While these delivery and ride-share companies continue to evolve to stay afloat, one thing is still certain — people require an inexpensive, reliable, and safe way to get around.
Enter the electric bicycle. It may be a game-changer for REs. As both local and federal governments are encouraging social distancing around the world, many commuters are taking to the eBike to remain active while maintaining their distance from one another at the same time, which explains why multiple eBike vendors are reporting sales spikes upwards of almost 50% since February of this year.
Lectric eBikes cofounder Levi Conlow crystallized this new trend in a recent interview: “Our customers have been saying that e-bikes are a great option for the new coronavirus-era way of living. The dramatic increase in sales shows that nationally, people are looking to shift how they get around. It’s also a fantastic option for those looking to socially isolate while getting fresh air outside.“
In an eBikesHQ article comparing over 450 ebikes, the largest share of the price bracket pie for a brand new eBike was in the $1000-2000 range.
Unlike electric cars however, one of the largest selling points of an eBike is that your standard bicycle can be easily converted into an eBike with just a few hundred dollars and some tools. Independent of which wheel the motor powers or the voltage of the battery, we compared just the top 50 most popular and most recommended eBike conversion kits around. Assuming those kits advertised as best selling actually are getting the most sales, it would seem like the average consumer is paying about $760 to turn their bicycle into an eBike, battery included!
With no end to the COVID-19 pandemic in sight, and with eBike popularity skyrocketing, eBike neo magnets could be asking for a larger share of the rare earth magnet pie very, very soon. Indeed, eBikes exceeded Hybrid and EV usage of neo magnets in 2015, and were projected to account for more than 70% of Hybrid and EV neo magnet usage in 2020, at 13,000 tpa. (Source: Steve Constantinides, “The Big Picture: Putting the Magnet Market Trends Together,” Brief at Magnetics 2018, Orlando, Florida, February 8, 2018, Slide 9). That share is indeed likely even larger than projected given the sharp drop in vehicle sales in 2020. Better line up now; do you have your order for an eBike ready?
Precious rare earths metals (REM; not the band) are in our computers; they’re in our cell phones, televisions, hospitals, and trains — and more and more, they’re in our electrified vehicles.
Rare earth permanent magnet (PM) applications have grown rapidly over the past few years, and are projected to keep doing so. As market demand continues to grow for electrified vehicles and electrical gadgets that run on specialized rare earth magnets, more and more light is being shed on where these rare earth metals are actually being mined, and where some of their most strategic customers want them to be mined.
Today, China is the most dominant supplier in the rare earth metals market. However, it was not always so:the US was lead supplier of rare earths and REM technology into the early 1980s. In a post-COVID-19 supply chain world, with every supply network being re-engineered for a new level of resilience, other countries (most notably the United States) have been increasing efforts to localize their rare earth mining and reduce dependence on foreign trade to acquire them.
As rare earths applications increase, it is only natural that the call for transparency about sourcing grows with it. Responsible Sourcing is an increasing priority among participants in the RE mining and metal production business – just like in any business. It is simply good for business to be able to show you operate fairly, treat your workers well and that you buy your materials from responsible suppliers.
However, Responsible Sourcing remains an opaque issue. Rare earth mineral mines are most common in just a handful of countries, which vary greatly in size, population, regulatory approach, governance and GDP. The truth about rare earth mining practices and actual application of mining regulations is hard to find. For example, a simple google search on the status of rare earth mining regulations and status of enforcement action re: same, produces information from a decade ago that is almost the exactly the same as in 2020, (paraphrasing): “There are many calls for reform, esp. in China, but there is little actual information about the status of reform measures.”
For example, China has been making statements about plans and attempts to crack down on illegal rare earth mining for nearly a decade now. When asked about their efforts just last year, the Chinese Ministry of Industry and Information Technology (MIIT) claimed they were making it easier to subpoena rare-earth companies practicing illegal mining, increasing penalties for being caught, and that they were establishing a “traceability system” to stop illegal market buyers. This is nearly thesame thing they were saying on the subject four years ago.
As demand for rare earths rise, so will the calls for improved transparency on sourcing. The illicit mining practices taking place in the Congo over cobalt, or in Nigeria over gold, suggests a few challenges ahead for rare earths sourced from non-transparent mining interests. Very soon, leading electric vehicle companies like Tesla, Chevy (Bolt), and Nissan (Leaf) will either prove that their rare earth magnets and batteries were responsibly sourced, or watch as some sort of large industry exposé forces them into a literal mine field of public scrutiny. We’ll keep you posted.
The top gaps in this category have relatively high work-plan relevance scores, showing the significance of two or more of private sector investment gaps, 5-year time horizons and possibilities in hardware R&D among the highly interdisciplinary topics in this gap category.
