Transportation Systems

Transportation Systems Summary

1. The ride-hailing industry highlights the growth of a new “Transportation System” TS a. For ride-hailing TS controls rides matching drivers and customers; it predicts how to position cars and how to avoid traffic slowdowns b. However, TS is much bigger outside ride-hailing as we move into the “connected vehicle” era c. TS will probably find autonomous vehicles easier to deal with than human drivers
2. Cloud Fog and Edge components
3. Autonomous AI was centered on generalized image processing
4. TS also needs AI (and DL) but this is for routing and geospatial time-series; different technologies from those for image processing

Slides

Transportation Systems A: Introduction

1. “Smart” Insurance
2. Fundamentals of Ride-Hailing

Transportation Systems B: Components of a Ride-Hailing System

1. Transportation Brain and Services
2. Maps, Routing,
3. Traffic forecasting with deep learning

Transportation Systems C: Different AI Approaches in Ride-Hailing

1. View as a Time Series: LSTM and ARIMA
2. View as an image in a 2D earth surface - Convolutional networks
3. Use of Graph Neural Nets
4. Use of Convolutional Recurrent Neural Nets
5. Spatio-temporal modeling
6. Comparison of data with predictions
7. Reinforcement Learning
8. Formulation of General Geospatial Time-Series Problem