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市場調查報告書
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1916759

下一代行動安全演算法市場，全球預測至2032年－按演算法類型、組件、車輛類型、技術、應用、最終用戶和地區分類

Next-Gen Mobility Safety Algorithms Market Forecasts to 2032 - Global Analysis By Algorithm Type, Component, Vehicle Type, Technology, Application, End User, and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的一項研究，全球下一代行動安全演算法市場預計到 2025 年將達到 22 億美元，到 2032 年將達到 55 億美元，在預測期內的複合年成長率為 13.5%。

新一代行動安全演算法是先進的運算框架，旨在預測、偵測和回應自動駕駛和聯網汽車中的安全關鍵場景。它們處理感測器融合數據、車輛動力學和環境訊息，從而實現碰撞規避、車道維持和行人偵測等即時決策。這些演算法利用人工智慧、機器學習和車聯網（V2X）通訊技術來提升情境察覺和合規性。其適應性確保了持續改進，使其成為減少事故、提升乘客安全以及支援全球全自動駕駛系統部署的關鍵。

人們越來越關注車輛安全系統

市場發展的主要驅動力是自動駕駛和近自動駕駛平台對先進車輛安全系統的日益重視。各國政府和汽車製造商正優先採用能夠減少碰撞、增強情境察覺和改善駕駛行為監控的技術。消費者對更安全出行的需求不斷成長，加上監管機構對ADAS整合的要求，正在加速安全演算法的普及應用。這些系統正成為下一代出行架構的核心，能夠在乘用車、商用車和共用出行生態系統中實現即時決策和預測性風險緩解。

監管檢驗和認證的延誤

關鍵的阻礙因素在於安全關鍵演算法漫長的監管檢驗和認證流程。這些延誤源於複雜的合規要求、不斷發展的標準以及大量的模擬和道路測試。監管機構對演算法的可靠性有著極高的保證，尤其是在自動駕駛領域。這延緩了產品上市時間並增加了開發成本。缺乏統一的全球框架進一步加劇了部署的複雜性，並為希望跨多個地區和汽車平臺擴展業務的供應商造成了瓶頸。

人工智慧驅動的預測性安全建模

人工智慧驅動的預測性安全建模蘊藏著巨大的成長潛力。這些模型利用即時感測器融合、歷史數據和情境察覺，在風險發生前進行預測。透過實現諸如規避動作或駕駛員警告等主動干預措施，人工智慧能夠提升各種出行場景下的安全性。與雲端平台和邊緣運算的整合，使得可擴展部署成為可能。隨著原始設備製造商 (OEM) 和車隊營運商尋求更智慧、更具適應性的安全解決方案，預測性建模正逐漸成為下一代出行智慧的基礎。

邊緣環境下的演算法可靠性

一個重大威脅是難以確保演算法在極端情況下（例如罕見天氣狀況、不可預測的行人行為和感測器異常）的可靠性。這些情況會削弱決策邏輯，導致安全漏洞。缺乏標準化資料集和實際極端情況測試經驗不足阻礙了演算法的穩健性。供應商必須投資於基於模擬的檢驗、冗餘機制和故障安全架構，以降低這種威脅並維護公眾對自主和半自主安全系統的信任。

新冠疫情的影響：

新冠疫情導致供應鏈受阻和車輛產量下降，暫時擾亂了行動安全演算法的研發和部署進程。然而，疫情也加速了人們對非接觸式自動駕駛和數位安全平台的關注。汽車製造商已將重心轉向軟體定義架構和遠距離診斷，從而推動了對智慧安全邏輯的需求。疫情後復甦階段，對人工智慧驅動的安全系統的投資已恢復，個人和商業出行領域都更加重視系統的韌性、適應性和預測能力。

在預測期內，碰撞避免演算法細分市場將佔據最大的市場佔有率。

由於碰撞避免演算法在預防事故和增強即時決策方面發揮著至關重要的作用，預計在預測期內，該細分市場將佔據最大的市場佔有率。這些演算法處理多感測器輸入，以檢測威脅並啟動諸如煞車或轉向等糾正措施。它們與高級駕駛輔助系統 (ADAS) 和自動駕駛平台的整合正逐漸成為所有車輛類別的標準配備。監管要求和消費者對安全駕駛體驗的需求正進一步推動其在全球的應用。

在預測期內，軟體平台細分市場將呈現最高的複合年成長率。

預計在預測期內，軟體平台領域將實現最高成長率，這主要得益於模組化和可升級安全架構的興起。這些平台能夠將人工智慧模型、感測器數據和決策邏輯無縫整合到各種車輛系統中。雲端連接、邊緣處理和空中升級等技術提升了平台的擴充性和效能。隨著汽車製造商優先發展軟體定義汽車，對強大、安全且適應性強的安全平台的需求激增，使得該領域成為市場成長最快的細分市場。

佔比最大的地區：

預計亞太地區將在整個預測期內佔據最大的市場佔有率。這主要歸功於該地區作為主要汽車製造中心的地位、快速的都市化以及對更嚴格車輛安全法規的推動。中國、日本和韓國等國家在高級駕駛輔助系統（ADAS）的採用和自動駕駛汽車試驗方面發揮主導作用。當地汽車製造商正在將先進的安全演算法整合到量產車型中，區域政府也在支持智慧運輸計畫。這個生態系統使亞太地區成為全球ADAS採用領域的領導者。