40% of the total number of gaps discovered (15 of 37 gaps) are binned in this “Other” category – suggesting the increasing relevance of interdisciplinary research in autonomous and connected vehicles for future R&D planning.
93% (14 of 15) of gaps in this category are identified by SP as consensus gaps, demonstrating the strong interest-level indicated in primary sources in these gaps.
It is plausible that this category will increase in size and significance in the future and therefore VTO has a clear opportunity to explore expanding its role in the types of topics raised here.
The topics raised in this category are mostly multi-disciplinary, underscoring a potential role for VTO. A more detailed review of the top five consensus gaps for this category is contained in the Recommendations section.
Only one gap is not a consensus gap – Balancing Vehicle Design Time with Software Upgrade Time-Cycles – and therefore is ranked at the bottom of this category.
Autonomous and Connected Vehicles Report (2016-2018)
Findings from the V2X Communications and Intelligence Networking
All but one of the gaps in this category have high work-plan relevance scores, indicating again the significance of both 5-year time horizons and/or hardware R&D among the interdisciplinary topics in this gap category.
30% of the total number of gaps identified (11 of 37 gaps) is classified as V2X communications and intelligence systems gaps.
82% (9 of 11 gaps) of the gaps in this category are identified by SP as consensus gaps, demonstrating the strong interest-level indicated in primary sources (again, non-statistical, non-survey-based and a snap-shot in time) for these gaps.
The top five consensus gaps in this category are highlighted for relevance to our research work-plan:
V2X software-hardware integration (all aspects of design, test, engineering and piloting of sensing and communication protocols);
Cyber Security (covers all aspects of making V2X communications secure);
Low-Cost Geo-Localization at 2-3 cm accuracy (requires many sensors, infrastructure and systems to work seamlessly together);
Low Cost V2X Connectivity (requires benchmarking true costs of pilot systems, and paths to cost reduction); and
Strategic Planning (guidance for fed-state-local governments and industry in defining needs and opportunities for integrated Smart City, Smart Grid and Smart AV Car applications).
Only two gaps in this category are not considered consensus gaps at this time.
Autonomous Vehicle Mobility Command Centers;
OEMs as Spectrum Providers, where the primary sources expressed a need to address the volume of data that vehicles will be producing and using in autonomous vehicle and connected vehicle scenarios.
Most V2X and Intelligence Networking gaps have both strong support in the AVS community and relatively high work-plan relevance scores. This suggests opportunities to take action on many gaps in this category.
Synthesis assesses that VTO has opportunity to expand engagement into new technical fields because all V2X and Intelligence Networking gaps exist at the interface between software and hardware.
Autonomous and Connected Vehicles Report (2016-2018)
Findings from the Vehicle Sensors and Intelligence Materials:
All gaps in this category have high work-plan relevance scores; which is to say at least 20 out of a maximum 30. This reflects the relative significance of two or more of the attributes of private-sector investment gap, 5-year time horizons and hardware R&D among topics in this gap category.
These gaps indicate in particular numerous pathways to hardware-focused R&D across the full spectrum of the sensor and sensor application-engineering development chain.
30% of the total gaps discovered (11 of 37) relate to vehicle sensors and intelligence materials.
46% (5 of the 11 gaps) of gaps in this category are assessed by Synthesis as consensus gaps, indicating that speakers at the AVS 2017 plenary summary sessions addressed these topics as gaps in their concluding slides and accompanying discussions, per Synthesis analyst attendance at AVS 2017 in San Francisco. These gaps appear to have the largest number of experts in agreement, based on the non-statistical, non-survey-based, primary source research in this study.
The following consensus gaps that would benefit from immediate attention:
Sensor Cost Reduction;
Scalable Low-Cost Autonomous Vehicle (AV) Black Boxes;
Onboard Scalable Low-Cost Power and Processing (to enable sensor operations); and
Sensor Fusion.
The six remaining gaps in this category – from miniaturized processors to memory supply chain bottleneck – are not considered consensus gaps at this time. Nonetheless, they deserve careful consideration because, from among hundreds of sources contacted, primary sources took time to recommend the gap to Synthesis in an in-depth interview.
Autonomous and Connected Vehicles Report (2016-2018)
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:
Embedded software
Variable compression ratio
Motors
Power electronics
Car sharing
Autonomous vehicles
Vehicle embedded software
Solid-state batteries
Carbon fiber
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)
This report provides an update on work completed by Synthesis Partners, LLC (“Synthesis”) for the Department of Energy’s Vehicle Technologies Office (VTO) under contract number DE-DT0006388, during fiscal years (FY) 2016 and 2017.
Synthesis performs targeted research to help inform VTO research and development (R&D) decision-making about critical technology bottlenecks, gaps or constraints in the US industrial base and supply chains. This report is the public outcome of a global, data-driven approach – employing hundreds of primary sources and thousands of secondary sources – to assess and characterize potential R&D gap topic areas that are relevant to the VTO’s mission of energy affordability, efficiency and resiliency, and that can provide a path toward transitioning VTO R&D work into US-based jobs.
