Autonomous Vehicles: Drivers of Change
Thomas J. Bamonte
Mr. Bamonte is general counsel at the North Texas Tollway Authority, Plano, Texas. This paper discusses how Highway authorities need to start preparing now for the inevitability of driverless vehicles.
Future Ride
Peter Wayner
The future of transportation is coming faster than ever. Cars that drive themselves are already on the road giving rides to people all day long. When they become widespread, every part of society will change as everyone can enjoy the pleasure of their own chauffeur.
The Evolution of Connected Vehicle Technology: From Smart Drivers to Smart Cars to… Self-Driving Cars
ITE Journal
Vehicle-to-vehicle and vehicle-to-infrastructure technology promise to change the way we move on our roads. Siva R. K. Narla, senior director, Transportation Technology, Institute for Transportation Engineers, Washington, DC, USA, writes about how the research for these technologies is shaping the travel scene in the United States and Europe.
Disruptive technologies: Advances that will transform life, business, and the global economy
McKinsey Global Institute
This report identifies 12 technologies, including driverless cars, that could drive truly massive economic transformations and disruptions in the coming years.
Preliminary Statement of Policy Concerning Automated Vehicles
NHTSA
The NHTSA policy concerning vehicle automation, including its plans for research on related safety issues and recommendations for states related to the testing, licensing, and regulation of autonomous or self-driving vehicles.
Debate: Driverless cars - Are completely self-driving cars feasible in the foreseeable future?
The Economist
An online debate, with external comments, on if driverless cars are coming.
The Road Ahead: The Emerging
ITIF
This paper discusses how policy decisions about IT in the vehicle should be driven, not by narrow interests and concerns, but rather by a broad government mandate to foster innovation in the transportation sector.
Driverless Cars: Trillions Are Up For Grabs
Chunka Mui, Paul B Carroll
In January 2013, Chunka Mui started a series of columns at Forbes on the driverless car, drawn from research that he and Paul Carroll were conducting for their coming book, “The New Killer Apps: How Large Companies Can Out-Innovate Start-Ups.” That seven-part series garnered almost 500,000 views and generated hundreds of informative comments from all over the world. Given the immense interest, Mui and Carroll have turned that series into this ebook. They have integrated all the columns, incorporated many of the comments and added their latest research.
Transforming Personal Mobility
The Earth Institute Columbia University
A series of case studies that look at the economic impact of autonomous vehicles and car sharing businesses.
Automated Vehicles are Probably Legal in the United States
Stanford Center for Internet and Society
This paper provides the most comprehensive discussion to date of whether so-called automated, autonomous, self-driving, or driverless vehicles can be lawfully sold and used on public roads in the United States. The short answer is that the computer direction of a motor vehicle’s steering, braking, and accelerating without real-time human input is probably legal. The long answer, contained in the paper, provides a foundation for tailoring regulations and understanding liability issues related to these vehicles.
International Survey of Best Practices in Connected Vehicle Technologies: 2012 Update
CAR
Michigan is a major U.S. center of connected vehicle technology development and testing, but other states within the country are involved in significant connected vehicle activities as are other countries throughout the world. This report investigates connected vehicle and connected vehicle-related activities underway outside Michigan, especially international examples of connected vehicle work, for the purpose of understanding and describing overall best practices in connected vehicles.
A Cloud-Assisted Design for Autonomous Driving
MIT
This paper presents Carcel, a cloud based system for Autonomous Driving. Carcel enables the cloud to access to sensor data from autonomous vehicles as well as the roadside infrastructure.
Self-driving cars: The next revolution
KPMG/Center for Automotive Research
This paper provides the most comprehensive discussion to date of whether so-called automated, autonomous, self-driving, or driverless vehicles can be lawfully sold and used on public roads in the United States. The short answer is that the computer direction of a motor vehicle’s steering, braking, and accelerating without real-time human input is probably legal. The long answer, contained in the paper, provides a foundation for tailoring regulations and understanding liability issues related to these vehicles.
The Case for Driverless Cars
AUVSI
This paper takes a look at the current U.S. consumer car market, how it might change with driverless cars, and some emerging issues as technology hurdles are overcome.
Connected Vehicles: An Executive Overview of the Status and Trends
Globis Consulting
An high level introduction to connected vehicles.
The Impact of Carsharing on Household Vehicle Ownership
Access the magazine of UCTC
A detailed study on the impact of car sharing today.
Liability and Regulation of Autonomous
UC Berkley PATH Program
This paper discusses the regulatory climate around driverless transportation.
Traffic
Tom Vanderbilt
Tom Vanderbilt examines the perceptual limits and cognitive underpinnings that make us worse drivers than we think we are. He demonstrates why plans to protect pedestrians from cars often lead to more accidents. He uncovers who is more likely to honk at whom, and why. He explains why traffic jams form, outlines the unintended consequences of our quest for safety, and even identifies the most common mistake drivers make in parking lots.
A Perception-Driven
MIT
This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceive information in preference to potentially inaccurate or incomplete map data.