Monthly Archives: June 2024

MaaS Platform Equilibrium Model

MaaS Platform Equilibrium Model is a tool designed to model the decisions of travelers and operators in a Mobility-as-a-Service (MaaS) platform, allowing platform subsidy plans to to achieve a desirable equilibrium. The model considers different types of services providers: Mobility-on-Demand (MoD) operators and traditional fixed-route transit operators. It facilitates efficient management and coordination between users, operators, and the platform within a mobility ecosystem.

The model takes the network structure of the operators, travelers’ and operators’ costs, traveler demand, and a system objective, and outputs the assignment of traveler demand, operators’ operation decisions, and subsidy plans that optimizes the system objective. Potential system objectives includes minimizing system total costs, maximizing equity indices, minimizing GHG emissions, etc. The current tool considers minimizing system total costs.

The tool is coded in Python 3.8.5, which could be found here. 

Urban freight tour data set synthesized for NYC

What are the truck patterns in NYC? In this C2SMARTER Center project we (Haggai Davis, III, Hector Landes, Farnoosh Namdarpour, Hai Yang, Kaan Ozbay) synthesized truck tours from public data to provide a publicly available data set for researchers and policymakers for estimating truck VMT, evaluate impacts of truck routes, and relating those to different freight industries. It makes use of route data shared by NYC DOT (thanks Diniece Mendes, EIT A.M ASCE and team!) with borough-level screenline errors of ~10%. We can use the data to evaluate scenarios like “if truck sizes were reduced by 20%”, a preliminary assignment suggests a 49% reduction in ESALs (and impact on pavement) while increasing GHG emissions by 25%. The synthetic data are designed to be compatible with MATSim-NYC v2.0, and should be useful for evaluating off-hour deliveries, truck electrification scenarios, and multimodal last mile deliveries. The output synthetic truck tour data can be found here: https://zenodo.org/records/8000176.

Paper here: https://www.sciencedirect.com/science/article/abs/pii/S0965856424001551