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Market research of unmanned / self-driving cars (highly automated vehicles, HAV)

February 2020

Analytical Report (full version)

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Analytical Report (full version)

Market research of unmanned / self-driving cars (highly automated vehicles, HAV)
Market research of unmanned / self-driving cars (highly automated vehicles, HAV)
February 2020

Market research of unmanned / self-driving cars (highly automated vehicles, HAV)

February 2020

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J’son & Partners Consulting presents the results of comprehensive market research on highly automated vehicles (HAV). The study uses the term HAV, adopted as a priority (relative to the term Unmanned Vehicle / Self-Driving Car) in the draft Concept of Road Safety with the participation of unmanned vehicles on public roads, used in the Russian Federation.

 

A highly automated vehicle is a vehicle equipped with an automated driving system that operates within a specific operating environment for some or all trips without the need for human intervention as a backup option for road safety.

 

Automated driving systems are classified according to their automation levels, which are an assessment of the ability of an automated system to independently manage various control tasks in various road traffic situations.

 

Driving automation technologies are actively developing, almost all new passenger cars on the consumer market are already equipped with level 1 automation systems ("advanced driver assistance systems" - automatic braking, lane-keeping, adaptive cruise control, driving in motorcades, road sign recognition, lane crossing warning systems, etc.), and "autopilots" of level 2 are installed in some premium class models, including Tesla cars.

 

Fully automated vehicles of levels 4-5 are already actively used in industrial manufacturing or extractive industry, where human labor is associated with a constant risk to life (quarries, mines) and in railway passenger transport (train autopilots). In such isolated environments, it is easy to take into account all the features of the environment and create effective automation mechanisms. Unmanned shuttles are increasingly being introduced in the corporate and municipal sectors to serve passengers at airports and major shopping and exhibition centers. The main players in the global market are Baidu/King Long (China), Navya (France), EasyMile (France), ZF/2GetThere (Germany) and Local Motors (USA).

 

High-level automation technologies will not reach the mass consumer until 2030. The main problem with this is the weak readiness of automated driving systems to work in real urban environments, where there is always a factor of uncertainty that cannot be programmed in advance. According to statistics of the HAV developers, it is the last 1% of unaccounted risks that account for the majority of errors and failures of HAV systems that result in accidents that involve such systems.

 

The technology used in HAV systems

 

HAV technology differentiation factors:

 

- Degree of modification done in the automated driving system — automation functions are presented in the serial model of the vehicle, or automation can be added by the user with help of external plug-in attachment to the serial model, or it is a specially built HAV, in which the automation system is inseparable from the transport platform.

 

- Type of the "human-machine interface" of the HAV— whether there is mechanical control in the cabin or control is carried out from a push-button control panel or only remotely by operator commands.

 

- According to the type of the automation and navigation system — whether the HAV is controlled by a person remotely, or makes decisions about driving and route selection automatically, by means of software and processing data received from various sensors.

 

- Type and characteristics of sensors used. There are many HAV configurations from different manufacturers on the market, and they all differ in a set of sensors and automated driving capabilities. The general rule is that the more different sensors are used in the HAV, the better the vehicle is oriented in the environment in different situations, but at the same time, the more expensive and complicated the whole system becomes and the higher the risk of errors and failures in both the electronic and software parts, which can one day lead to fatal accidents.

 

 

The HAV management system includes the following basic elements:

 

- transport platform (chassis)

 

- system for transmitting electronic sensor commands to mechanical commands

 

- system of various external and internal sensors

 

- the on-board computing system (computer)

 

- software that synthesizes the received data and turns it into motion control commands

 

Through the use of special equipment and technologies such as video cameras, radars, lidars, GPS, odometers, computer vision, and machine learning, HAVs are able to perceive the environment. One of the main conditions for implementing the driving automation function is the presence of interface for converting digital commands to mechanical commands in the vehicle (drive-by-wire, CAN bus) this allows the on-board computer processor control steering, gas, and brake.

