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原文地址：https://github.com/zzsza/Awesome-Mobility-Machine-Learning-Contents/blob/master/README.md

交通运输相关机器学习/深度学习相关资源列表

HitCount

Machine Learning / Deep Learning Contents in Mobility Industry(Transportation)
- 我收集它是为了学习
- 我选择了至少10次引文或最新论文的论文
Made by Seongyun Byeon working at Socar(Korea Car Sharing Company)
Last modified date : 19.05.06

Awesome Public Datasets(Transportation), [Github]
Google Dataset Search, [Car Sharing], [Ride Hailing]
Highway Tollgates Traffic Flow Prediction(KDD Cup 2017), [URL]
Uber Movement(Uber), [URL]
NYC Taxi DATA(NYC), [URL]
Next Generation Simulation(Federal Highway Administration), [URL]
GAIA Open Dataset(DiDi Chuxing) : Trajectory Data, [URL]
BSS Dataset(Consumer Data Research Centre), [URL]

地图匹配

Some map matching algorithms for personal navigation assistants(2000), Christopher E. White. [pdf]
On map-matching vehicle tracking data(2005), Sotiris Brakatsoula et al. [pdf]
Map Matching with Travel Time Constraints(2006), John Krumm et al. [pdf]
Hidden Markov map matching through noise and sparseness(2009), Paul Newson et al. [pdf]
Map-matching for low-sampling-rate GPS trajectories(2009), Yin Lou et al. [pdf]
Online map-matching based on Hidden Markov model for real-time traffic sensing applications(2012), C.Y. Goh, J. Dauwels et al. [pdf]
Large-Scale Joint Map Matching of GPS Traces(2013), Yang Li et al. [pdf]
Map Matching with Inverse Reinforcement Learning(2013), T. Osogami et al. [pdf]

路线规划

Contraction hierarchies: Faster and simpler hierarchical routing in road networks(2008), R. Geisberger et al. [pdf]
Customizable Route Planning in Road Networks(2013), Daniel Delling et al. [pdf]
Route Planning in Transportation Networks(2015), Hannah Bast et al. [pdf]
Modeling Trajectories with Recurrent Neural Networks(2017), H Wu et al. [pdf]
Imagination-Augmented Agents for Deep Reinforcement Learning(2017), T. Weber et al. [pdf]
Learning to navigate in cities without a map(2018), Piotr Mirowski et al. [pdf]
A Unified Approach to Route Planning for Shared Mobility(2018), Yongxin Tong et al. [pdf]

ETA

Estimation Time Arrival
Traffic Estimation And Prediction Based On Real Time Floating Car Data(2008), Corrado de Fabritiis et al. [pdf]
Travel time estimation for urban road networks using low frequency probe vehicle data(2013), Erik Jenelius et al. [pdf]
Travel time estimation of a path using sparse trajectories(2014), Yilun Wang et al. [pdf]
Learning to estimate the travel time(2018), Zheng Wang et al(DiDi AI Labs). [pdf]
Multi-task Representation Learning for Travel Time Estimation(2018), Yaguang Li et al(DiDi AI Labs). [pdf]
When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks(2018), Dong Wang1 et al. [pdf]

流量估算和预测

Traffic flow theory and control(1968), Donald R Drew, [pdf]
Dynamic Prediction of Traffic Volume Through Kalman Filtering Theory(1984), Okutani et al. [pdf]
Predicting time series with support vector machines(1991), Muller et al. [pdf]
Modeling and forecasting vehicular traffic flow as a seasonal ARIMA process: Theoretical basis and empirical results(2003), Billy M et al. [pdf]
Travel-time prediction with support vector regression(2004), Wu et al. [pdf]
Gaussian processes for short-term traffic volume forecasting(2010), Xie et al. [pdf]
Road Traffic Prediction with Spatio-Temporal Correlations(2011), Wanli Min et al. [pdf]
Utilizing real-world transportation data for accurate traffic prediction(2012), Pan et al. [pdf]
A k-nearest neighbor locally weighted regression method for short-term traffic flow forecasting(2012), Li S et al. [pdf]
Traffic Flow Prediction With Big Data: A Deep Learning Approach(2015), Lv Y et al. [pdf]
SMiler: A Semi-Lazy Time Series Prediction System for sensors(2015), Zhou et al. [pdf]
Latent Space Model for Road Networks to Predict Time-Varying Traffic(2016), Deng, D et al.[pdf]
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting(2017), Li Y et al.
[paer]
Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction(2017), Ma X et al. [pdf]
Diffusion Convolutional Recurrent Neural Network: Data-driven Traffic Forecasting(2018), Li Y et al. [pdf]
Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested LSTM Models(2018), Ma X et al. [pdf]

