Principal Investigator

Erick Guerra

Status

Active

Start Date

July 1, 2024

End Date

June 30, 2025

Project Type

Research Advanced

Grant Program

US DOT BIL, Safety21, 2023 - 2028 (4811)

Grant Cycle

Safety21 : 24-25

Visibility

Public

Abstract

Digital tools for mapping are now an integral tool for navigation. Waze, Google maps have leveraged Satellite and Google Street imagery which allow us to have an accurate representation of any set of GPS coordinates. This technology evolved just a couple of months ago with the release in May 2023 of dynamic models of the Earth. Companies like Cesium, a Google backed up startup based in Philadelphia is offering Unity and Unreal models of the Earth, with an Application Programming Interface (API) that can be leveraged for any dynamic Geospatial application. While a number of drone applications have been developed, no solid test has been developed for a driving application.
This proposal continues a project with Jitsik LLC, a small startup in Mixed Reality, testing the Unity and Unreal API of the Earth to create Virtual Reality models and extends the work for application as a planning support tool. We propose to continue to focus on Roosevelt Blvd in Philadelphia, which has already been the subject of academic research (Dr.Guerra) and is at the center of ongoing advocacy work by Dr. Guerra’s PhD student Jay Arzu to redesign the Boulevard to improve safety and accommodate high-capacity transit infrastructure. The main idea is to develop drivable virtual models of existing conditions, as well as proposed infrastructural changes, such as lane removals, an elevated train, and exclusive bus only lanes. This environment will support the Environmental Impact Review process as state agencies develop locally preferred investment priorities and design alternatives to share with the public.
We will also work with the City of Philadelphia to identify and install cameras on roadway segments that will receive speed camera enforcement based on new legislation. We will develop digital twins for selected roadway corridors and control segments. We will also collect camera data from before and after camera enforcement to examine how speed cameras affect driver behavior and use these data to simulate driver behavior for our digital twin simulator.
By developing and interactive model, we hope to help residents better understand the implications of public policies, such as speed cameras and roadway redesigns, and democratize the review process, which currently often requires a basic understanding of plan views, sections, and other technical drawings for full citizen interaction.

Please note that this project is a continuation of a year one project and includes the same partners.
    

Description

Timeline

Strategic Description / RD&T

This project is a Research Project at its Core. Should we be successful in establishing the value of the Earth 3D database for driving, we anticipate additional education and translational research projects will follow. These are the first translation application we are testing and will follow up with research work to understand the effects of the virtual models on citizens’ understanding of and support for alternative infrastructure proposal.


This project addresses the Safety goal of the US DOT Research, Development and Technology Strategic Plan (listed page 14) by targeting a critical artery in Philadelphia. In the previous 5 years, the Boulevard had accounted for 14% of the City of Philadelphia’s total traffic fatalities. The techniques developed in this project will translate into a toolkit that can be reused to create a digital twin of any other road in the US.

This project addresses the Transformation goal of the US DOT Research, Development and Technology Strategic Plan (listed page 50). It is indeed Data Driven as it leverages advanced data collection and data processing capabilities to create accurate, credible, and accessible information for decision making on infrastructure. This project leverages satellite and drone imagery of the existing US roads and aims at refining this model to prepare it for commercial use in safety and education. 

This project has a strong component in Technology Transfer and Deployment  as it precisely assesses the suitability of GeoSpatial computational models made available in Spring 2023 for practical applications. These applications will range from University studies, to planning by local authorities to education of young novice drivers. The models developed will also have a value for Urban Planning and Design.

Deployment Plan

Expected Outcomes/Impacts

This project is very ambitious as it aims to make satellite imagery of the earth drivable for urban planners, for driving safety and for education. Drivers may want to experiment driving on the left in the UK before renting a vehicle. Drivers may want to visualize a merge of highways before actually being there. Google released 3D visual directions for driving through its API. This project goes one step further by making these models drivable. 

Expected Outputs

We anticipate the development of a toolkit that can be reused for any neighborhood in the US, so that drivers can experience a simulated experience in the environment they live. The project will improve safety by paving the ground to Human Subject Research so that dangerous roadways can get better designed.

TRID

A search of “driving”, “earth”, “satellite” in the TRID database led to 7 references. Four references are anterior to 2005 when satellite positioning was limited by the Department of Defense GPS Selective Availability.  These references are not relevant to our project. For the three references.
In 2018, Gao et al published “GPS Modeling for Vehicle Intelligent Driving Simulation”. This article establishes a new GPS algorithm based on the functional characteristics of GPS. It does not address driving applications and is irrelevant to our application.
In 2020, Wang et al published “Development of Unmanned Roller and Its Application in Highway Engineering”. This article targets the development of a Highly Automated Vehicle for construction sites. Its use of GPS targets self-driving. It does not address the smoothness of the terrain, our research focus.
In 2021, Goswami et al published “Intersection of Automotive and Satellite Connectivity: Use Cases and Exploration of a Hybrid Model”. This paper explores a potential intersection of automotive and satellite connectivity. It is focused on connectivity and communication and does not address the quality of 3D mapping for driving applications. Our work is unique and pushes the limit of what can be accomplished with satellite imagery driving.

Individuals Involved

Email	Name	Affiliation	Role	Position
xiaoxiad@upenn.ed	Dong, Xiaoxia	University of Pennsylvania	Co-PI	Faculty - Adjunct
erickg@upenn.edu	Guerra, Erick	University of Pennsylvania	PI	Faculty - Tenured
helensloeb@gmail.com	Loeb, Helen	JitSik LLC	Co-PI	Other

Budget

Amount of UTC Funds Awarded

$

Total Project Budget (from all funding sources)

$161039.38

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