Estimation of Accurate Path Length with Geospatial Data Analysis
Rapport, 2024
The core objectives of this study included creating a backend system to process and sort road data, deploying multiple path length estimation methods, and quantifying their accuracy using standard measures. The performance of each method was showcased through a case study, highlighting their effectiveness in different scenarios. Additionally, the study developed a deterministic Operating Cycle (dOC) model to encapsulate road data and facilitate residual range prediction in simulations. For the complete code, click the button in the top right corner "read online". To download the technical report, click the top right corner "read full text" button.
Road data
dOC
Path length estimation
Författare
Carl Emvin
Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system
Yogeswaran Amsavalli
Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system
Fredrik Bruzelius
Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system
Bengt J H Jacobson
Chalmers, Mekanik och maritima vetenskaper, Fordonsteknik och autonoma system
Rickard Andersson
Volvo Group
Nytta och förtroende för elektriska fordon (U-FEEL)
Volvo Group, 2022-10-01 -- 2025-09-30.
Volvo Cars, 2022-10-01 -- 2025-09-30.
Energimyndigheten (P2022-00948), 2022-10-01 -- 2025-09-30.
Volvo Group, 2022-10-01 -- 2025-09-30.
Scania CV AB, 2022-10-01 -- 2025-09-30.
Styrkeområden
Transport
Ämneskategorier
Farkostteknik
Datorseende och robotik (autonoma system)
Multidisciplinär geovetenskap
Utgivare
Chalmers