Autonomous Vehicles: Technology, Safety, Policy, and Market Motivation20 Feb

Dr. Jeffrey H. Everson*

Reading, MA 01867

According to a presentation (December 15, 2016) by the Automated Vehicles Working  Group (AVWG) of the Massachusetts Department of Transportation (MASS DOT), there is a requirement for technical experts to support this group:

  • Provide input guidance to MASSDOT for safe testing of AV technologies
  • Ensure that AVs, which have completed testing, can be operated safely to advance the welfare of Massachusetts residents
  • Follow developments in AV technology, Federal policy and laws/policies in other states
  • Facilitate the widespread deployment of Automated Vehicles (AV) in Massachusetts.

Several other states have similar interests in Autonomous Vehicles.

I can support these requirements based on my technical background and program management experience. The latter stems from programs awarded to me by the US Department of Transportation (US DOT).

Crash Warning Systems: I have extensive contractual experience as Principal Investigator (PI) with vehicle crash warning systems for Run-Off-Road (ROR),and Intersection collisions for automobiles, as well as crash warning systems for inner city transit buses. This work was a precursor development leading to driverless vehicles. Contracts for these programs were awarded by the National Highway Traffic Safety Administration (NHTSA) and the Federal Transit Administration (FTA). The first two programs were performed at Battelle Memorial Institute as a subcontractor to Carnegie Mellon University, while the third was undertaken at Foster-Miller, Inc. as a subcontractor to Calspan.

On Board Vehicle Sensors: Sensors for these vehicles were selected from visual/infrared, acoustic, radar, and Light Detection and Ranging (LIDAR) technologies. Data from these sensors served as input to onboard computers equipped with algorithms designed to issue warnings for crash avoidance. Warning modalities included visual, audio and haptic (i.e., vibrating driver seat or steering wheel).

Computer Simulations: The ROR project involved a computer simulation to test various driver warning algorithms. The simulation included human factor inputs for driver steering, throttling and braking. The simulated automobile was a Ford Taurus that was operated on a roadway designed with various curves and straight segments.

Test Vehicle Design: During the ROR program, I was involved with the design of a test vehicle. This included:

  • Review state-of-the-art sensing, processing and driver interface technologies for their applicability to Run-Off-Road collision prevention
  • Design an advanced test bed vehicle for evaluating alternative countermeasures

Driver Training Simulator for Warning Algorithm Evaluation: My work on inner city transit buses involved a test of various warning algorithms integrated within a driver training simulator utilized by the New York City Transit Authority. Transit operators were recruited as study participants. My work also included a statistical analysis of transit operator responses to alerts as a function of warning modality and timing with transit operator experience, age and gender as control parameters.

Sensor Performance During Inclement Weather: A serious issue for driverless vehicles is operation during inclement weather. I worked on this problem in relation to sensor performance and weather effects modeling.

My Experience with Autonomous Vehicles: According to the Society of Automotive Engineers (SAE), there are 6 levels of vehicle automation, starting with 0 (i.e., no automation) and ending with 5 (i.e., complete system level automation with no driver involvement).** My work described above spans levels 0-2, and overlaps levels 3-5.

My Future Work: I continue to follow driverless vehicle developments regarding Testing, Technology, Machine Learning, Policy, Weather and Cyber Security.

*PhD, Physics, Boston College

**, op. cit. p 15.


Could Driverless Vehicles Be Lethal Weapons? The FBI Thinks So01 Dec

SBIR CONSULTANT BULLETIN See National Science Foundation Proposal SBIR Topic WT1 on Smart Vehicles for Potential Bidding Opportunities

According to the Guardian, “The FBI believes the “game changing” vehicle (i.e., driverless vehicles) could revolutionize high-speed car chases within a matter of years. The report also warned that autonomous cars may be used as ‘lethal weapons'”. This blog post presents findings that support the FBI’s apprehensions. Driverless vehicles could become the weapon of choice for terrorists by eliminating the need for suicide drivers.

Many late model vehicles are equipped with a variety of technologies that support driver assistance, lane position monitoring, emergency braking and infotainment. Some of these subsystems will undoubtedly lead to driverless vehicles that are under development.

According to a report written for Senator Markey (D-MA) , “The proliferation of these technologies raises concerns about the ability of hackers to gain access and control to the essential functions and features of those cars and for others to utilize information on drivers’ habits for commercial purposes without the drivers’ knowledge or consent.”