调度

Design and Modeling of Real-time Shared-Taxi Dispatch Algorithms(2013), J Jun et al. [pdf]
Large-Scale Order Dispatch in On-Demand Ride-Sharing Platforms: A Learning and Planning Approach(2018), Zhe Xu et al(DiDi AI Labs). [pdf]
Order Dispatch in Price-aware Ridesharing(2018), Libin Zheng et al. [pdf]
Efficient Ridesharing Order Dispatching with
Mean Field Multi-Agent Reinforcement Learning(2019), Minne Li et al(DiDi Research). [pdf]
Dynamic Pricing and Matching in Ride-Hailing
Platforms(2018), Nikita Korolko et al(Uber Technologies). [pdf]
DeepPool: Distributed Model-free Algorithm for
Ride-sharing using Deep Reinforcement Learning(2019), Abubakr Allabbsi et al. [pdf]

动态定价

Vehicle Sharing System Pricing Optimization(2013), A Waserhole. [pdf]
Pricing in Ride-share Platforms: A Queueing-Theoretic Approach(2015), Carlos Riquelme et al. [pdf]
Dynamic Pricing in Ridesharing Platforms(2015), [pdf], [video]
Dynamic Pricing and Matching in Ride-Hailing
Platforms(2018), Nikita Korolko et al(Uber Technologies). [pdf]
Dynamic Pricing in Shared Mobility on Demand
Service(2018), Han Qiu et al. [pdf]

供需预测

The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms(2017), Tong et al. [pdf]
Supply-demand Forecasting For a Ride-Hailing System(2017), Wang, Runyi. [pdf]
Predicting Short-Term Uber Demand Using Spatio-Temporal Modeling: A New York City Case Study(2017), Sabiheh Sadat et al. [pdf]
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction(2016), Zhang et al. [pdf]
Short-Term Forecasting of Passenger Demand under
On-Demand Ride Services: A Spatio-Temporal Deep
Learning Approach(2017), Jintao Ke et al. [pdf]
Predicting citywide crowd flows using deep spatio-temporal residual networks(2017), Zhang et al. [pdf]
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction(2018), Yao et al. [pdf]
Forecasting Taxi Demands with Fully Convolutional
Networks and Temporal Guided Embedding(2018), Doyup Lee et al(Kakao Brain). [pdf], [blog #1], [blog #2]

电动汽车

A self-learning TLBO based dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads(2014), Zhile Yang et al. [pdf]
A Comprehensive Study of Key Electric Vehicle (EV)
Components, Technologies, Challenges, Impacts, and
Future Direction of Development(2017), F Un-Noor et al. [pdf]
Planning of Electric Vehicle Charging
Infrastructure for Urban Areas with Tight
Land Supply(2018), C Guo et al. [pdf]
Optimal Allocation Model for EV Charging
Stations Coordinating Investor and User Benefits(2018), Youbo Lie et al. [pdf]

平台

Flexible Dynamic Task Assignment in Real Time Spatial Data(2017), Yongxin Tong et al. [pdf]
Ride-Hailing Networks with Strategic Drivers: The Impact of
Platform Control Capabilities on Performance(2018), Philipp et al. [pdf]

调度优化

Constraint Programming for Scheduling(2004), John et al. [pdf]
Scheduling problem using genetic algorithm, simulated annealing and the effects of parameter values on GA performance(2006), A Sadegheih. [pdf]
Scheduling part-time personnel with availability restrictions and preferences to maximize employee satisfaction(2008), S Mohan et al. [pdf]
Genetic Algorithms For Shop Scheduling Problems : A Survey(2011), Frank Werner. [pdf]
Scheduling part-time and mixed-skilled workers to maximize employee satisfaction(2012), M Akbari et al. [pdf]
Optimization of Scheduling and Dispatching Cars
on Demand(2014), Vu Tran. [pdf]
Vehicle Relocation Scheduling Method for Car
Sharing Service System based on Markov Chain
and Genetic Algorithm (2018), Tingying Song et al. [pdf]
Uber Driver Schedule Optimization(2018), Ivan Zhou. [blog]

自动驾驶汽车

Awesome Autonomous Vehicles, [Github]
Deep Autonomous Driving Papers, [Github]

共享单车

Bicycle-sharing system, [Wikipedia]
Bike-sharing: History, Impacts, Models of Provision, and Future(2009), Paul DeMaio. [pdf]
Bicycle-Sharing Schemes: Enhancing Sustainable Mobility in Urban Areas(2011), P Midgley et al. [pdf]
Static repositioning in a bike-sharing system: models and solution approaches(2013), Tal Raviv et al. [pdf]
Bicycle sharing systems demand(2014), I Frade et al. [pdf]
Incentivizing Users for Balancing Bike Sharing Systems(2015), A Singla et al. [pdf]
Mobility Modeling and Prediction in Bike-Sharing Systems(2016), Z Yang et al. [pdf]

License

Distributed under the MIT License. See LICENSE for more information.

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交通运输相关机器学习/深度学习相关资源列表

目录

交通运输公司名单

技术博客

数据集

地图匹配

路线规划

ETA

流量估算和预测

调度

动态定价

供需预测

电动汽车

平台

调度优化

自动驾驶汽车

共享单车

License

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