ITGS Case Study 2019 - The Road to Driverless Cars

Society of Automotive Engineers (SAE) automation scale

The Society of Automotive Engineers (SAE) is mentioned in the case study booklet in reference to their six level scale for describing vehicle automation. This ranges from Level 0 (No automation), through Level 3 (Conditional automation), to Level 5 (Full automation). The SAE's own link is broken at the moment, but you can find out more about the SAE scale here.

Understanding the SAE automation scale may help students organise their understanding of the different driverless car technologies further down this page.

Waymo (Google)

Waymo is the new name of Google's driverless car project. The project's website has some interesting information, including a video showing how Waymo senses the road, complete with a visualisation of the data collected. There is even a project called Early Rider where members of the public can sign up to trial the driverless car in their everyday life!

In February 2018 Waymo also announced that they are planning a self-driving truck programme.

RoboRace

This resource is probably slightly less useful for the Road to Driverless Cars case study. However, the ability to build a self driving vehicle that can negotiate a racetrack while competing against other cars is still pretty impressive. It could also be useful to discuss the difference between designing a car racing around a fixed track and a car that must negotiate city streets.

The RoboRace web page and YouTube channel are resources worth visiting.

Tesla

Tesla is one of the companies explicitly mentioned in the case study booklet (line 16). Tesla's case is an interesting one: they actually claim their current vehicles are fully able to self drive (i.e. level 5 on the SAE scale). However, they say they are unable to activite this technology in their cars due to legal restrictions. This links directly with the legal challenges section of the case study booklet. The Tesla website has lots of useful information, including a video of their car in action (with the requisite visualization of sensor data).

Uber

What Uber Learned from a Year of Self Driving is a short video (produced before the March 2018 fatal accident) those guys into great depth about Uber's self driving car project. The technical aspects are probably more than is required for ITGS (although it doesn't hurt to understand them), but the discussion of social issues (such as the reluctance of people to use autonomous vehicles) is perfect.

Of course, sadly Uber has been in the limelight for the wrong reasons recently, with a pedestrian died in a collision with one of their driverless cars. Uber self-driving cars: everything you need to know goes into detail about the roots of the driverless car project and the accident.

Homer (Voyage)

Concrete information on Voyage's self driving vehicles is hard to come by. Their attempt, named Homer, is a conversion of a regular vehicle into an autonomous taxi. The use of driverless taxis and other public transport could be very relevant for the environmental goals of the World Driverless Vehicle Federation (line 86). The Story of Homer is probably the best source of information on this project.

Army marches forward with self-driving trucks

In 2016 the US Army experimented with self driving trucks in Michigan. The system relied heavily on Vehicle to Infrastructure (VTI) communication to inform the trucks about road conditions (such as lane closures). Replacing trucks with driverless vehicles clearly has potential to cause significant social impacts, including unemployment, making this article a good class discussion starter.

Intel and self driving vehicles

Intel is one of the companies specifically mentioned in the case study booklet (line 16). Although Intel do not build their own driverless vehicles, they do supply to technology used by a large number of them. The Intel website offers insight into their various collaborations, the technology they use, and their vision for the future of automated driving.

GPS technology

How does GPS work? and How GPS works both do exactly what they say on the tin. It is worth noting that generally GPS does not provide sufficient accuracy or reliability for driverless vehicles to rely on for obstacle avoidance. Wide Area Augmentation System (WAAS) is one system designed to improve the accuracy of location systems.

LIDAR technology

LIDAR technology is often used by driverless vehicles to sense the environment around them. The technology works by emitting light pulses and measuring the time it takes for them to be reflected back to the vehicle. LIDAR is also used in remote sensing, which is part of the Environment topic in Strand 2. One of the best ways to understand how autonomous vehicles 'see' the world is to watch a visualization of LIDAR data.

Driverless cars and ethics

Driverless or self-driving vehicles are often promoted as being safer than human drivers. However, there may be situations in which an accident is unavoidable. In these situations, how should a driverless vehicle be programmed to behave? Which course of action should it take if all have negative outcomes? And, of course, who takes responsibility for any damage that is caused?

This is a topic which links to ITGS and TOK. The ethical dilemma of self-driving cars (video) is a good introduction. Why Self-Driving Cars Must Be Programmed to Kill and Ethics of Self-Driving Cars are great articles that examine the topic in more detail.

Uber driverless car accident

In March 2018 an accident occured which was reportedly the first death caused by a driverless vehicle. The Uber self-driving car hit and killed Elaine Herzberg, 49, in Arizona. The human monitor in the car also failed to spot the pedestrian until seconds before the collision. Uber stopped all self driving experiments in the aftermath of the crash.

Velodyne, the company that produces the sensors for the cars, reported that the sensors were working correctly - suggesting a software issue may have been the cause. It was later reported that the car's sensors detected Herzberg, but chose not to swerve as it was uncertain about the nature of the obstacle.

The Trolley Problem

The Trolley problem is not explicitly mentioned in the case study text, but it is included in the list of key terms at the end of the booklet. The trolley problem is a well known situation and clearly links ITGS with TOK. Justice: What's The Right Thing To Do? is an excellent video that investigates the trolley problem in an interactive manner. Don't be put off by the apparently lecture format - the first 15 to 20 minutes are very engaging and relevant.

