DESCRIPTION
Autonomous Car research and development is booming today, with many companies developing such cars, e.g., TESLA, BMW, MERCEDES, FIAT, TOYOTA, to name a few. Very many application areas emerge from companies like UBER and LYFT, that tend to change the city landscape in the near future, e.g.,
- Car rentals (instead of car purchases)
- Autonomous taxis.
- Autonomous vans for goods transportation.
This CVML Web Module focuses on Autonomous Car methods and technologies, its applications in the above-mentioned diverse domains towards new challenges ahead. An Introduction to Autonomous Car Vision paves the way to Autonomous Car perception, based on Autonomous Car Sensors. Particular attention is paid to Pedestrian Detection and Street Environment Perception, as they enable car safety. Two lectures address semantic road mapping: 3D Road Surface Reconstruction and Road Condition Assessment. Road Traffic Monitoring allows proper Autonomous Car path (re)planning.
Autonomous car architecture.
LECTURE LIST
- Introduction to Autonomous Car Vision
- Autonomous Car Sensors
- Autonomous Car Modeling and Control
- Pedestrian Detection
- 3D Road Surface Reconstruction
- Road Condition Assessment
- Road Traffic Monitoring
- Privacy Protection, Ethics and Regulations for Autonomous Cars
CVML WEB LECTURE MODULE SCHEDULE
This module has been designed to be mastered within 1 month (or less), if you have proper background (at least early undergraduate student in an EE, ECE, CS, CSE or any Engineering or Exact Sciences Department).
We propose that you follow the above mentioned Lecture order. You may want to skip few Lectures that might not be of immediate interest to you for later study.
On average you can study 4 lectures per week. The related effort is as follows:
Lecture pdf study and filling the related understanding questionnaire: 1-2 hours per lecture (on average, depending on your background).