Dynamic Ride-Sharing (DRS) for MATSim

This MATSim module (or extension) simulates dynamic ride-sharing (DRS), i.e. it enables car drivers to pick up other agents, share a ride with them in the same vehicle, and drop them off before continuing their own trip.

In more detail DRS can be defined as follows:

• Drivers using a private car pick up riders for a part of their trip
• The driver's trip is part of the daily routine (not an additional trip with the sole purpose of picking up a rider)
• Driver and rider are not necessarily acquaintances
• Matching is facilitated through a platform (e.g. app) on a trip-by-trip basis (which defines the dynamic part of the DRS acronym)

Related Work:

Often passengers in cars have been incorporated as ride agents teleported from one activity location to another using car travel times and without being matched with other agents (e.g. Ziemke et al (2019)). While this approach suffices for private ride-sharing, it fails to represent the potential for DRS where non-acquaintances share rides to reach similar destinations.

Wang et al (2017) conducted previous endeavors to model DRS in MATSim, employing the dvrpmodule (source code). Their approach involved introducing a dynamic agent alongside the standard population agent during simulation iterations, specifically chosen when the leg's mode is ride share driver.

Simulation of DRS

The implemented DRS has the following additional properties / restrictions:

• A maximum of one rider is allowed per DRS trip
• Pickup and dropoff of the rider takes place directly at the rider's activity locations
• Matching of drivers and riders is done before the start of each day (no spontaneous requests during the day or during the trip), i.e. in the replanning phase of the MATSim loop before mobsim. In comparison to Wang et al (2017) this approach reduces complexity and avoids waiting time for the rider, since with the dvrp module only allows a rider to request a ride when he already wants to depart.

New modes of transport

• drsDriver
• drsRider

New person attribute

Agents require the a priori attribute drsAffinity that determines if they are potential driver, rider, both or no DRS user.

• drsAffinity must be set for each person to either
  • driverOrRider
  • driverOnly
  • riderOnly
  • none

In more detail, DRS is integrated into the MATSim loop as follows:

Replanning

First the slightly adjusted innovation strategy SubtourModeChoiceForDrs assigns the new modes drsDriver and drsRider to agents' subtours. This assignment can be restricted with the optional person attribute drsAffinity. Then requests are collected and matched based on origin, destination, departure time and detour time. The riders' acceptance of deviations to their desired departure time can be controlled with the DRS config parameter riderDepartureTimeAdjustmentSeconds. The agents' plans are adjusted accordingly. This entails adding pickup and dropoff activities at the riders' origins and destinations to the plans of matched drivers. For matched riders the departure time is adjusted if necessary.

Mobsim

Each matched driver proceeds to the specified pickup point to collect the assigned rider. The DRS config parameter pickupWaitingSeconds determines how long a driver waits for a delayed rider before proceeding. Subsequently, the driver transports the rider to the designated dropoff point. Concurrently, matched riders await the arrival of their driver for pickup and subsequently for dropoff at the predetermined locations. Riders that could not be matched still get a mobility guarantee and are teleported to their next activity based on teleportedModeParameters in the planscalcroute config.

Note, that to successfully simulate DRS it is necessary to (1) kickstart the pool of potential drivers and (2) to assign costs to the mobility guarantee. Before the first iteration all agents that can potentially act as a driver are assigned a copy of their original plan with as many driver legs as possible. This avoids the problem of riders not finding a match. On the other hand the mobility guarantee must be assigned a cost with the DRS config parameter riderMobilityGuaranteeMonetaryConstant. Otherwise unmatched ride trips can make up a relevant part of the modal split when ideally they should only occur in negligible amounts.

Before next iteration

Adjustments to the agents' plans are reverted.

Usage

Installation

Releases and snapshots are available on repo.matsim.org.

To include the DRS module in your maven project, add the MATSim repo and the following dependency to your pom.xml:

<repositories>
    <repository>
        <id>matsim</id>
        <url>https://repo.matsim.org/repository/matsim/</url>
    </repository>
</repositories>

<dependencies>
    <dependency>
        <groupId>at.ac.ait.matsim</groupId>
        <artifactId>matsim-drs</artifactId>
        <version>VERSION</version>
    </dependency>
</dependencies>

Currently available VERSIONs are:

• 14.1
• 15.0-SNAPSHOT

The DRS module's major version (e.g. 14) corresponds to the MATSim version it is compatible with.

Config Parameters

config_drs.xml serves as a complete example on how to configure a DRS scenario. Note, that other modules must be configured in a specific way as well, e.g. qsim.

List of all parameters:

Costs

• carAndDrsDailyMonetaryConstant: Daily price for car usage including when using the private car as drsDriver. If specified here do not additionaly specify it in planCalcScore.scoringParameters.modeParams.dailyMonetaryConstant - otherwise it will be counted twice (typically negative)
• driverProfitPerKm: The amount of money per kilometre the driver gains for a rider (typically positive)
• riderMobilityGuaranteeMonetaryConstant Price per unmatched rider trip. Such trips are typically teleported, imagine the rider e.g. gets provided a taxi. Use to avoid unmatched rider trips to get an attractive mode on their own. (typically negative)
• Note, that for the drsRider's costs there is no parameter, because this should be set in planCalcScore.modeParams.monetaryDistanceRate (typically negative)

