Global Information
회사소개 | 문의 | 위시리스트

자율주행차 소프트웨어

Autonomous Vehicle Software

리서치사 ABI Research
발행일 2019년 07월 상품 코드 881180
페이지 정보 영문 40 Pages
가격
자세한 내용은 문의바랍니다.

자율주행차 소프트웨어 Autonomous Vehicle Software
발행일 : 2019년 07월 페이지 정보 : 영문 40 Pages

자율주행차용 소프트웨어(Autonomous Vehicle Software) 시장에 대해 조사했으며, 자동차 산업이 채용하고 있는 인공지능 소프트웨어 개발 기술 분석, 개발 기술 과제 분석, 주요 비지니스 모델·어프로치 비교 및 주요 기업 개요 등을 제공합니다.

제1장 주요 요약

제2장 자율주행 스택의 개요

제3장 인지

  • 시각 우선의 우세
  • CNN(Convolutional Neural Networks)을 이용한 동정
  • RNN(Recurrent Neural Networks)을 이용한 예측
  • 결론

제4장 센서 융합

  • 초기 vs. 후기 센서 융합

제5장 지역화 및 환경 모델링

  • 자율주행의 디지털 맵
  • HD맵 관련 이용 사례

제6장 모션 플래닝 및 컨트롤

  • 멀티 에이전트 문제
  • 행동 플래닝
  • 엔드 투 엔드 딥러닝
  • 결정론적인 세이프티 모니터
  • 복합적인 전개 시나리오

제7장 자율주행차 소프트웨어 개발 툴

제8장 AV 소프트웨어 비지니스 모델

  • 라이선싱/계약 비지니스 모델
  • 엔드 투 엔드 vs. 모듈러 어프로치

제9장 자율주행 소프트웨어 벤더

  • AImotive
  • Aurora
  • Elektrobit
  • FiveAI
  • Mobileye(An Intel Subsidiary)
  • NVIDIA
  • Zenuity

제10장 시장 예측

  • AV 소프트웨어 라이선스
  • 반복되는 수익 기회
  • 전체적인 시장 기회
KSM 19.07.11

The development of a robust Autonomous Vehicle software stack is a highly complex engineering task, requiring automakers and their suppliers to develop software that can perceive and comprehend the environment, predict the behavior of dynamic agents within the scene, and execute maneuvers in a way that does not contribute to an unsafe scenario and does not cause the occupant any discomfort.

This report investigates the artificial intelligence and software development techniques being adopted by the automotive industry too meet the challenge, and assess issues such as early vs. late sensor fusion, and how the correct balance of deterministic and trained software can help to address functional safety requirements, and give confidence that no autonomous vehicle will ever be the responsible party in an accident.

As well as considering the technical challenges which remain in autonomous vehicle software development, the report also addresses how this software can be brought to market and monetized, comparing the more flexible and modular approaches of vendors such as AIMotive and NVIDIA with the more integrated, end-to-end approaches of Mobileye and Aurora. Market sizing and forecasting is given for autonomous vehicle software licensing, as well the significant market potential for recurring revenue streams from essential and functional updates to autonomous vehicles over the course of their lifetime.

In a time of market consolidation, with many OEMs rationalizing their spend on autonomous vehicles and with many robotaxi startups beginning to feel the strain, this report can help guide OEMs to autonomous software development partners that can best help meet their autonomous and driverless objectives. At the same time, the report highlights which software development techniques and software tools can help autonomous software developers to secure vital revenue in the short term and position themselves effectively in the nascent autonomous vehicle market.

Companies Mentioned:

  • AIMotive
  • Aurora
  • BMW Group
  • Chrysler LLC
  • CNN
  • Elektrobit
  • FiveAI
  • General Motors Corporation
  • HERE Technologies
  • Hyundai
  • Intel Corporation
  • Mercedes Benz
  • Mobileye
  • NVIDIA
  • OnStar
  • TomTom
  • Veoneer
  • Zenuity

TABLE OF CONTENTS

1. EXECUTIVE SUMMARY

  • 1.1. Introduction
  • 1.2. Artificial Intelligence (AI) Techniques Dominate Perception
  • 1.3. Deterministic Software Development Complements AI
  • 1.4. Software Toold Provide Short-Term Revenue Flow
  • 1.5. Expect Vendor Consolidation during the Coming Years
  • 1.6. End-to-End Stacks Will Triumph over Modular Approaches in the Short Term
  • 1.7. Recurring Revenue Streams

2. OVERVIEW OF THE AUTONOMOUS DRIVING STACK

3. PERCEPTION

  • 3.1. Vision-First Dominance
  • 3.2. Identification Using Convolutional Neural Networks
  • 3.3. Prediction Using Recurrent Neural Networks
  • 3.4. Conclusions

4. SENSOR FUSION

  • 4.1. Early versus Late Sensor Fusion

5. LOCALIZATION AND ENVIRONMENT MODELING

  • 5.1. Digital Maps in Autonomous Driving
  • 5.2. Relevant Use Cases for HD Maps

6. MOTION PLANNING AND CONTROL

  • 6.1. A Multi-Agent Problem
  • 6.2. Behavior Planning
  • 6.3. End-to-End Deep Learning
  • 6.4. Deterministic Safety Monitors
  • 6.5. Mixed Deployment Scenarios

7. AUTONOMOUS VEHICLE SOFTWARE DEVELOPMENT TOOLS

8. AV SOFTWARE BUSINESS MODELS

  • 8.1. Licensing/Subscription Business Model
  • 8.2. End-to-End versus Modular Approaches

9. AUTONOMOUS SOFTWARE VENDORS

  • 9.1. AImotive
  • 9.2. Aurora
  • 9.3. Elektrobit
  • 9.4. FiveAI
  • 9.5. Mobileye (An Intel Subsidiary)
  • 9.6. NVIDIA
  • 9.7. Zenuity

10. MARKET EXPECTATION AND FORECASTS

  • 10.1. AV Software Licenses
  • 10.2. Recurring Revenue Opportunity
  • 10.3. Total Market Opportunity
Back to Top
전화 문의
F A Q