 

 

In the automated systems industry, there are no common standards and requirements for the HAV scheme. Every developer tries to find its own optimal technical solution. Depending on the approach chosen by each developer company, the set of hardware and systems installed on HAV, their functionality, characteristics, and usage patterns may differ.

 

J'son & Partners Consulting experts conducted an in-depth analysis of the existing HAV model range and driving automation technologies in the world, creating a comprehensive classification of HAVs that allows evaluating the vehicle by quantitative and qualitative parameters.

 

The HAV market development prospects

 

There is a continuous and consistent process of integration of highly automated transport systems in the field of transportation in particular and the everyday life of society in general.

 

The experts predict the introduction of vehicles with automated driving systems (3rd level of automation, situational automation) in the world market in the short term (2020-2022), vehicles with a high degree of automation (4th level of automation) are expected to enter the market in 2023-2025, and vehicles with full automation (5th level of automation) will enter the market no earlier than 2030.

 

Mass use of passenger HAVs will begin with special lanes on highways and special areas (University campuses, enterprises). At the first stages of implementation, the goal will be to demonstrate to all traffic participants that the use of HAVs has begun on this section of the road. The main operators of HAVs will be municipalities and corporate customers (enterprises, transport and logistics companies, taxi fleet operators). Large-scale launch of HAVs, when passenger HAVs have become common, will not occur until 2025-2030.

 

According to the "Strategy for the automotive industry development in the Russian Federation for the period up to 2025", a significant share of vehicles with limited autonomy technology (level 3) is expected to increase in the future until 2035, while it is premature to talk about significant prospects for full autonomy (level 4 and 5).

 

The development of the Russian market of vehicles with automated driving systems (3rd level of automation) lags behind the global market by 4-5 years, the share of such vehicles in sales will not exceed 1-2% due to the wider introduction of limited autonomy technologies in the basic equipment of premium segment cars. The availability of limited autonomy technologies in budget segment models will increase the share of sales to 10% by 2030. The road infrastructure will require some adaptation and modernization in terms of the state of the roadway, markings, and signs, which will increase the share in sales to 60-65% by 2035.

 

J'son & Partners Consulting experts estimate the current level of readiness of HAV technologies for launch in the Russian Federation as "average", which is due not only to the lack of development of new driving automation technologies but also to the unavailability of the industry's regulatory framework for the widespread introduction of HAVs. J'son & Partners Consulting developed a number of recommendations for implementation of HAVs in manufacturing processes, taking into account the requirements of the industry regulator.

 

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This newsletter was prepared by J'son & Partners Consulting. We make every effort to provide factual and forecast data that fully reflect the situation and are available at the time of the release of the material. J'son & Partners Consulting reserves the right to revise the data after the publication of new official information by individual players.

 

Detailed results of the study presented in the full version of the Report:

 

«Market research of unmanned / self-driving cars (highly automated vehicles, HAV)»

 

Contents

  1. Introduction

1.1.    Problem statement

1.2.    Method

1.3.    Sources

1.4.    Abbreviations

  1. Classification of HAVs

2.1.  Types of HAVs

2.1.1.         By physical characteristics

2.1.2.         By traffic automation systems

2.2.  Types of HAV navigation

2.2.1.         Navigation technologies based on sensor signals

2.2.2.         Navigation technologies with the environment recognition

2.2.3.         Remote control technologies

2.2.4.         Automated control technologies

2.2.4.1.      Automatic response functions

2.2.4.2.      Automatic threat warning features

2.3.  Advantages and disadvantages of HAVs

2.3.1.         Advantages of using passenger HAVs at the enterprise

2.3.2.         Disadvantages of using passenger HAVs at the enterprise

2.4.  Analysis of HAV technology limitations

2.4.1.         Software limitations

2.4.2.         Limitations of navigation technology using signals from sensors

2.4.3.         Limitations of navigation technology with the environment recognition

2.4.4.         Limitations of remote control systems

2.4.5.         Limitations of units and components

2.4.6.         Limitations of technical infrastructure

2.5.  Analysis of regulatory restrictions and barriers to implementation of various types of HAVs and search for ways to overcome them