Markkula (Santa Clara) ethical decision making

It isn't 100% clear why the IB have chosen this particular 'model' of ethical decision making for inclusion in the ITGS case study. However, Santa Clara University do have a very nice interactive Making an Ethical Decision page that guides users through the process. If you'd prefer to just read about it, they have a PDF summary sheet too.

Driverless vehicle accidents

Accidents are perhaps the greatest fear people have in relation to driverless vehicles. When developing IT systems, overcoming psychological issues can be as difficult as solving technical problems. TechRadar has a good series of articles about incidents involving driverless vehicles. The articles cover Uber's early accidents (before the fatality), Google's collision with a truck, a Tesla parking accident, and a fatality involving Tesla's Autopilot system. It should be noted that Tesla's Autopilot is not intended as a Level 5 automation feature.

Most recently a pedestrian in Arizona was killed after being hit by an Uber driverless vehicle that failed to avoid her as she crossed the road. Several theories about the cause of the crash have been put forward, but the most recent thinking is that the Uber vehicle detected the pedestrian but did not take evasive action because the emergency braking had been disabled. This raises several issues directly linked to the 2019 ITGS case study, including human complacency (the person monitoring the vehicle's driving was apparently distracted), and legal responsibilities and ramifications in the event of an accident.

Voyager Communities

The Communities section of the Voyage website has great examples of driverless vehicles being implemented in real world conditions. The two urban communities in San Jose and Florida are test beds where driverless vehicles are used over hundreds of kilometres of real roads. The web page features details of various Voyager users and how the driverless car systems benefit them.

Self-driving cars attacked by angry San Francisco residents

In an interesting development, in March 2018 the Independent reported on an increase in attacks on self driving vehicles in San Francisco. The article doesn't fully explain why people were angry with self driving cars, although this could be a good classroom discussion point.

Trust and autonomous driving

This excellent article and video from Intel offers great insight into a key problem of autonomous vehicles: getting humans to put their trust in machines. Although most accidents are caused by human error, getting putting to relinquish control of a vehicle is still a key challenge. This article examines some of the possible solutions to this psychological barrier.

Vehicle to Infrastructure (VTI) communication

Vehicle to Infrastructure communication (VTI) is one of the big issues in the case study. It is the process of vehicles (whether autonomous or not) communicating with infrastructure such as traffic lights and road signs to discover information about the environment. Vehicles can also relay requests to the infrastructure - for example, an emergency vehicle could request a smart traffic light to switch to green to facilitate its passage.

VTI is a potential economic concern because of the need to update large amounts of existing infrastucture. However, VTI can also have environmental and economic benefits by reducing idling at unnecessary traffic stops, and by encouraging vehicles to travel at the most fuel efficient speeds. This saves fuel and money, and reduces harmful vehicle emissions.

Smart Intersection Controller is a great example of this, and there are many other VTI videos on the ITGS YouTube Channel.

Vehicle to Vehicle Communication (VTV)

As the name suggests, Vehicle to Vehicle (VTV) communication allows vehicles (whether they are automated or not) they share information about the environment. This could include a vehicle warning following cars about a hazard (e.g. ice) ahead, vehicles working together to drive at the same speed to ensure smooth traffic flow, or vehicles communicating to avoid an imminent collision.

Honda V2X Communications and automated driving is a particularly good example video that shows how VTV can help protect vulnerable road users such as pedestrians, cyclists, and motorcyclists. There are also numerous other VTV videos on the ITGS YouTube Channel.

Driverless vehicles and the law

Driverless vehicles is a good example of a situation where technology creates situations existing laws were not designed to deal with (we come across many of these in ITGS).

Globally

Which are the top autonomous vehicle ready countries? is a great top 20 table of countries across the world. Each is given a score based on factors including technology, infrastructure (for technology such as smart roads and Vehicle to Infrastructure communication), and legislative framework.

Global Survey of Autonomous Vehicle Regulations is a good summary of laws relating to driverless vehicles worldwide. In many cases countries have no specific laws relating to such vehicles, or they are implicitly banned by existing legislation. However, several countries have made changes in this area. Driverless Car Rules in Flux examines the situation in Japan, Singapore, and Germany.

United States

The NCSL has a good overview of the law regarding driverless vehicles in different US states. It is worth checking this site often as the legal situation changes quite frequently.

In February 2018 California moved to allow driverless cars to operate on its roads without a human backup driver being present. They would still require a human to remotely monitor the car however.

Europe

Autonomous Car Law in Europe summarises the legal situation, examining European Union laws and any changes made in individual countries.

United Kingdom

In the UK, a three year legal review will occur before driverless cars will be allowed on public roads. Driverless cars: the legal issues goes into more detail about some of the potential stumbling blocks for law makers.

China

In early 2018 China developed new regulations to catch up with the latest developments in self driving technology. Previously Beijing had allowed testing of autonomous vehicles within the region provided they met certain requirements, including the use of a human backup driver. The tests were also limited to designated roads at designated times.

Driverless vehicles and legal responsibility

Driverless cars and the law is a podcast from the BBC that deals with legal aspects of self driving cars. The particular focus is on legal responsibility in the event of an accident, and issues such as insurance and compensation in the event of an accident.