https://peertube.watch/videos/watch/881c63af-2267-4624-bb5f-3ef954073d4b Trains are planned with margins compared to their fastest possible drive. Without them, they would not be able to catch up in case of a delay. A train departing 5 minutes late would arrive at least 5 minutes late. A driver accelerating or braking a bit slower than planned would inevitably be late. The entire transportation plan would fail. Those margins/allowances consist of adding extra time to the total running time. This implies planning trains with a lower speed than the maximum they could physically drive. There are many ways to lower the speed of a train along its trip, but one of them is particularely efficient in terms of energy savings. The algorithm MARECO, developped by SNCF, details an entire strategy for this purpose: how to plan a train that would intelligently drives slower in a way that consume the least amount of energy ? In this talk we will go though the main ideas of the algorithm, then we will compare its efficiency to other margin distribution stratgies on a few relevant examples, and finally we will discuss the impact of this algorithm on train planning and operation. Speaker: Alex Rolland, Track: Railways and Open Transport devroom, Room: K.4.401, When: Saturday 3 February 2024, 12:45–13:05 (Brussels time), Schedule: FOSDEM 2024 event page, Slides & links Slides, Licence: Creative Commons Attribution 2.0 Belgium (CC BY 2.0 BE) (as stated in the FOSDEM video archive). Attribution: “MARECO algorithm: how to drive a train using the least amount of energy” by Alex Rolland, FOSDEM 2024. Original recording: 2024/k4401/fosdem-2024-2650-mareco-algorithm-how-to-drive-a-train-using-the-least-amount-of-energy.av1.webm from the FOSDEM video archive. This channel is an unofficial mirror; FOSDEM is a free and non-commercial event organised by the community for the community. Sun, 18 Oct 2026 20:57:16 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://peertube.watch https://peertube.watch/lazy-static/avatars/3b284627-b75f-409e-ac2e-10f4c2946f43.png https://peertube.watch/videos/watch/881c63af-2267-4624-bb5f-3ef954073d4b All rights reserved, unless otherwise specified in the terms specified at https://peertube.watch/about and potential licenses granted by each content's rightholder.