mobility-modeling

Luxembourg SUMO Traffic (LuST) Scenario

Monaco SUMO Traffic (MoST) Scenario

simobility - light-weight mobility simulation framework. Best for quick prototyping

An Activity-based Multi-modal Mobility Scenario Generator for SUMO. This project is available in the Eclipse SUMO contributed tools section (https://github.com/eclipse/sumo/tree/master/tools/contributed) under the name SAGA (SUMO Activity GenerAtion).

LSTM Mobility Model implementation using Tensorflow

Urbano: Plugin for Rhino/Grasshopper

Python Parking Monitoring Library for SUMO

A Spherical Hidden Markov Model for Semantics-Rich Human Mobility Modeling (AAAI 2018)

More than a billion of the rural merchants in the developing world commonly depend on hiring on-demand transportation services to commute people or goods to markets. The process of selecting the optimal fare involves handling decision-making characterised with multiple alternatives and competing criteria. Decision support systems are commonly used to solve these types of problems. However, most widely used systems are based on object-based approaches which lack high-level abstractions needed to effectively model and scale human-machine communication. This paper reviews previous literature on the field and introduces an improved preliminary agent-based decision-support approach to overcome those challenges. As a proof of concept, we developed a two-agent simulation that, given a request from one of the agents, the other one takes a dataset of a stratified sample of 104 Ethiopian commuter criteria preferences taken from the Dukem region and an exemplary dataset of fare alternatives. The assistant agent computes those datasets using widely used HPA and TOPSIS algorithms to weight, score, rank those alternatives. Once we run the simulation, in a matter of milliseconds the assistant agent effectively returns an optimal prescription to the other agent, storing all interactions in a self-contained memory resulting in an architecture that allows developers to program further customisation as interactions scale.

Simulator developed for the mobility management of UAV base stations project featuring A3C

A modern agent-based modeling platform for mobility-on-demand simulations.

Codebase for SIGSPATIAL ARIC 2020: Data-Driven Mobility Models for COVID-19 Simulation

A high-capacity on-demand ride-sharing simulator, with three representative vehicle dispatch algorithms implemented.

Code for "Learning the Relation Between Mobile Encounters and Web Traffic Patterns: A Data-driven Study" MSWiM 2018 (ACM: https://dl.acm.org/citation.cfm?id=3242137, Tech Report: https://arxiv.org/abs/1808.03842)

Exploring mobility patterns in US cities

Orderd logit model based on the Mobility and Transport Microcensus 2015 explaining the number of trips (from home to work for now) in Switzerland.

Test on various scenarios using NS3

Sadie: Stochastic Agents in DIscrete time and Euclidean space

Distributed agents for mobility generation

Fleet Supply-Demand Simulator for Autonomous Bike Sharing Services using Boston as Test Bed (2016-2019)