1) The document discusses the requirements and models needed for autonomous vehicles, including software, hardware, AI models, machine learning categories, and infrastructural needs.
2) It then focuses on the specific needs and considerations for adopting autonomous vehicles on the M1 Motorway in Mauritius, such as lane designations, energy requirements, geospatial data, cultural attitudes, and policy/regulatory frameworks.
3) In conclusion, the technology for autonomous vehicles is ready for commercial use pending clear regulatory standards from governments to address challenges and speed adoption.
3. Introduction
Many policymakers and practitioners are concerned about how autonomous
(also known as self-driving or robotic) vehicles (AVs) will affect future travel
and, as a result, the need for roads, parking lots, and public transportation, as
well as what public policies can be implemented to mitigate the problems and
maximize the benefits of these new technologies.
An autonomous vehicle also known as an autonomous vehicle, driverless car,
or robotic car, is a vehicle that is capable of sensing its environment and
moving safely with little or no human input.
5. Requirements to operate Autonomous vehicles
● SOFTWARES
Navigation Map
High Definition Map
Localization software
Software for perception
Software for prediction
● HARDWARES
Sensors
Cameras
6. AI Models
An AI model is an application, program or algorithm that uses a
set of specific data that allows it to recognize patterns. These
patterns allow the model to reach conclusions or make
predictions when enough information is provided.
Different AI Models:
● Linear regression
● Deep neural networks
● Logistic Regression
● Decision trees
7. Machine Learning
Machine learning is the study of computer algorithms that can improve
automatically through experience and by the use of data. It is seen as a part of
artificial intelligence.
Categories of ML:
● Supervised learning
● Unsupervised learning
● Semi-supervised learning
● Reinforcement learning
9. Infrastructural requirements
For AV to run smoothly, it requires excellent roads, proper regulations and standards for the
constructions and renovation of roads. The current infrastructure will have to go through a drastic
change in terms of road telematics, lanes, signage, curbs and sidewalk.
Requirements:
● Roadside sensors
● Machine-readable signs
● New pavement, paint,Line marking
● Advanced vehicle to infrastructure (V2I) communications
● Curb modifications
● Changing Paradigms of Liability and Safety.
● Making Logistics Greener
10. Local Specificities for AV adoption
● The M1 Road Network
● Energy requirements
● Geospatial Ecosystems
● Culture and Attitude
● Training of Local workforce and Drivers
● Policy & Regulations
● Road Traffic Act
● Industry partnerships
● Standards, privacy and security
11. The M1 Road Network
● Lane Designation
○ Overcome immediate challenges
○ Equipping with proper
infrastructure
○ Quick win
● Motorway as a testbed
○ “Laboratory with real-life conditions”
12. Energy Requirements
● Increase in energy consumption
● What will be the impact on demand and supply of energy
● Develop clean energy technologies
● Energy sustainability
14. Culture and Attitude
● AVs cannot predict the intent of
road users
● Recklessness and Incivility
● Need for change in attitude and
culture
● Awareness campaigns, re-training
of drivers
15. Policy and Regulations
● Road Traffic Act
○ Autonomous Driving Act to enable drivers to hand over control of their
automobiles
○ Definition of Motor Vehicles with Autonomous Driving Capabilities
○ Compliance with traffic regulations
● Open Data Policy
○ Policy to provide datasets that can be shared and used openly (already in place)
○ Continuous effort to ensure availability of high quality datasets
○ Greater collaboration between Academia, Industry associations, private sectors
and government
16. Policy and Regulations
● Data Privacy and Security
● Vehicle tracking and sharing of data
● Driver Privacy Act
17. Type of data and data models required
for development
● Labeling Types in Auto-Driving
● Image segmentation
● High Accuracy Needed for High-
Performing Vision Systems
18. ● A2D2 Dataset for Autonomous Driving
● ApolloScape Open Dataset for Autonomous Driving
● Argoverse Dataset
● Google-Landmarks Dataset
Existing Datasets
19. Conclusion
To conclude, the technology that underpins semi- and fully autonomous vehicles
has advanced to the point where it is ready for commercial implementation. In
navigation, accident avoidance, and street mapping, major automotive makers and
software developers have made significant advances.
Governments can speed up or impede the development of self-driving vehicles in
Mauritius by regulating them in a certain way. In all countries considering
autonomous vehicles, addressing pertinent challenges and ensuring that regulatory
standards are clear should be top priority.