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

Mer information

Senast uppdaterat

2024-08-14