Smart Matching Engine for Ride-Sharing: Technical Implementation and Algorithms

The Smart Matching Engine for Haolo’s ride‑sharing service ingests driver and passenger orders via Kafka‑Flink pipelines into Elasticsearch, then applies multi‑stage matching—nearby search, itinerary‑based filtering using ETA, angle, distance, route‑similarity and shared‑mileage calculations—and finally ranks results with evolving pre‑sorting and algorithmic models, including PMML and deep‑learning, to optimize driver‑passenger pairing.

ElasticsearchFlinkKafka

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Smart Matching Engine for Ride-Sharing: Technical Implementation and Algorithms

DataFunSummit

Sep 12, 2021 · Artificial Intelligence

Algorithmic Practices in Haola Ride-Sharing: Platform Infrastructure, Matching Recommendation Engine, Transaction Governance, and Intelligent Marketing

This article details Haola's end‑to‑end algorithmic ecosystem for its ride‑sharing service, covering the machine‑learning platform built on Hadoop/YARN, the architecture and evolution of the matching recommendation engine, transaction‑ecosystem governance models, and intelligent marketing strategies including uplift modeling and optimization.

AIRecommendation EngineRide-sharing

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Algorithmic Practices in Haola Ride-Sharing: Platform Infrastructure, Matching Recommendation Engine, Transaction Governance, and Intelligent Marketing

HelloTech

Sep 10, 2021 · Artificial Intelligence

Algorithmic Practices in Haolo Carpool Service: Platform, Matching Engine, Transaction Governance, and Intelligent Marketing

The article details Haolo's end-to-end AI platform—built on Hadoop/Yarn with Spark ML, XGBoost and TensorFlow—and explains how its matching recommendation engine, transaction-ecosystem governance models, and intelligent uplift-based marketing system jointly boost carpool efficiency, safety, user retention, and ROI.

AI AlgorithmsRide-sharingTransaction Governance

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Algorithmic Practices in Haolo Carpool Service: Platform, Matching Engine, Transaction Governance, and Intelligent Marketing

DataFunTalk

Jun 26, 2021 · Artificial Intelligence

Algorithmic Practices in Haola Ride‑Sharing: Platform Infrastructure, Matching Recommendation Engine, Transaction Governance, and Intelligent Marketing

This article presents a comprehensive overview of Haola's ride‑sharing algorithm ecosystem, covering the machine‑learning platform foundation, the architecture and evolution of the matching recommendation engine, the transaction‑ecosystem governance models, and the intelligent marketing uplift framework, highlighting technical challenges, solutions, and performance gains.

AI AlgorithmsMarketing OptimizationRide-sharing

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Didi Tech

Jul 17, 2018 · Industry Insights

How Didi’s AI‑Powered Map Engine Redefined Ride‑Sharing Navigation

At the ArchSummit conference, Didi’s senior engineer Zhu Zhiqing detailed how massive real‑time travel data and AI techniques are reshaping the company’s map engine architecture, boosting path‑planning accuracy, ETA precision, data‑update speed, and overall ride‑sharing efficiency.

AIData UpdateMap Engine

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How Didi’s AI‑Powered Map Engine Redefined Ride‑Sharing Navigation

Didi Tech

Jul 17, 2018 · Artificial Intelligence

Didi Showcases AI‑Driven Intelligent Transportation Research at ACM SIGIR 2018

At ACM SIGIR 2018, Didi presented AI‑driven intelligent‑transportation research—including a ride‑sharing preference prediction paper, keynote insights on smart dispatch, maps and traffic, collaborations with over twenty cities and numerous universities, open data initiatives, and plans for new thematic research programs.

Big DataIndustry-Academia CollaborationIntelligent Transportation

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Didi Showcases AI‑Driven Intelligent Transportation Research at ACM SIGIR 2018

21CTO

Mar 8, 2016 · Backend Development

How Uber Engineers Tailor Core Infrastructure for China’s Ride‑Sharing Market

Uber’s CTO Thuan Pham explains how the company builds a specialized engineering team and core infrastructure in China, uses data‑center support, dynamic pricing, anti‑fraud machine learning, and safety features to adapt its global platform to local market needs.

Ride-sharingUberbackend infrastructure

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How Uber Engineers Tailor Core Infrastructure for China’s Ride‑Sharing Market