Autonomous and Connected Vehicles Report: Key Findings and Gap Scoring Methodology

The following are priority recommendations about R&D gap targets identified during the FY16 and FY17 research period.   These recommendations are based solely on Synthesis’ conclusions and do not reflect the viewpoints of the VTO or any particular source.  Anonymity of primary sources is maintained unless Synthesis receives specific approval to share this information by individual sources.

Results from FY16 Work

Synthesis ranked ten top-level R&D topics raised by primary sources (based on open-ended, in-depth interviews), intended to represent a broad range of interests and technical fields, based on four variables using a basic scoring system.  The four variables used for ranking are a) expected energy efficiency improvement; b) amount of scientific evidence provided by sources; c) relevance to fast-growing US industry sectors; and d) a Google Scholar activity index.

The top-ten R&D topics identified from Synthesis’ contact with 100s of sources are:

  1. Embedded software
  2. Variable compression ratio
  3. Motors
  4. Power electronics
  5. Car sharing
  6. Autonomous vehicles
  7. Vehicle embedded software
  8. Solid-state batteries
  9. Carbon fiber
  10. Advanced cylinder deactivation

In terms of highest-priority recommendations, Synthesis drilled down to identify the following three areas as both directly relevant to future automotive technology capabilities and among export categories in which the US shows unique, industrial strength:

  • #1: Automotive semiconductor manufacturing and manufacturing equipment.  This includes semiconductors designed for discrete and integrated circuits (ICs) for power management, electric traction drive power electronics (inverters and converters), as well as signals processing for advanced driver assistance systems (ADAS), and infotainment systems.

  • #2: Embedded software. This covers software written to execute a particular function in a particular hardware implementation, such as field-programmable gate arrays (FPGAs), to include functional capabilities that are increasingly important for “smart” vehicles and automotive electronics, such as:
    • Machine vision;
    • Image analysis;
    • Signals processing for self-driving cars;
    • Safety management;
    • Wireless updating;
    • Artificial intelligence;
    • Automotive cloud engineering; and
    • Software to drive a wide range of field-programmable gate arrays (FPGAs) that can be altered based on the application.

  • #3: Integration of power management and wireless baseband in application processors.  This covers system-on-chip (SoC) design, in which an IC integrates multiple components of a computer or other electronic system into a single chip.  It may contain digital, analog, mixed-signal, and often radio-frequency functions – all on a single chip substrate.  SoCs are very common in the mobile electronics market because of their low power consumption.  They are becoming the first choice for future embedded system developments – which are of increasing relevance in automotive applications – due to the increasing demand for higher performance, reliability and power density in autonomous applications.

It is notable that hybrid and electric vehicle manufacturing are driving vehicles toward computerization.  Microcontrollers, sensors and analog devices have led the growth of automotive semiconductors.  McKinsey analysts have noted that three areas will drive the next wave of growth: 1) further electrification of drivetrain; 2) ‘consumerization’ of auto electronics, and 3) vehicle intelligence (including active safety innovations and connectivity-enhanced driving).  The electrification of the drivetrain due to hybrid or fully electric vehicles may lead to the “largest expansion over the next ten years,” according to these analysts.  The drivetrain accounts for 30% of all semiconductor content in an automobile, and “developing a less expensive alternative to IGBTs would be one way to win the market share in this area.” [1]

Automotive power management is the third largest market for semiconductors, comprising about 8% of the total market in 2015, with a 10.8% growth rate compared to 5.5% for the total IC market.  In 2014, the automotive market for ICs totaled about $21.7 billion.  Amongst automotive power management applications, demand is strongest in advanced driver assistance systems (ADAS), which include Lane Departure Warning (LDW), Forward Collision Warning (FCW), Automotive Emergency Braking (AEB); and infotainment systems.

From a market perspective, the worldwide automotive semiconductors industry is more than a $24 billion business and has experienced one of the fastest growth rates of any large segment in the $300 billion worldwide chip market – averaging 8 percent annually between 2002 and 2012. The top-ranked companies involved in semiconductor equipment manufacturing are provided in the table below.  US headquartered firms in this sector accounted for 39.5% of the global market in 2015.  This demonstrates an apparent competitive strength of US firms, from which Synthesis is working to identify new R&D topics relevant to the VTO mission, with transition opportunities.

Top 10 Worldwide Semiconductor Manufacturing Equipment Vendors, By Revenue ($ Billions)

In the automotive semiconductor sector there are certain technical gaps that – if filled by US-based engineering R&D advances – present a concrete opportunity to expand US-based advantages in design and development of critical engineering systems and products for the automotive industry and beyond.  US-headquartered firms are among the top-ranked companies in the automotive semiconductor sector and accounted for 39.5% of the global market in 2015.  For this reason, research work in core R&D in this sector, including research on next-generation energy efficiency targets for automotive applications, has inherently strong transition opportunities.

Within the semiconductor space, Synthesis assessed in FY16 that the following technical and engineering fields are notable for further discussion regarding R&D gaps.

