Since version 1.5.0 SUMO supports simulation of demand responsive transport (DRT) via the taxi device. This allows a fleet of taxis to service customer requests based on a configurable dispatch algorithm.
While the taxi capabilities are under development, their status can be checked via Issue #6418.
A vehicle can be equipped with an Taxi device to make it part of the taxi fleet.
To attach a Taxi device to a vehicle, the standard device-equipment
procedures can be applied using
For instance, a single vehicle can configured as taxi as in the following minimal example
<vehicle id="v0" route="route0" depart="0" line="taxi"> <param key="has.taxi.device" value="true"/> <stop lane="C0D0_1" triggered="person"/> </vehicle>
Note, that the stop definition is used to keep the taxi waiting in the simulation until the first dispatch is received.
Direct ride hailing#
A person can be defined as taxi customer with the following definition:
<person id="p0" depart="0.00"> <ride from="B2C2" to="A0B0" lines="taxi"/> </person>
A person can also use a taxi by including it as a personTrip mode:
<person id="p0" depart="0.00"> <personTrip from="B2C2" to="A0B0" modes="taxi"/> </person>
Groups of Persons#
Multiple persons can travel together as a group using attribute
group (if the taxi has sufficient capacity):
<person id="p0" depart="0.00"> <ride from="B2C2" to="A0B0" lines="taxi" group="g0"/> </person> <person id="p1" depart="0.00"> <ride from="B2C2" to="A0B0" lines="taxi" group="g0"/> </person>
The dispatch algorithm assigns taxis to waiting customers. The algorithm is selected using option --device.taxi.dispatch-algorithm ALGONAME. The following algorithms are available
- greedy: Assigns taxis to customers in the order of their reservations. The closest taxi (in terms of travel time) is assigned. If the reservation date is too far in the future, the customer is postponed.
- greedyClosest: For each available taxi, the closest customer (in terms of travel time) is assigned. If the reservation date is too far in the future, the customer is postponed.
- greedyShared: like 'greedy' but tries to pick up another passenger while delivering the first passenger to it's destination. The algorithm supports parameters absLossThreshold and relLossThreshold to configure acceptable detours.
- routeExtension: like greedy but can pick up any passenger along the route and also extend the original route (within personCapacity limit).
- traci: Dispatch is defered to traci control. The algorithm only keeps track of pending reservations
User-contributed dispatch algorithms are welcome.
To make a taxi stay in the simulation it receives a stop with attribute
triggered="person" after servicing a customer.
It is recommended to also define such a stop in the xml input so that the taxi can wait for the first customer.
By default, taxis will remain in the simulation until all persons have left. To make them leave the simulation at an earlier time, the end time can be defined using a generic parameter in their
<vType id="taxi" vClass="taxi"> <param key="has.taxi.device" value="true"/> <param key="device.taxi.end" value="3600"/> </vType>
To couple an external dispatch algorithm to SUMO, the following TraCI functions are provided:
To make use of these functions, the option --device.taxi.dispatch-algorithm traci must be set
- traci.vehicle.dispatchTaxi(vehID, reservations)
This set of API calls can be used to simplify writing custom dispatch algorithms by letting sumo:
- manage existing reservations
- manage the taxi fleet
- dispatch a taxi to service one or more reservations by giving a list of reservation ids (vehicle routing and stopping is then automatic).
The Taxi device generates output within a tripinfo-output file in the following form:
<tripinfo id="trip_0" ... > <taxi customers="5" occupiedDistance="6748.77" occupiedTime="595.00"/> </tripinfo>