Workshop on Ride-hailing Algorithms, Applications, and Systems

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Chicago, Illinois

November 5, 2019

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.

 Introduction 

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 related to the ride-hailing industry. We also encourage proposals based on preliminary research using DiDi GAIA Open Dataset. Register and apply for diverse kinds of real-life data generated on DiDi ride-hailing 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

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

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 and proposals are to be submitted via EasyChair https://easychair.org/conferences/?conf=raas2019.

Program Committee

Tiger Qie

Vice President of Didi Chuxing, CTO of DiDi Ride-hailing Business Group, China

Cyrus Shahabi

Professor,

University of Southern California, USA

Chair of ACM SIGSPATIAL

Xiaofeng Meng

Professor, 

Renmin University of China, China

Chair of ACM SIGSPATIAL China Chapter

Hua Chai

Distinguished Engineer, Didi Chuxing,

General Manager of DiDi Maps, China

For questions about the workshop and submissions, please contact Mandy Ma, DiDi Research Outreach Manager via email ([e-mail]).

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/

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