Matching Algorithm

• cellSize: The side length of square zones in meters used in zonal registers of riders requests. The default value is good for urban areas. For large areas with sparsely distributed population and low drs share, you may consider using a bigger cell size. On the other hand, if neighbourhoodSize is very low, a smaller cell size may work better.
• maxPossibleCandidates: Limits the number of possible riders requests considered for a driver during the matching process. Used to speed up computations, values 20 to 40 make a good trade-off between computational speed and quality of results. To turn off this feature specify a sufficiently big number (not recommended).
• minDriverLegMeters: minimum length of legs (routed with the drsDriver mode) to be considered for the drs driver mode. 0 means no minimum.
• minRiderLegMeters minimum length of legs (routed with the drsDriver mode) to be considered for the drs ride mode. 0 means no minimum.
• timeSegmentLengthSeconds: The duration of the time segments used in time segment registers of riders requests. To avoid scenarios where a driver and a rider departure time are close but cross a segment boundary candidate requests are token not only from the current segment but also from the one before and after.

Simulation / Plan Adjustment

• pickupWaitingSeconds The amount of time the driver is expected to wait until the rider enters the vehicle.
• riderDepartureTimeAdjustmentSeconds The amount of time the riders are willing to adjust their departure times. During the matching process, the arrival of driver to pick-up point is checked whether it is within the rider departure time +- the riderDepartureTimeAdjustment.

Plan Innovation

• subtourModeChoiceChainBasedModes: Defines the chain-based modes for the SubtourModeChoiceForDrs strategy, separated by commas.
• subtourModeChoiceModes: Defines all modes available for the SubtourModeChoiceForDrs strategy, including chain-based modes, separated by commas.

Run Example

The main method of RunSimpleDrsExample takes only the config file as an input in order to run.

• It automatically adds drsDriver mode as an allowed mode to all car links.
• It automatically kick-starts all potential drsDriver agents, i.e. with an according drsAffinity + car + license availability, with a drsDriver plan.

This should assure, that at the beginning of the simulation many drivers are present and "starvation" of the people choosing rider mode is avoided. (MATSim guarantees to try out / score all un-scored plans of an agent - see RandomUnscoredPlanSelector - before a different plan is selected e.g. via SelectPlanExpBeta).

Mode Innovation

Mode innovation relies on an adapted version of the innovation strategy SubtourModeChoice named SubtourModeChoiceForDrs. SubtourModeChoiceForDrs will by default add the DRS driver and rider mode to the mix and can also be configured via the relevant parameters in the drs config group.

Output

The following output files are additionally created in the MATSim output directory:

• drs_rider_request_stats.txt/png: evolution of number of matched and unmatched rider requests
• drs_vkt_stats.txt/png: evolution of distribution of vehicle kilometers traveled by motorized individual transport between
  • DRS travel, i.e. parts of a DRS driver's trip with an actual rider
  • before and after DRS, i.e. parts of a DRS driver's trip to the pickup point / after dropping off the rider
  • individual travel, i.e. regular non-DRS car trips or unmatched DRS driver trips
• drs_[un]matched_trips.csv: details for all matched and unmatched trips of the last iteration
• drs_sim_stats.csv: number of actually successful pickups and stuck riders in mobsim (found in the ITERS/it.x folders)

Limitations & Future Work

• Only one rider is supported per driver's trip (but a driver may take different riders along on different trips).
• If a drsDriver can not pick up a drsRider because it is not there it will still make the detour to the dropoff place. A future improvement is to optimize the drivers route on the fly in such cases
• pickupWaitingSeconds prolongs pickups in case the rider is not already waiting when the driver arrives However, even if the rider arrives soon after the driver starts waiting for him, the driver will only depart when the full pickupWaitingSeconds are over.
• Unmatched drivers and riders even after reaching equilibrium account for 6% and 0.3% respectively for our Upper Austria model. Ideally that should be 0.
• Improve the matching algorithm
  • Option for predefined pickup points (instead of door-to-door)
  • Use sociodemographic attributes in the matching algorithm, not only for scoring
  • Avoid local optimums (and implement a more complex optimization algorithm)

Literature

Reference publications

• Müller, J., Nassar, E., Straub, M., Chou, A. T. M., 2024. Integrating Dynamic Ride-Sharing into an Agent-Based Traffic Simulation: A Sensitivity Analysis. 103rd Annual Meeting of the Transportation Research Board
• Nassar, E., 2023. Integrating Dynamic Ride-Sharing in MATSim. Master’s thesis. Technical University Munich.

Related

• Wang, B., Liang, H., Hörl, S., Ciari, F., 2017. Dynamic ride sharing implementation and analysis in matsim. hEART 2017.
• Ziemke, D., Kaddoura, I., Nagel, K., 2019. The matsim open berlin scenario: A multimodal agent-based transport simulation scenario based on synthetic demand modeling and open data. Procedia computer science 151, 870–877.

License & Credits

The DRS module is GPL-2.0-or-later licensed for maximum compatibility with MATSim.

This work was developed by Eyad Nassar for his master's thesis (Nassar, 2023) with support of Markus Straub and Johannes Müller.

It is part of the lead project DOMINO, which was promoted and financed within the framework of the RTI programme Mobility of the Future by the Federal Ministry for Climate Protection, Environment, Energy, Mobility, Innovation and Technology (BMK) and handled by the Austrian Research Promotion Agency (FFG) under grant 3300226.

If you have any questions, remarks, or collaboration ideas, please get in touch: either via GitHub or via email to markus.straub or johannes.mueller (both at ait.ac.at).