This review covers targeted research on R&D gaps regarding technologies and capabilities in vehicle electric traction drive, autonomous and connected vehicle systems and sectors. Two separate inquiries were pursued in FY16 and FY17. Research during FY 2016 focused on identification and prioritization of research and development (R&D) fields in the automotive sector that have a strong chance to grow in the USA because of unique US-based capabilities and strengths. Research work during FY 2017 focused on identification and prioritization of gaps in R&D that point to promising, hardware-oriented research directions in autonomous and connected vehicle fields. Primary sources and English-language (and targeted foreign language) secondary sources, as well as proprietary and commercial databases, were accessed during the period of this work.
A high priority has been placed on R&D fields that are among the highest-value (based on share of US exports and revenue growth rates), and that are relevant over five-plus year planning horizons for VTO decision-makers seeking significant energy efficiency and core technology cost reductions. The gap intelligence work in FY16 and FY17 is ultimately intended to identify high potential targets for US autonomous vehicle R&D development and high-value job creation.
Overview of FY16 and FY17 Tasking
Details on the tasking and deliverable produced over the FY16 and FY17 period are available from VTO. This report provides a summary review of the public key findings and recommendations produced.
During FY16 Synthesis assessed US export sectors relevant to electrical engineering in the automotive industry, in terms of relative size (by sales) and growth rates, in order to identify high strength or competitive US sectors. The top-ranked sectors identified are home to some of the most highly competitive and innovative US-based firms. These sectors were then reviewed to identify and assess potential new R&D areas, defined as technical areas in which the VTO has not previously engaged and where R&D investments could address a gap. Such new R&D areas represent a complex set of technical needs that are generally beyond the ability of any individual company to address, and which are included under Synthesis’ interpretation of the VTO mission.
During FY17, Synthesis identified, characterized and
prioritized key gaps in current research activities, in order to highlight
promising R&D possibilities in the fields of:
Light Detection and Ranging (LiDAR);
Sensor system development; and
Vehicle-to-vehicle (V2V) or
vehicle-to-anywhere connectivity (V2X).
Promising research in the FY17 work is defined as R&D activities pertaining to a gap in autonomous and connected vehicle technology that is also:
Hardware-focused;
US-based, or has 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.
Statistics on Sources Accessed in FY17
Sources: Synthesis Partners, LLC (2017)
Autonomous and Connected Vehicles Report (2016-2018)
The following summarizes recommendations from Synthesis’ FY17 work. These recommendations focus on autonomous vehicles, connected vehicles (vehicle-to-anywhere (V2X)), and LiDAR sensors. They provide the “consensus” viewpoints, based on Synthesis’ ranking of information collected from 100s of primary sources and 1,000s of secondary sources evaluated during FY17.
There is a clear opportunity and need to address the challenge of integrating software and hardware for future mobility applications, particularly mobility use-case-driven R&D gaps in software-enabled, V2X systems are expected to grow significantly.
A taxonomy or roadmap of R&D gaps in autonomous and connected vehicles is needed to depict the attributes and categories of technical gaps. In this regard, there is an opportunity to lead R&D data collectors to collect, categorize, and quantify the priority or relevance of specific types of R&D gaps– especially in the fast-changing and growing LiDAR, sensors, autonomous and connected vehicle research spaces.
Support for engagement in hardware-oriented sensor R&D, including in: a. Substrate-level (e.g., increase wafer size) R&D b. Embedded electro-optics design and engineering (e.g. improve imaging resolution, resilience, accuracy) c. Glass materials development (e.g., address reduction of REs, and add improved optics and machining properties) d. Application-specific electro-optical engineering (e.g. learning-by-doing manufacturing and electrical engineering for human transport applications, in terms of cost, quality and performance)
Two gaps in the V2X and Intelligence Networking category are consensus gaps and deserve VTO’s immediate attention: a. R&D on Low-Cost Geo-Localization with 2-3 cm accuracy: Opportunity for design and engineering of low-cost sensors and sensor fusion systems that enable required accuracy for reliable autonomous vehicle applications. b. V2X Software-Hardware Integration: Opportunity for guidance, independent test, validation and understanding for software-hardware integration for highly specific AV use cases.
