Introduction

The 1st ACM SIGSPATIAL International Workshop on Ride-hailing Algorithms, Applications, and Systems (RAAS 2019) will be held in conjunction with the ACM SIGSPATIAL 2019 Conference in Chicago, IL.

Ride hailing, which uses app-based ride services, didn’t exist 10 years ago, but is now growing at an unprecedented speed. Arguably, data-enabled ride-hailing services are leading to a technological and transportation revolution. This has attracted a surge of interest from a wide variety of research communities.

Thus, we propose a half-day workshop at ACM SIGSPATIAL 2019 for the professionals, researchers, and practitioners who are interested in algorithms, applications, and systems in regarding to the ride-hailing and ride-sharing industries and services.


Format:

Half-day workshop with invited speakers and several contributed talks. 

Call for Papers/Proposals

The RAAS 2019 workshop welcomes papers that address challenging research issues in the ride-hailing industry. We also encourage proposals based on preliminary research using DiDi GAIA Open Dataset. Register and apply for real-life data generated on DiDi platform (https://outreach.didichuxing.com/research/opendata/en/). 

The workshop will offer two Best Paper/Proposal awards. Each winner will be awarded a certificate with signatures of the workshop co-chairs. Further discussions on research collaboration may follow after the workshop.


Topics of interest include the following areas, but are not limited to:

  • Estimated Time of Arrival (ETA)
  • Route Planning in Ride-hailing and Ride-sharing
  • Traffic Forecasting for Ride-hailing and Ride-sharing
  • Destination Suggestion and Prediction
  • POI Discovery, Classification, Retrieval, Filtering and Recommendation
  • Spatial Crowdsourcing for Ride-hailing and Ride-sharing
  • Location Privacy in Ride-hailing and Ride-sharing
  • Trajectory Mining for Ride-hailing Safety
  • Detection of Road Network Anomaly
  • Ride-hailing Safety Modeling and Intervention
  • Demand and Supply Prediction
  • Order Dispatch and Resource Allocation
  • Ride Sharing and Bike Sharing
  • Dynamic Pricing Tools for Demand and Supply Balancing
  • Driver/Passenger Behavior Modeling and Analysis
  • Econometric Methods Using Big Data and Machine Learning for Two-sided Marketplace

Workshop Chairs

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Tiger Qie

Vice President of Didi Chuxing

CTO of Ride-hailing Business Group

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Cyrus Shahabi

Professor, University of Southern California

Chair of ACM SIGSPATIAL

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Xiaofeng Meng

Professor, Renmin University of China

Chair of ACM SIGSPATIAL China Chapter

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Hua Chai

Distinguished Engineer, Didi Chuxing

General Manager of DiDi Maps

For questions about the workshop and submissions, please contact Mandy Ma, DiDi Research Outreach Manager via email (mandyma.edu@didiglobal.com).

Submission Instructions

Submitted papers/proposals must be written in English, in PDF format, should conform to the standard ACM Template, and not exceed 10 pages (for short technical or vision paper no longer than 4 pages). Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this workshop.   

At least one of the authors of each paper accepted for presentation in RAAS 2019 must register for the workshop. All papers presented at the workshop will be included in the ACM Digital Library. All papers are to be submitted via EasyChair https://easychair.org/conferences/?conf=raas2019.


Important Dates:

Paper submission due: September 15, 2019 11:59PM (PDT)

Notification to the authors: September 30, 2019 11:59PM (PDT)

Camera ready papers due: October 4, 2019 11:59PM (PDT)

RAAS Workshop: November 5, 2019

ACM SIGSPATIAL Conference: November 5 – 8, 2019

Organizer

About DiDi:

Didi Chuxing (“DiDi”) is the world’s leading mobile transportation platform. The company offers a full range of app-based transportation options for 550 million users, including Taxi, Express, Premier, Luxe, Bus, Designated Driving, Enterprise Solutions, Bike Sharing, E-bike Sharing, Car Rental and Sharing and food delivery. Tens of millions of drivers who find flexible work opportunities on the DiDi platform provide 10 billion passenger trips a year.

Website: https://www.didiglobal.com/


About DiDi GAIA Open Dataset:

With DiDi's advantages in big data and technology, the GAIA Open Dataset provides academic community with real-life application use cases, anonymized data and computing resources, and seeks collaboration with the academic community. The Open Dataset aims to advance fundamental and prospective studies in transportation research. It promotes the application of scientific achievements by strengthening ties between industry, university and research. This effort will drive scientific development in intelligent transportation systems and contribute to societal development. So far, we have opened Trajectory Dataset,POI Retrieval Dataset, and Large-scale Driving Video Dataset.

Website: https://outreach.didichuxing.com/research/opendata/en/


About DiDi Research Outreach:

DiDi is developing advanced technologies to build a safe, efficient, people and eco-friendly transportation ecosystem. But our work does not end with that. We also collaborate with universities, colleges and research institutions all over the world to explore cutting-edge technologies along with the commitment to serve as the most trustworthy partner in the academic field. Our unique programs, such as ATHENA Global Talent Program, enable us to provide world-class talents with a comprehensive platform to explore technology and to improve themselves.

Website: https://outreach.didichuxing.com/

WeChat: DiDi Research Outreach