Project Manager: Thomas Hill (Florida Department of Transportation)
Background
Micromobility is an emerging mode of transportation that has gained popularity in many cities in Florida and in the nation because it provides an alternative mobility option for commuters and residents nearby, particularly over the first mile and last mile services. The promotion of micromobility devices (i.e., bicycles, e-bikes, and electric scooters) is an important step to reduce people’s dependencies on private vehicles over a short travel distance, encourage the use of public transit, and fulfill the sustainable transportation goals. In Florida, these micromobility devices have been widely distributed in 15 cities due to their ease of accessibility, affordable access, and growing popularity as an innovative mobility alternative.
Meanwhile, there are some problems with micromobility systems, such as safety concerns, competing mode to transit, random laying-about of dockless rental scooters, conflicts with automobile traffic, and so on. Chief among them is the spatiotemporal mismatch between the supply and demand of micromobility devices. In other words, micromobility devices are often in oversupply or insufficient supply at certain time periods in certain geographic locations, which results in inefficient usage and mismanagement of devices, thus a potential safety hazard. Second, the current micromobolity planning (e.g., routing, device parking stations) are based on planners’ educated guesses. There is no modeling to guide the planning process. In addition, there is no clear answers whether the micromobility compete with or complement public transit.
However, there is no existing micromobility model in Florida and even in the nation. The main reason behind a lack of modelling framework for micromobility was an absence of micromobility data in the past because micromobility is new. Fortunately, there are now available usage data in different cities, which provides a good opportunity to understand travel behavior of micromobility users and to model the supply and demand of the micromobility services. As of the end of 2021, the state of Florida has 15 cities with micromobility services. Among them, at least four cities (Gainesville, Jacksonville, Orlando, and Tallahassee) have direct contracts with vendors of micromobility devices that the vendors, as the owner of micromobility data, are obligated to provide ridership data to the cities. With these available data, it is possible to model micromobility.
Project Objectives
The purpose of this research project is to assess and recommend a modelling framework for micromobility systems based on the usage data of micromobility services in Florida cities. Specifically, the following research questions are to be addressed in developing a modelling framework for micromobility:
(1) What are general patterns of micromobility usage and demand in Florida, in terms of users’ sociodemographic characteristics, travel time and distances, trip origins and destinations, trip purposes, as well as their relationships with land use types and intensities?
- Who use it? (e.g., users’ sociodemographic characteristics)
- Why to use it? (e.g., trip purposes, trip origins and destinations)
- When to use it? (e.g., travel time and distances)
- Where to use it? (e.g., locations, land use types and intensities, street characteristics)?
(2) What is the relationship between micromobility and existing transit services, for instance, whether the use of micromobility services competes with or complements public transit, and how does the relationship vary by travel time and distances?
- Does the use of micromobility services compete with or complement public transit?
- How does the relationship vary by travel time and distances?
(3) What is the relationship between micromobility usage and infrastructure characteristics, how to derive potential micromobility usage from other transportation big data like streetlight, and what is the implication for future transportation infrastructure planning like the complete street program?
- What is the relationship between micromobility usage and infrastructure characteristics?
- How do we derive potential micromobility service areas and usage information from existing transportation data sources like the streetlight data?
- What is the implication for future transportation infrastructure planning like the complete street program?