cd.ethz.idsc.amodeus

Autonomous mobility-on-demand simulation library, version 1.8.8

Purpose

This repository is a library that allows the simulation of autonomous mobility-on-demand (AMoD) system including their fleet management algorithms in the multi-agent transportation simulation environment MATSim.

Try it, orchestrate your own fleet of amod-taxis! To get started, install and run amod. Here is a visualization.

Our website is amodeus.science.

Features

The code manages the dispatching of autonomous taxis in the MATSim environment. It provides standard autonomous mobility-on-demand dispatching algorithms and an API to implement and test novel ones.

Available Unit Capacity Dispatching Algorithms

• Adaptive Real-Time Rebalancing Policy from Robotic load balancing for mobility-on-demand systems by Pavone, M., Smith, S.L., Frazzoli, E. and Rus, D., 2012.
• Feedforward Fluidic Optimal Rebalancing Policy from Robotic load balancing for mobility-on-demand systems by Pavone, M., Smith, S.L., Frazzoli, E. and Rus, D., 2012.
• Global Bipartite Matching Policy fromRuch, Claudio, Sebastian Hörl, and Emilio Frazzoli. "Amodeus, a simulation-based testbed for autonomous mobility-on-demand systems." 2018 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2018.
• SQM algorithm from Fundamental Performance Limits and Efficient Polices for Transportation-On-Demand Systems by M.Pavone, K.Treleaven, E.Frazzoli, 2010.
• Demand-supply-balancing dispatching heuristic from Large-scale microscopic simulation of taxi services by Maciejewski, M., and Bischoff J., 2015.
• First Come First Served Strategy with Grid Rebalancing from Operations of Shared Autonomous Vehicle Fleet for Austin, Texas, Market by Fagnant, D. J., Kockelman, K. M., and Bansal, P., 2015.
• Feedforward time-varying rebalancing policy from Spieser, Kevin, Samitha Samaranayake, and Emilio Frazzoli. "Vehicle routing for shared-mobility systems with time-varying demand." American Control Conference (ACC), 2016. IEEE, 2016.

Available Ride Sharing Dispatching Algorithms

• Demand-supply-balancing with Beam Extension for Ride Sharing Demand Supply Balancing heuristic from Large-scale microscopic simulation of taxi services by Maciejewski, M., and Bischoff J., 2015 extended with ride sharing if two requests start close to each other and have a similar direction.
• Dynamic Ride Sharing Strategy from Dynamic ride-sharing and optimal fleet sizing for a system of shared autonomous vehicles by Fagnant, D. J., and Kockelman, K. M., 2015.
• T-Share from Ma, Shuo, Yu Zheng, and Ouri Wolfson. "T-share: A large-scale dynamic taxi ridesharing service." Data Engineering (ICDE), 2013 IEEE 29th International Conference on. IEEE, 2013.
• High-Capacity Algorithm from Alonso-Mora, Javier, et al. "On-demand high-capacity ride-sharing via dynamic trip-vehicle assignment." Proceedings of the National Academy of Sciences 114.3 (2017): 462-467.

Gallery

Integration

Specify repository and dependency of the amodeus library in the pom.xml file of your maven project:

<repositories>
  <repository>
    <id>amodeus-mvn-repo</id>
    <url>https://raw.github.com/idsc-frazzoli/amodeus/mvn-repo/</url>
    <snapshots>
      <enabled>true</enabled>
      <updatePolicy>always</updatePolicy>
    </snapshots>
  </repository>
</repositories>

<dependencies>
  <dependency>
    <groupId>ch.ethz.idsc</groupId>
    <artifactId>amodeus</artifactId>
    <version>1.8.8</version>
  </dependency>
</dependencies>

The source code is attached to every release.

Misc

So beherrscht mein äusserer Sinn die physische, mein innerer Sinn die moralische Welt. Alles unterwirft sich meiner Willkür, jede Erscheinung, jede Handlung kann ich nennen, wie es mir gefällt; die lebendige und leblose Welt hängt an den Ketten, die mein Geist regiert, mein ganzes Leben ist nur ein Traum, dessen mancherlei Gestalten sich nach meinem Willen formen. Ich selbst bin das einzige Gesetz in der ganzen Natur, diesem Gesetz gehorcht alles.