2.5.1.         Foreign legal practice of regulations related to HAVs

2.5.1.1.      International legal acts and standards

2.5.1.2.      Regulations in the European Union

2.5.1.3.      Regulations in countries around the world

2.5.2.         Legal practice of HAV-related regulations in the Russian Federation

2.5.2.1.      Regulatory barriers in the Russian Federation

2.5.2.2.      Russian regulations of HAV import

2.5.2.3.      Necessary changes to the Russian regulations

2.5.2.4.      Options for overcoming regulatory restrictions in the Russian Federation

  1. Analytical review of foreign and Russian HAV manufacturers

3.1.HAV manufacturers in the world market

3.2.HAV manufacturers in the Russian market

  1. Assessment of the HAV development prospects

4.1.Global market for passenger HAVs

4.1.1.       Stages of the world market development

4.1.2.       Characteristics of the global HAV market

4.2.Russian market of passenger HAVs

4.3. Assessment of readiness of the technology for implementation

  1. Typical scheme of the infrastructure for a HAV

5.1.Typical scheme of an unmanned shuttle, automation level 4-5

5.2.Typical scheme of a HAV, level 3, with remote control

5.3.Typical wiring diagram of a HAV, level 3-5, with the environment recognition system

5.4.Typical scheme of a HAV, level 3, with marker navigation

  1. Conclusions

6.1.Conclusions about HAV development in the world        

6.2.Conclusions about regulatory restrictions, barriers, and opportunities for implementing HAVs

6.3.Recommendations for overcoming barriers        

6.4.Recommendations for testing

  1. Applications

7.1.Source list

 

List of pics

Pic. 1. Classification of driving automation levels according to SA J3016

Pic. 2. Complex of systems that make up a HAV

Pic. 3. StarLine HAV sensors

Pic. 4. Example of anattachment to the serial model that extends the functions of automated driving. EON DevKit from Comma.ai, $599

Pic. 5. Example of a modified vehicle with driving automation features. Toyota Prius serial model with Yandex autopilot add-on

Pic. 6. Example of a specially built vehicle. Waymore Firefly

Pic. 7. Example of a HAV based on universal transport chassis

Pic. 8. Unmanned Pod

Pic. 9. Passenger HAV

Pic. 10. Unmanned space shuttle           

Pic. 11. Driverless bus

Pic. 12. Unmanned train

Pic. 13. Driverless truck

Pic. 14. HAVs without zoom capability

Pic. 15. Limited scalability

Pic. 16. Free scalability

Pic. 17. Combined movement

Pic. 18. Availability of manual control option in the cabin

Pic. 19. Optional external remote control / joystick in the HAV cabin

Pic. 20. Only buttons for the main control commandsare available

Pic. 21. Remote control of the vehicle

Pic. 22. The ability of a HAV to perceive environments depends only on the characteristics and number of sensors installed

Pic. 23. Machine vision based on a neural network allows HAVs to recognize the environment

Pic. 24. Unconditional route

Pic. 25. Reaction route

Pic. 26. Custom route

Pic. 27. Permanent M2M connection between HAVs

Pic. 28. HAV movement with use of contact guides

Pic. 29. Electromechanical navigation

Pic. 30. Magnets integrated into the roadbed

Pic. 31. Laser triangulation and laser scanner on a mine unmanned loader

Pic. 32. Geolocation navigation on "virtual rails" and GPS/GLONASS antenna

Pic. 33. INB Block

Pic. 34. Ultrasonic navigation     

Pic. 35. Optical object recognition and optical camera

Pic. 36. Laser navigation and lidar

Pic. 37. Radar navigation and radar

Pic. 38. Infrared navigation and IFK camera

Pic. 39. Basic scheme of the BTS control system

Pic. 40. Phantom Auto remote control

Pic. 41. Operator at the remote control

Pic. 42. Example of a graphical interface for monitoring and route planning for HAV trucks, Cat MineStar

