Work2017

A Taxi Order Dispatch Model based On Combinatorial Optimization

Lingyu Zhang · Tao Hu · Min Yue · Guobin Wu · Pengcheng Feng · Pinghua Gong +1 more

244 citations0/0 files storedACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

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Transportation and Mobility Innovations Transportation Planning and Optimization Traffic Prediction and Management Techniques

Abstract

Taxi-booking apps have been very popular all over the world as they provide convenience such as fast response time to the users. The key component of a taxi-booking app is the dispatch system which aims to provide optimal matches between drivers and riders. Traditional dispatch systems sequentially dispatch taxis to riders and aim to maximize the driver acceptance rate for each individual order. However, the traditional systems may lead to a low global success rate, which degrades the rider experience when using the app. In this paper, we propose a novel system that attempts to optimally dispatch taxis to serve multiple bookings. The proposed system aims to maximize the global success rate, thus it optimizes the overall travel efficiency, leading to enhanced user experience. To further enhance users' experience, we also propose a method to predict destinations of a user once the taxi-booking APP is started. The proposed method employs the Bayesian framework to model the distribution of a user's destination based on his/her travel histories.

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References

2013Predicting Taxi–Passenger Demand Using Streaming Data 2011Where to find my next passenger 2011Hunting or waiting? Discovering passenger-finding strategies from a large-scale real-world taxi dataset 2006Learning to Predict Driver Route and Destination Intent 2004Taxi Dispatch System Based on Current Demands and Real-Time Traffic Conditions 2015Artificial Neural Networks Applied to Taxi Destination Prediction 2009Hierarchical route planning based on taxi GPS-trajectories

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2020Pricing and equilibrium in on-demand ride-pooling markets 2019A Deep Value-network Based Approach for Multi-Driver Order Dispatching 2018Hexagon-Based Convolutional Neural Network for Supply-Demand Forecasting of Ride-Sourcing Services

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