Autonomous Mower Pilot Project

Evans, John T; Shaver, Greg; Mardikes, Michael A; Sprague, Nathan C; Weigman, Timothy J; Supe, Shreyas; Brown, Ethan M

doi:10.5703/1288284317840

i

Autonomous Mower Pilot Project

2025-01-01
By Evans, John T ; Shaver, Greg ; Mardikes, Michael A

File Language:

English

Details

Creators:

Evans, John T ; Shaver, Greg ; Mardikes, Michael A ; Sprague, Nathan C ; Weigman, Timothy J ; Supe, Shreyas ; Brown, Ethan M
Corporate Creators:

Purdue University. Joint Transportation Research Program
Corporate Contributors:

Indiana Department of Transportation ; United States. Department of Transportation. Federal Highway Administration
Subject/TRT Terms:
Publication/ Report Number:

FHWA/IN/JTRP-2025/01
DOI:

https://doi.org/10.5703/1288284317840
Resource Type:

Tech Report
Geographical Coverage:

Indiana ; United States
Edition:

Final Report
Corporate Publisher:

Purdue University. Joint Transportation Research Program
Abstract:

The Indiana Department of Transportation (INDOT) spends approximately $19 million annually on roadside mowing, which is a process that is time-consuming, costly, and poses safety risks. Automated mowing solutions have the potential to reduce costs and increase safety, but they will need to be extremely well tested before being deployed. In this work, data from current mowing practices was collected using machine mounted cameras, which was used to inform the creation of a digital twin environment that allows for rigorous initial testing of potential autonomous solution with no risk. The digital twin was created using digital elevation models of Indiana highway corridors and geolocated features to create a high-fidelity test environment. Algorithms including path planning, obstacle avoidance, and road entry detection were created and tested in a simulation and validated in a real-world environment. Results showed that the digital twin was able to simulate real-world conditions and accurately demonstrate how the algorithms performed.
Format:

PDF
Funding:

SPR-4702
Download URL:

https://rosap.ntl.bts.gov/view/dot/85433/dot_85433_DS1.pdf
File Type:

[PDF - 9.00 MB]
Collection(s):

Autonomous Vehicles
Main Document Checksum:

urn:sha-512:0e8b4e34f14019213a0df0d0fcc89cbd22f5ccf232c96fb6cd5181de71f97d9047286e1f34fed9a6229ff0d702e911cb1242615541cfa4f90dd6b2140a7bd4cb

File Language:

English

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