Pic. 43. Vehicle accident while driving on a winter road

Pic. 44. A typical HAV computer system takes the entire trunk, for example: HAV StarLine (Russia)

Pic. 45. Optical recognition of objects and their segmentation into 8 preset groups

Pic. 46. Prototype of the budget solid state lidar Velodyn 

Pic. 47. The world's most powerful but also most expensive 64-channel Velodyn HDL-64E lidar, costing $75,000    

Pic. 48. The level of detail of the lidar image (left) is better than that of the radar (right)

Pic. 49. Identification of people against the background of other objects in thermal radiation

Pic. 50. Response time depending on the data channels used, when various standard types of road obstacles occur

Pic. 51. Estimation of the amount of data generated by HAV sensors per second. A total of 4 TB per day. Evaluation done by Intel

Pic. 52. Countries that have adopted the Vienna Convention on Road Traffic

Pic. 53. Example of a reasonable violation of the rules that a tr68 HAV can allow — crossing a double solid to avoid an improperly parked car

Pic. 54. Official Russian sign “Autonomous vehicle”

Pic. 55. Ecosystem of the HAV market participants

Pic. 56. Examples of some partnerships in the field of automated driving

Pic. 57. Baidu Apolong Minibus 2nd-gen Unmanned Shuttle

Pic. 58. Unmanned Shuttle, company 1

Pic. 59. unmanned Shuttle, company 2

Pic. 60. Unmanned Shuttle, company 3

Pic. 61. Unmanned Shuttle, company 4

Pic. 62. Passenger HAV Yandex Driverless Taxi

Pic. 63. Unmanned Shuttle, company 5

Pic. 64. Unmanned Shuttle, company 6

Pic. 65. Passenger HAV StarLine

Pic. 66. Forecast of sales of passenger vehicles with traffic automation functions in the world, million units (Level 2 and higher)           

Pic. 67. Share of vehicles with automation functions in sales of new passenger vehicles in the world, %

Pic. 68. Sales of automated passenger vehicles in the world, billion dollars

Pic. 69. Average cost of an automation add-on with automated driving functions, $ USD.

Pic. 70. Average cost of anautomation add-on with automated driving functions, $ USD.

Pic. 71. Structure of the HAV offer by types of automated driving systems

Pic. 72. Structure of the offer in the world market by type of passenger HAV

Pic. 73. Share of HAV models available for purchase in 2019 to the total number of models in development

Pic. 74. Typical arrangement scheme 6.1. for a level 4-5 Unmanned Shuttle PATS

Pic. 75. Typical arrangement scheme 6.2. for a HAV level 3 with remote control

Pic. 76. Typical arrangement scheme 6.3. for a HAV level 3-5 with the environment recognition

Pic. 77. Typical arrangement scheme 6.4. for a level 3 unmanned HAV with marker navigation     

Pic. 78. Higher automation levels require more data and sensors

 

List of Tables

Table 1. “Frequency of intervention” indicates frequency at which the driver needs to take control of the vehicle (Disengagement events), km

Table 2. Overview of vehicle safety-related topics covered by various ISO standards

Table 3. Rank of development of policy and legislation in the field of HAV, 2019

Table 4. Distribution of prices for HAV shuttle offers, prices as of 2019, USD, USA.

Table 5. Distribution of prices for HAV shuttle offers in the Russian Federation in comparison with prices of foreign manufacturers, prices as of 2019, USD, USA.

Table 6. Distribution of prices for HAV platform offers in the Russian Federation in comparison with prices of foreign manufacturers, prices as of 2019, USD, USA.

Table 7. Distribution of prices for offers of ready-made unmanned shuttles, prices as of 2019, USD, USA.