“Senator Markey sent letters to the major automobile manufacturers to learn how prevalent these technologies are, what is being done to secure them against hacking attacks, and how personal driving information is managed…These letters were sent to16 major automobile manufacturers: BMW, Chrysler, Ford, General Motors, Honda, Hyundai, Jaguar Land Rover, Mazda, Mercedes-Benz, Mitsubishi, Nissan, Porsche, Subaru, Toyota, Volkswagen (with Audi), and Volvo. Letters were also sent to Aston Martin, Lamborghini, and Tesla, but those manufacturers did not respond.”

Here is a summary of the manufacturers’ responses taken from the Markey Report:

  1. Nearly 100% of cars on the market include wireless technologies that could pose vulnerabilities to hacking or privacy intrusions.
  1. Most automobile manufacturers were unaware of or unable to report on past hacking incidents.
  1. Security measures to prevent remote access to vehicle electronics are inconsistent and haphazard across all automobile manufacturers, and many manufacturers did not seem to understand the questions posed by Senator Markey.
  1. Only two automobile manufacturers were able to describe any capabilities to diagnose or meaningfully respond to an infiltration in real-time, and most say they rely on technologies that cannot be used for this purpose at all.
  1. Automobile manufacturers collect large amounts of data on driving history and vehicle performance.
  1. A majority of automakers offer technologies that collect and wirelessly transmit driving history data to data centers, including third-party data centers, and most do not describe effective means to secure the data.
  1. Manufacturers use personal vehicle data in various ways, often vaguely to “improve the customer experience” and usually involving third parties, and retention policies – how long they store information about drivers – vary considerably among manufacturers.
  1. Customers are often not explicitly made aware of data collection and, when they are, they often cannot opt out without disabling valuable features, such as navigation.

SUMMARY: The Markey report noted, “These findings reveal that there is a clear lack of appropriate security measures to protect drivers against hackers who may be able to take control of a vehicle or against those who may wish to collect and use personal driver information…In response to the privacy concerns raised by Senator Markey and others, the two major coalitions of automobile manufacturers recently issued a voluntary set of privacy principles by which their members have agreed to abide.” It remains to be seen how effective these “voluntary principles” will be.


Driverless Vehicles – Hack Proof? Safe for You and Your Family?29 Nov

SBIR CONSULTANT BULLETIN – See National Science Foundation SBIR Proposal Topic WT1 for Potential Bidding Opportunities

Based on an article written in March 29, 2015, “Last week, Tesla Motors unveiled another first for the auto industry: starting immediately, the company will be delivering upgrades directly to vehicles via the Internet

Tesla plans to distribute these upgrades over a period of months. “Unlike most of the auto industry’s upgrades, which are delivered to customers through an independent dealer network, Tesla is building on a sales and marketing philosophy that cuts out the middleman by sending the new software directly to its cars over their embedded wireless connections.”

However, Congress is concerned about the vulnerability of wirelessly transmitted up- grades. In 2015, “Senator Edward Markey (D-MA) sent a letter to 20 car manufacturers asking them about their vehicles’ reliance on wireless computing technology and, in turn, the vulnerability of their systems. In February, he published the companies’ replies, and they weren’t completely reassuring (the full report is here).

“Manufacturers that responded to the Senator’s inquiry gave mostly ambiguous answers about the cyber security of their products. Some said they encrypt information such as driving history and physical location, while others admitted that they don’t use encryption. The same is true for third-party testing of vehicle cyber security—some do it, but many do not.”

Note: “Tesla was one of three companies that chose not to respond to Sen. Markey’s questions.”

In the meantime, “The Alliance of Automobile Manufacturers, composed of 12 automakers, and the Association of Global Automakers, comprising 12 manufacturers and five suppliers, have developed a framework for automotive cyber security best practices.”

  • What has this Alliance achieved to date on driverless vehicle cyber security?
  • Who is responsible for checking these accomplishments?
  • Has anyone from this Alliance responded clearly to Senator Markey’s questions?

Driverless Vehicles – What Makes You Think They are Safe?17 Nov

SBIR CONSULTANT BULLETIN – See National Science Foundation SBIR Proposal Topic, WT2, Wireless Devices and Components for Potential Bidding Opportunities

Driverless vehicles are equipped with several sensors to monitor the roadway and surrounding environment. These sensors include radar on the front end, a forward-looking video camera, a roof mounted LiDAR sensor, rear-mounted ultrasonic sensors, also another radar sensor affixed to the rear of the vehicle and GPS for vehicle location data. An onboard computer processes these sensor data to provide navigational/control signals for vehicle guidance. This sensor configuration is illustrated in the following link.

