Travel Demand Forecasting and Model Application
Friday, September 14, 2018
9 a.m. - noon EDT
Fort Lauderdale, FL, United States
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BAPA is continuing its collaboartin with FSUTMS Users Group for a September 14 Meeting entitled Travel Demand Forecasting and Model Application. The meeting includes three presentations:
The first presentation is titled “AirSage OD Data, GPS Update and Travel Time Validation”, and It will be given by Mr.Bill King, PE, of AirSage
The following is the abstract of the presentation:
AirSage is the leader in providing insights on population mobility from passive spatio-temporal data. AirSage delivers these insights through a suite of data products, which provides population mobility metrics across all of Continental US, Alaska, Hawaii, and Puerto Rico. Data products are developed from a nationwide sample of anonymized and encrypted GPS sightings (location traces) generated by
communication devices. AirSage using its proprietary algorithm analyzes GPS sightings generated by each sample communication device across the nation over a period of one calendar month to estimate home and work locations for the sample device. On average, the algorithm estimates home and work census block for a sample more than 120 million devices per month.
We now have GPS data that has persistent ID's for the life of the device. Pervasive coverage...GPS follows everywhere and uploads when cell service is resumed. And of course, GPS data is precise. We now can pin the stops down at the actual address.
This presentation will focus on Airsage OD data and metrics, travel time validation for planning and modeling applications.
The second presentation is titled “Use of US Census Data for Transportation Modeling and Planning”, by Mr. Yongqiang Wu, PE, of CTS Engineering, Inc.
The following is the abstract of the presentation:
With the rapid advent of highly automated vehicles, many transportation analysts and researchers are anticipating the growth of new transportation modes. The new mode most commonly anticipated is often called the “shared automated vehicle” or SAV. These modes would be like an automated Uber – they would come to a passenger upon electronic hailing, pick them up at or close to their origin, and then deliver them to their destination without a transfer. SAVs are a shared mode in that the vehicle is not owned by the passenger, rather being provided by a service provider who owns and manages the vehicle fleet. SAVs combine the convenience of point-to-point travel on demand, at any time of day or night, without having to deal with the financial and logistical burdens of vehicle ownership, i.e. parking, vehicle maintenance, and vehicle insurance. As such, many transportation analysts are anticipating a rapid growth of SAV mode share after such services are introduced.
Because these proposed SAV modes do not exist yet, it is particularly difficult to anticipate their impacts, especially at the transportation-system scale. Researchers have begun to investigate the potential impacts of SAVs through modeling and simulation by asking various what-if questions, i.e. what if an SAV system served 2% of existing trips in a metropolitan region? In this presentation I will provide a broad overview of such simulation efforts, their strengths, and their limitations. The presentations include recommendations for such simulation efforts to make them more transparent and generalizable.
I will briefly review my own research results regarding the potential replacement of public transit with SAVs for Ann Arbor, Michigan. Then I will conclude by discussing some interesting results from the International Transport Forum regarding the potential for new shared mobility modes to transform the transportation system in Portugal based on a very detailed model of travel behavior.
The third presentation is titled “Model Development & Model Applications at the Atlanta Regional Commission: How ARC is using the Activity-Based Model for Regional Transportation Planning”, by Mr. Guy Rousseau of ARC.
The following is the abstract of the third presentation.
The Atlanta Regional Commission (ARC) activity-based travel demand model is designed to, at a minimum; represent the state of the practice in travel demand modeling and to meet all modeling requirements in the US EPA Transportation Conformity Rules. Since the late 1990s, a full consultation process, peer reviews and the ARC strategic travel demand model enhancement program have guided all modifications to the travel demand model. As a result, all elements of the travel demand model are designed to support all technical and policy decisions that are required in developing a comprehensive, multimodal transportation plan and program in accordance with the latest and greatest planning assumptions. The Activity-Based Model (ABM) of the Atlanta Regional Commission (ARC) forecasts typical weekday travel undertaken by residents of the ARC region. It is one of the components of the ARC regional travel demand model, along with the truck, airport, external-external and external-internal models. This model has been developed to ensure that the regional transportation planning process can rely on forecasting tools that are adequate for new socioeconomic environments and emerging planning challenges. It is equally suitable for conventional highway projects, transit projects, and various policy studies such as highway pricing and HOV analysis.
Bill King Ph.D
Yongquiang Wu, PE
Marilyn Mammano, firstname.lastname@example.org