The following top five consensus gaps in the Other R&D Collaboration gap category are recommended for VTO’s immediate attention:
a. Fundamental Competition at Core Technology Level(e.g., Robotics, Machine Vision, AV Sensor Requirements):
The need is for more clarity, commitment, and investment regarding the core figures of merit, the baseline current state and the targets for future R&D – all to accelerate potential breakthroughs in these fields.
b. Scalability of Autonomous Vehicle Engineering (Hardware, Software, Multi-Context, Global Implementations)
The need is to investigate AV engineering approaches across a spectrum of operational contexts (e.g., city, urban, people-transport, things-transport, logistics, on-ground, marine, air, etc.) and to address where scalable solutions are being executed, are feasible, and to identify and share best-practices.
c. Situational Awareness: Data Repository on Technology Used (AVs, Smart City and Smart Grid)
The need is for a verifiable, publicly accessible data source that provides multiple stakeholders (e.g. academics, researchers, investors, inventors and state-local-federal partners) clarity about who is doing what where, in order to catalyze facts-based decision-making in this important and growing field.
d. Systematic Assessment of AV Technology Gaps
The need, as discussed above, is for a systematic, independently derived view on the technology gaps in autonomous and connected vehicle applications. A technology roadmap is recommended based on the high-score for this gap.
e. Need for Opto-Electronic Engineers (including for LiDAR, Optics, Sensor Development Engineering)
The probability that AV technologies, like LiDAR, will be available at significantly lower costs for widespread application depends significantly (indeed, this is a first and foremost driver – based on numerous sources) on the availability of a skilled workforce to ramp up production, reduce costs and maintain quality of end products.
The availability of skilled AV-domain manufacturing engineers is viewed as a key constraint to growth in capacity (esp. if the growth is rapid) of autonomous vehicle technologies (including LiDAR) in the US.
Disruptive Technology Recommendations
The extensive data collection and analysis in FY17 suggests that there are disruptive technology R&D opportunities to consider in the fields of LiDAR-related sensors, connected vehicles, and V2X. The data also suggests that there may be unique opportunities for US-based job creation by focusing on such leap-ahead innovations.
“Disruptive” is defined as technologies which present opportunities to address significant cost- or cost and performance gap closing needs by one or more orders of magnitude, in which current technology is too costly to scale to address the radical performance increases and cost reductions that are needed.
Each of the following recommendations regarding disruptive technology reflects Synthesis’ independent assessment of both primary and secondary source research completed under this work-plan.
New I/O control architectures can address multiple on-vehicle intelligence processing functions, at human-transport quality, in fraction of time and fraction of cost. For example, fusion of all domain control units (DCUs) in one centralized vehicle computer OR new validated, tested architectures that permits “full sense-and-compute” at the edges. New I/O control architectures would present:
a. A solution that removes the requirement to send data off of vehicle, including for map location, navigation or processing. b. A solution that is lighter, faster, more secure data generation, collection, mining and processing on vehicle. c. solution that can scale in terms of information processing to match the “every car a map-maker and every car a map-user” paradigm.
“Power by Ethernet:” This covers the need to wirelessly charge AVs in many contexts, while mobile or stationary. An alternative to costly production, install, maintain and package of power through (heavy) motors, batteries and wiring harnesses.
Accelerated engineering of “hard-coded hardware accelerators.” This includes – for example – hard-coded devices that can enable fleet-wide AV software upgrades and that enable such software upgrades to be: a. Fail-safe b. Valid c. Cyber secure
Final Conclusions
The combination of autonomous systems and Internet of Things (IoT) demands new, in-depth understanding of future engineering R&D requirements at every level of the systems engineering process. Information is (becoming) the new energy.
New partnerships among OEMs, Tier 1-3s, software developers,
cyber-security experts, research universities and federal R&D labs are
needed to catalyze R&D work in hardware, software and systems-engineering
fields. Such new partnerships are needed
to guide the software-based and interdisciplinary work that needs to be done to
advance autonomous and connected vehicles.
Synthesis has explored the industry data in this report on a few topics,
and has identified several fast-growing fields that will frame the nature of
this new R&D reality.
In brief, future R&D will enable systems and components in vehicles to communicate and compute with networks from the component up through the transportation grid, through to a global-level grid. This is why emerging R&D gaps are numerous, and not only hardware-focused. From a hardware perspective, autonomous and connected vehicles continuously seek smaller, more functional, more power dense and lower cost designs of every component and sensor. From an information perspective, rigorous processes for collecting, maintaining and analyzing information about the “information gains” of future R&D is needed. From a US job and manufacturing growth perspective, this report finds that more skill in engineering-to-manufacturing capabilities is needed. This simply means more learning-by-doing.
The fast-emerging, estimated multi-trillion dollar market for autonomous systems is directly connected to (as both a driver and beneficiary of) the Internet of Things.[1] Semiconductor manufacturers play a key role in this opportunity.
Autonomous and Connected Vehicles Report (2016-2018)
Global EV Supply Chain Intelligence: Portal to Actionable Reporting on EV Charging Stations, Motors, Power Electronics, Rare Earths, Lithium Battery Materials and Autonomous Vehicle Supply Chain Assessments 
