Multidimensional vehicle loads and capacities for Demand Responsive Transport in MATSim

Tarek Chouaki, Sebastian Hörl

13 June 2025

MATSim User Meeting 2025

• MATSim allows to simulate on-demand mobility services (DRT)
   
• For a long time, one request represented one person and one seat in the fleet management algorithm
   
• However, it is useful to cover situations with more complex loads and capacities:
  • Groups of passengers (multiple persons)
  • Passengers with luggage (and luggage space in vehicles)
  • Transportation of goods ...
  • ... with compartments for normal and cold goods
  • and so on ...
     
• Large interest in hybrid on -demand services for the transport of passengers and goods in literature

Introduction

• Group travel (contribution by MOIA)
  • Allows to assign a group identifier to each request
  • Requests with the same group identifier much be dispatched together (i.e. occupying multiple seats in the vehicle)
  • Allows for the simulation of group bookings
     
• Companions (contribution by Volkswagen)
  • Samples, for each traveler request, a couple of virtual agents that represent accompanying persons
  • Using the group identifier functionality, group requests can be simulated comfortably
  • Number of companions is sampled according to predefined distributions (zero, one, two companions, ...)

Existing work

• Each request has a latest departure time and a latest arrival time
  
  
  
   
• Each vehicle has a schedule of tasks
  
  
  
   
• The goal of DRT's insertion algorithm is to insert a pickup and a dropoff for a new request such that not timing constraints of the requests (new and existing) are violated.
   
• And, importantly, the capacity constraint (= seats) of the vehicle should not be violated

DRT Algorithm

Pickup R2

Pickup R1

Dropoff R1

Dropoff R2

• Previously, a capacity was simply represented by an integer
• Now, a capacity (and each load of a request) is represented by a complex object
• The DvrpLoad interface encapsulates arithmetic operators

Modifications

int

• Previously, a capacity was simply represented by an integer
• Now, a capacity (and each load of a request) is represented by a complex object
• The DvrpLoad interface encapsulates arithmetic operators
• DvrpLoadType is a global instance that manages creation of load objects

Modifications

• Previously, a capacity was simply represented by an integer
• Now, a capacity (and each load of a request) is represented by a complex object
• The DvrpLoad interface encapsulates arithmetic operators
• DvrpLoadType is a global instance that manages creation of load objects

Modifications

Initializes the load of a vehicle (= empty)

• Previously, a capacity was simply represented by an integer
• Now, a capacity (and each load of a request) is represented by a complex object
• The DvrpLoad interface encapsulates arithmetic operators
• DvrpLoadType is a global instance that manages creation of load objects

Modifications

Set up the load of a request or the capacity of a vehicle

• Previously, a capacity was simply represented by an integer
• Now, a capacity (and each load of a request) is represented by a complex object
• The DvrpLoad interface encapsulates arithmetic operators
• The DRT InsertionGenerator is modified to limit insertion points

Modifications

Check whether a request can be inserted given the current load of a vehicle along the schedule

requestLoad.fitsIn(currentVehicleCapacity)

Modifications

Calculate the load after picking up a request

• Previously, a capacity was simply represented by an integer
• Now, a capacity (and each load of a request) is represented by a complex object
• The DvrpLoad interface encapsulates arithmetic operators
• The DRT InsertionGenerator is modified to limit insertion points

newOccupancy = occupancy.add(request.getLoad())

Modifications

Calculate the load after dropping off a request

• Previously, a capacity was simply represented by an integer
• Now, a capacity (and each load of a request) is represented by a complex object
• The DvrpLoad interface encapsulates arithmetic operators
• The DRT InsertionGenerator is modified to limit insertion points

newOccupancy = occupancy.subtract(request.getLoad())

Implementations

• By default, an IntegerLoadType / IntegerLoad implementation exists
   
• Alternatively, we offer the IntegersLoadType / IntegersLoad with independent slots
  • For instance, one slot for persons, one slot for luggage
  • Or, one slot for standard goods, one slot for cooled goods
     
• More complex implementations are possible, for instance:
  • Capacity for persons       ; load of persons for one request
  • Capacity for luggage       ; load of luggage for one request
     
  • Luggage either consumes space for persons (seats) or luggage
     

fitsIn: 

• The entire functionality can be used by
  • Modifying config.xml
  • Providing capacities in vehicles.xml / fleet.xml
  • Providing loads in population.xml
     
• No code modification necessary!

Usage

• Enabling multi-dimensional loads and capacities

Usage

A list of slot names can be provided in configuration when adding the load parameter set to the DRT mode configuration.

• Loads can be defined per trip (in the origin activity) or per person

Usage

Option 1: As a single string-based attribute

Option 2: As individual attributes per slot

Option 3: If no attributes are specified, one agent equals one capacity unit in the slot that is by default configured as "passengers"

• Capacities can still be defined using the fleet.xml file
• In the config.xml, it can be defined which slot the vehicle capacity represents

Usage

fleet.xml

• However, we recommend loading vehicles from a vehicles.xml (standard functionality in DRT already)
• Capacities can be defined per vehicle or per vehicle type using attributes

Usage

Option 1: As a single string-based attribute

Option 2: As individual attributes per slot

• Finally, MATSim vehicle types already provide capacity information:
  
  
  
  
  
   
• You can map those attributes to the slots via configuration:

Usage

• Furthermore, DRT has been extended to allow capacity changes of vehicles during the day
   
• This allows vehicles to update their configuration at a depot, for instance, to mount or unmount cooling equipment
   
• A new CapacityChangeTask is introduced to DRT that defines a new capacity for the vehicle. It can be inserted into the vehicle schedules by a custom logic to be implemented by the user.

• The insertion algorithm has been updated to track the vehicle's capacity while going through possible insertion points.

Bonus: Capacity changes

• No noticeable impact

Impact on performance

• For more details, see our presentation for hEART!
   
• Randomly generated demand for Paris
  • 10,000 passenger requests with two peaks
  • 5,800 food requests with two different peaks
  • Both have different criteria (only latest arrival time for food)

Example

• For more details, see our presentation for hEART!
   
• We propose an algorithm that adaptively reconfigures the fleet throughout the day to serve as much demand as possible

Example

Questions?

https://slides.com/sebastianhorl/mum25-drt