	GVA_FREIGHT_ETA			float
Time elasticity for freight demand	TIME_FREIGHT_ETA			float
Cost elasticity for freight demand	COST_FREIGHT_ETA			float
Averages link travel time with the time from previous iterations (1.0 = overwrite with new)	link_travel_time_averaging_weight			float
How many times to repeat the same assignment to obtain average times	assignment_iterations			int
How many times to iterate between flow prediction and flow assignment	prediction_iterations			int
Whether to use route-choice model (true) or routing with A-Star (false)	use_route_choice_model			bool

Outputs

description	name	unit	dims	dtype
Energy consumption (liquid fuels)	energy_consumption	l	[‘annual_day’, ‘transport_fuel_type’]	float
Energy consumption (electricity)	energy_consumption_electricity	kWh	[‘annual_day’]	float
Energy consumption (electricity, by start zone)	electric_vehicle_electricity_consumption	kWh	[‘lad_gb_2016’, ‘annual_day_hours’]	float
Electric vehicle trips	electric_vehicle_trip_starts	trips	[‘lad_gb_2016’, ‘annual_day_hours’]	int
Link travel time (used as input to next timestep)	link_travel_time	h	nan	float