Development of In-vehicle Computing and Simulation Technology for Energy Saving in Electric Vehicles

Development of In-vehicle Computing and Simulation Technology for Energy Saving in Electric Vehicles

Project Overview

As a comprehensive effort to reduce CO2 emissions from the use of automobiles, it is expected that publicly implementing automated driving will lead to the prevention of traffic congestion and accidents that cause such congestion.

However, in-vehicle computing, which is required for automated driving, uses a significant amount of power, which can affect the driving time and distance of electric vehicles, and given the current technology, could be a bottleneck to widespread use of electric vehicles.

Therefore, in order to greatly improve the energy efficiency of in-vehicle computing (namely by reducing power consumption by 70% compared to current technology), this project will conduct R&D on improving the energy efficiency of automated driving software and sensor systems, which have a significant effect on power consumption.

At the same time, in order to strengthen the competitiveness of the entire supply chain, where development systems for electrification and automation need to be transformed, the project will develop a standard simulation model for electric vehicles overall that is compatible with automated driving.

Project Features

Development of automated driving open platform software

The project will conduct R&D to reduce by 70% the software computation load related to hardware while securing the necessary level of performance (Level-4 automated driving in main travel environments), assuming architecture that mitigates the load placed on the network or cloud.

Development of automated driving sensor systems to realize high performance and low power consumption

Concerning “recognition” information processing for sensor systems used in automated driving, the project will conduct R&D geared to greatly reducing power consumption (by 70%) while satisfying the necessary level of performance (Level-4 automated driving in main travel environments) by enhancing the recognition method through more efficient processing and improving the performance of linked sensor devices by the enhancement of input values.

Development of electric vehicle simulation infrastructure

An electric vehicle simulation model, which is essential for testing and evaluating automated driving, will be developed to match the behavior of actual vehicles with a dynamic simulation precision of 90% or higher. By developing a standard model that can be widely used, the time required for performance verification will be reduced by half across the supply chain, thereby helping to shorten the time required for developing electric vehicles.

Project Summary

Budget

Up to 42 billion yen

CO2 Reduction Effect

In 2030
Approximately 1.69 million tons/year (Japan)
In 2050
Approximately 13.2 million tons/year (Japan)
Approximately 340 million tons/year (World)

Economic Effect (World)

In 2030
Approximately 43 trillion yen/year
In 2040
Approximately 148 trillion yen/year

Research and Development Targets

1. Open platform software for automated driving
  • Within the scope of R&D addressed by this project, reduce power consumption of In-vehicle computing by at least 70% compared to current technology, while taking into account load placed on networks and the cloud.
  • Realize level-4 automated driving function (including factors such as safety and reliability) in principal travel environments.
2. Automated driving sensor system
  • Within the scope of R&D addressed by this project, reduce power consumption of In-vehicle computing by at least 70% compared to current technology, while taking into account load placed on networks and the cloud.
  • In terms of sensory and recognition capabilities, realize level-4 automated driving function (including factors such as safety and reliability) in principal travel environments.
3. Electric vehicle simulation infrastructure
  • Establish methodologies for building the simulation model of whole electric vehicle based on a “digital twin” approach to realize level-4 automated driving compatible with SOTIF, that can be utilized in common by Japanese automobile and components manufacturers. In developing such a model, realize a dynamics simulation precision of at least 90%, while reducing by 50% the term required for using actual devices to conduct performance verifications.

Assumptions regarding estimates of CO2 reduction effect

  • Estimates calculated on basis of assumption that number of vehicles in Japan totals 74.4 million vehicles, with a global total of 1.9 billion vehicles.
  • With regard to 2030, estimates calculated on the reduction effect when high level ecological driving is in operation during normal driving on highways.
  • With regard to 2050, estimates calculated on the reduction effect when high level ecological driving is in operation during normal driving on highways and ordinary roads, and reduction effect eliminates traffic congestion in sag part and tunnels and caused by accidents.

Assumptions regarding estimates of economic effect

  • Based on the report “Future Prospects for Automated Driving and the AI Car Market, 2019” prepared by Fuji Chimera Research Institute, Inc., the market for automated vehicles is estimated to total 40 trillion yen by 2030 and the related market for components is estimated to total 3 trillion yen.
  • Based on the same report, the market for automated vehicles is estimated to total 143 trillion yen by 2040 and the related market for components is estimated to total 5 trillion yen.

Project Implementing Entities

[Research and Development 1]
Open platform software for automated driving

ThemeEntity
Microautonomy - Creating Collectively Scalable Autonomous Driving Systems
  • TIER IV, Inc.

[Research and Development 2]
Automated driving sensor system

ThemeEntity
Development of perception technology for energy saving of electric vehicles, etc
  • Sony Semiconductor Solutions Corporation

[Research and Development 3]
Electric vehicle simulation infrastructure

ThemeEntity
Establishment of a digital technology infrastructure to accelerate the development of electric vehicles and automated driving vehicles
  • Japan Automobile Research Institute (JARI)