Rather than relying on an extensive set of if-then rules applied to these sensor data, the onboard algorithm is trained on a vast set of traffic situations. This procedure is explained as follows. “… the programmers feed the software with many traffic situations and specify the correct action for each situation. The program then searches by itself for the best configuration of internal parameters and internal decision logic, which allow it to act correctly in all of these situations. Like with us humans, it then becomes difficult to answer the question why the car exhibits a specific behavior in a new situation: no “explicit rules” have been specified; the decision results from the many traffic situations to which the algorithm had been exposed beforehand.”

Before my family or I use a driverless vehicle, I would appreciate convincing answers to the following questions:

  1. How many sensors adequately characterize the vehicle trajectory and its highway environment? What does adequate mean? How can one answer this question?
  1. How many highway traffic scenarios should be presented to this driverless vehicle-learning algorithm? 1000? 10,000? How does one know?
  1. How well should this algorithm learn? Provide correct vehicle control signals 95 percent of the time? 99 percent? What is the test for judging learning performance?
  1. Google is gathering vast amounts of highway data in support of Question #2. Although Google is an impressive organization, who evaluates their learning algorithm performance?
  1. What does the National Highway Traffic Safety Administration(NHTSA) have to say on this matter?
  1. What about insurance companies and lawyers? What are their positions on driverless vehicle safety performance?

Older Truck Drivers Unfit for Duty? Driverless Trucks to the Rescue?12 Nov

Problem: A serious problem plaguing the U.S. trucking industry is a severe driver shortage that is being countered by older drivers, who cannot afford to retire. Affecting us all is the increase in highway accidents caused by these older drivers.

According to CBS News, “Companies are aggressively recruiting retirees. Drivers more than 65 years old make up about 10 percent of commercial vehicle operators in the U.S. A five-month investigation by CBS News looks at how the increase in older drivers translates to potential danger on the nation’s highways…Individuals are working well past the retirement age of 65. But as the industry has changed, the rules of the roads have not kept up with the times — raising the question: Is more screening needed for commercial drivers?”

The Hill Law Firm noted, “A recent NHTSA data analysis by CBS News looked at truck crashes for the past three years in 12 states and found a 19 percent increase in accidents involving commercial truck and bus drivers who were more than 70 years of age. In all, between 2013-2015, more than 6,600 trucks involved drivers in that age range. (Note: The National Highway Traffic Safety Administration [NHTSA])

Possible Solution: The accident problem caused by older truck drivers could be mitigated with the advent of self-driving trucks. This statement is quite plausible given the advantages cited for driverless cars. For example, “There’s potential in efficiency, in terms of better traffic flow, but also less fuel consumption…Because cars will be automated, there will be less chance of accidents caused by human error, leading to less traffic congestion.”

The headlines below show a distinct trend toward the deployment of this driverless truck technology innovation:

Opposition to Possible Solution:

There are at least 2 reasons why the commercialization of driverless trucks will be a protracted process:

  1. “There are more than 37,000 members of the American Trucking Associations (ATA) covering every type of motor carrier in the United States.” This group will undoubtedly seek to preserve truck driver jobs by influencing Congress.
  1. In the United States, there are approximately 2 million tractor-trailer units. They will be replaced slowly over many years as they age. Thus, replacement by driverless trucks will be slow on a national scale.

Note: “The mandatory retirement age of airline pilots is 65. The Fair Treatment for Experienced Pilots Act (Public Law 110-135) went into effect on December 13, 2007, raising the age to 65 from the previous 60.” A similar provision could be imposed upon truck drivers in the interest of public safety. 

About Dr. Everson

Prior to forming this SBIR consultant practice, Dr. Jeffrey Everson was director of business development for QinetiQ North America’s Technology Solutions Group (previously Foster-Miller, Inc.).

Dr. Everson has won and been the principal investigator for several SBIR programs, including a Phase I program for NASA, a Phase I project for the U.S. Air Force, and Phase I and II contracts from the U.S. Department of Transportation. For the Phase II program, he received a Tibbetts Award for exemplifying the best in SBIR achievement.

Previously Dr. Everson held senior scientist positions at Battelle Memorial Institute, The Analytic Sciences Corporation (TASC), Honeywell Electro Optics Systems Division, and Itek Optical Systems Division.

He holds a PhD in physics from Boston College and a MS/BS in physics from Northeastern University.


For more information about how JHEverson Consulting can help your company with its SBIR and STTR proposals, please contact Jeff Everson.

JHEverson Consulting is based in the Boston area but consults for clients throughout North America. It also is supported by affiliated consultants.