  • Functional chip-designs for automotive manufacturability.  For example, Jen-Hsun Huang, [then] chief executive of graphical chip maker Nvidia Corp., said [in 2016] that some of its’ processors were being strained as Tesla has increased its cars’ capabilities.
  • Instruments, methods and designs that ensure chip-design complexity keeps pace with, rather than outpaces, manufacturing productivity.  Put another way, the present challenge is that chip-design advances are outpacing manufacturability advances, and thus, for example, lithography presently appears to lag the growing need for complex designs executed on smaller surface areas at lower costs (see Synthesis’ FY16 extreme ultraviolet (EUV) case study).   One increasingly can design chips that are needed, but cannot be produced at a competitive cost – and this presents key research, development, engineering and testing gaps.
  • There is a continuous need for developmental work in multicore system-on-a-chip (SOC) architectures, to enable faster and “smarter,” increasingly functional, smaller, more power dense electronics.

Results from FY17 Work

At the beginning of FY17, VTO tasked Synthesis to further frame the opportunity for future R&D targets based on findings from FY16, and to focus in particular on the areas of autonomous drive, LiDAR (light detection and ranging) sensors and connected vehicles. 

Synthesis identified 37 R&D gaps in FY17, from the integrated primary and secondary source analysis, from February through August 2017.  Synthesis assessed numerous trends and technologies related to autonomous drive, sensors and connected vehicles.  Findings are derived from a structured, data-driven process intended to produce findings on plausible, high-value R&D targets for sustainable, US-based jobs.

Each R&D gap can be traced back to primary source interviews or secondary source documents.  A gap is based on specific needs stated by key sources, “in ongoing commercial R&D and product development activities,” which pertain to autonomous and connected vehicles that is:

  • Hardware-focused;
  • US-based, or have the potential to be US-based;
  • Could reach commercial vehicle markets in 5-10 years; and
  • Has the capability to reduce costs, ideally by a significant (>50%) amount.

The 37 R&D gaps are categorized and scored, with trace-back capability for each gap and score to Synthesis’ internal data sets.  The quantitative analysis of the gap topics is offered as an initial viewpoint. Synthesis welcomes discussion on additional perspectives to assess the nature of the gap intelligence obtained.  The following summarizes the findings, assesses the distribution of gaps across categories, and provides an analysis of the gaps based on quantitative scores.

Drill-Down on 37 R&D Gaps Identified in FY17
The 37 R&D gaps identified in FY17 are grouped into three categories developed by Synthesis to provide guidance on trends in findings, as follows:

  • Vehicle Sensors and Intelligence Materials: Hardware for low-cost, high-performance, energy dense on-vehicle data storage, processing and communication on the vehicle; includes LiDAR.
  • Vehicle-to-Vehicle (V2X) Communications and Intelligence Networking: Hardware for low-cost, high-performance, energy dense, secure and reliable communications V2X, including sensors and sensor fusion.
  • Other R&D Collaboration Opportunities: Other opportunities to address R&D gaps in the autonomous vehicle and V2X

The three bins illustrate the range of R&D topics that Synthesis identified as gaps during this research.  These categories are not mutually exclusive and are certainly not the only categories that could be developed from the gaps.  Follow-on analyses that assess the relationships within and between smaller groups of gaps for the purpose of identifying (more efficient, multi-impact R&D topics in more detail can be done.

As just one example of such a drill-down on gap categories, and focusing only at a high level based on numerous conversations with sources, there is an apparent relationship between the individual gap categories used in this report and the level of interdisciplinary RDT&E (research, development, testing and evaluation) work that is needed to respond to each gap.   This view is reflected in the Figure 2 below.  As research moves away from addressing gaps in (e.g.) individual sensors or sensor materials, and toward (e.g.) V2X communications systems and complex systems, the work required – speaking in general, at a high-level – is increasingly of a multi-disciplinary nature, moving beyond hardware alone.  More research on the validity and implications of this finding is recommended.

Gap Scoring Methodology

A scoring system was developed to analyze the relevance of the 37 gaps identified in FY17 and to introduce initial rankings to address the work-plan objectives.  Additional scoring techniques are feasible and available for discussion (e.g., scores that apply to clusters of gaps or specific technology attributes of gaps).  To start the discussion, the following three scores are employed:

Score #1: Work-plan relevance:
For each attribute, which included (1) hardware-focus, (2) more than five-year relevance, and (3) private sector R&D investment gaps, the following scores were applied:
0 points assessed if the attribute does not apply;
5 points assessed if the attribute partially applies; and
10 points assessed if the attribute fully applies.
The maximum score on work-plan relevance is 30 points.

Score #2: Number of sources in agreement:
1 point for each company or individual expert source in agreement;
25 points if the gap is developed from an AVS 2017 consensus finding, (approximates the 25 experts, conservatively speaking, holding the consensus view).
The minimum score is one and the maximum is in increments above 25.

Score #3: Sum total:
Summation of Scores #1 and #2 above is used as the integrated Synthesis final score for final rankings.  (Again, this is just one way of ranking the gaps and additional scoring approaches are available for discussion.)

Levels of Hardware or Software, and Interdisciplinary RDT&E (Research, Development, Testing and Evaluation) Work, by Category


Distribution of Gaps Identified in FY17, by Category

The 37 gaps were analyzed and placed in one of three categories.  Of course, different categories could be developed depending on how detailed one is in assessing each gap, or group of gaps.

30%: Vehicle Sensors and Intelligence Materials
30%: V2X Communications and Intelligence Networking
40%: Other R&D Collaboration Opportunities

Autonomous and Connected Vehicles Report (2016-2018)

Introduction

Gap Analysis

Final Recommendations and Conclusions

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