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#transit

@SunLau_: Sharing a site I've been obsessed with for two days — OpenRailwayMap. Recently I've been following the progress of the Tongsu-Jiayong high-speed railway and found it by accident. It has been online since 2013 and, through continuous updates, now covers mainstream rail transit networks worldwide (including trams, subways, conventional and high-speed trains, etc.). Lines under construction are also drawn based on public information. Based on the selected...

X AI KOLs Timeline ↗ · 2026-08-13 Cached

The author shares a site called OpenRailwayMap. Since going online in 2013, it covers mainstream rail transit networks worldwide, allowing users to view infrastructure, speed, and other information, and also draws lines under construction.

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#transit

Mitigating Bus Bunching with Reinforcement Learning Enhanced by Semantic Stop Embedding

arXiv cs.AI ↗ · 2026-08-12 Cached

This paper proposes an LLM-assisted semantic stop embedding approach for reinforcement-learning-based bus holding control, reducing headway variability, bunching events, and passenger waiting time in simulations.

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#transit

You can now ask Google Maps’ AI to order food for you

The Verge ↗ · 2026-08-06 Cached

Google Maps' Ask Maps AI is expanding with agentic capabilities like conversational food ordering, hotel and event discovery, and Gmail-connected Personal Intelligence, rolling out in the US and other countries.

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#transit

Google Maps adds agentic features, including food ordering and hotel bookings

TechCrunch AI ↗ · 2026-08-06 Cached

Google Maps' Ask Maps feature gains agentic capabilities for ordering food, booking hotels, and finding event tickets, plus Personal Intelligence integration with Gmail and Calendar for personalized recommendations.

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#transit

TransitLM: A Large-Scale Dataset and Benchmark for Map-Free Transit Route Generation

arXiv cs.CL ↗ · 2026-05-22 Cached

This paper introduces TransitLM, a large-scale dataset of over 13 million transit route planning records from Chinese cities, enabling map-free route generation via LLMs trained directly on planning data.

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