年複合成長率最高的地區：

在預測期內，由於自動駕駛領域的積極創新、健全的法規結構以及對人工智慧安全技術的早期應用，北美預計將實現最高的複合年成長率。美國在研發投資、試驗計畫以及科技公司與汽車製造商之間的合作方面處於主導地位。對智慧車隊安全日益成長的需求，加上邊緣運算和雲端整合的強大基礎設施，正在推動全部區域行動安全演算法的快速發展。

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目錄

第1章執行摘要

第2章 前言

  • 概括
  • 相關利益者
  • 調查範圍
  • 調查方法
  • 研究材料

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的感染疾病

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球下一代行動安全演算法市場（按演算法類型分類）

  • 碰撞避免演算法
  • 預測風險評估演算法
  • 駕駛員監控演算法
  • 決策安全邏輯

6. 全球下一代行動安全演算法市場（按組件分類）

  • 軟體平台
  • 人工智慧模型
  • 感測器資料處理單元
  • 嵌入式安全控制器

7. 全球下一代行動安全演算法市場（按車輛類型分類）

  • 搭乘用車
  • 商用車輛
  • 自動駕駛班車
  • 摩托車和微型交通工具

8. 全球下一代行動安全演算法市場（按技術分類）

  • 機器學習
  • 深度神經網路
  • 即時邊緣運算
  • 基於仿真的檢驗

9. 全球下一代行動安全演算法市場（按應用領域分類）

  • 高級駕駛輔助系統（ADAS）
  • 自動駕駛系統
  • 商業車隊安全
  • 智慧型運輸系統（ITS）

第10章 全球新一代行動安全演算法市場（按最終用戶分類）

  • 汽車製造商
  • 自動駕駛汽車開發商
  • 一級汽車供應商
  • 行動服務供應商

第11章 全球下一代行動安全演算法市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美國家
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 併購
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第13章：企業概況

  • Mobileye
  • Bosch Mobility Solutions
  • Continental AG
  • Aptiv PLC
  • ZF Friedrichshafen AG
  • Valeo SA
  • NVIDIA Corporation
  • Qualcomm Technologies
  • Intel Corporation
  • Renesas Electronics
  • Autoliv Inc.
  • Magna International
  • Veoneer Inc.
  • TTTech Auto
  • BlackBerry QNX
  • dSPACE GmbH
  • MathWorks
  • KPIT Technologies
Product Code: SMRC33333

According to Stratistics MRC, the Global Next-Gen Mobility Safety Algorithms Market is accounted for $2.2 billion in 2025 and is expected to reach $5.5 billion by 2032 growing at a CAGR of 13.5% during the forecast period. Next-Gen Mobility Safety Algorithms are advanced computational frameworks designed to predict, detect, and respond to safety-critical scenarios in autonomous and connected vehicles. They process sensor fusion data, vehicle dynamics, and environmental inputs to enable real-time decision-making for collision avoidance, lane keeping, and pedestrian detection. Leveraging artificial intelligence, machine learning, and vehicle-to-everything (V2X) communication, these algorithms enhance situational awareness and regulatory compliance. Their adaptability ensures continuous improvement, making them essential for reducing accidents, improving passenger safety, and supporting the deployment of fully autonomous mobility systems worldwide.

Market Dynamics:

Driver:

Increasing focus on vehicle safety systems

The market is driven by growing emphasis on advanced vehicle safety systems across autonomous and semi-autonomous platforms. Governments and OEMs are prioritizing technologies that reduce collisions, enhance situational awareness, and improve driver behavior monitoring. Rising consumer demand for safer mobility, coupled with regulatory mandates for ADAS integration, is accelerating adoption of safety algorithms. These systems are becoming central to next-gen mobility architectures, enabling real-time decision-making and predictive risk mitigation across passenger, commercial, and shared mobility ecosystems.

Restraint:

Regulatory validation and certification delays

A key restraint is the prolonged regulatory validation and certification process for safety-critical algorithms. These delays stem from complex compliance requirements, evolving standards, and the need for extensive simulation and real-world testing. Regulatory bodies demand high assurance levels for algorithm reliability, especially in autonomous driving contexts. This slows time-to-market and increases development costs. The lack of harmonized global frameworks further complicates deployment, creating bottlenecks for vendors aiming to scale across multiple geographies and vehicle platforms.

Opportunity:

AI-driven predictive safety modelling

AI-driven predictive safety modeling presents a major growth opportunity. These models leverage real-time sensor fusion, historical data, and contextual awareness to anticipate risks before they materialize. By enabling proactive interventions-such as evasive maneuvers or driver alerts AI enhances safety outcomes across diverse mobility scenarios. Integration with cloud platforms and edge computing allows scalable deployment. As OEMs and fleet operators seek smarter, adaptive safety solutions, predictive modeling is emerging as a cornerstone of next-gen mobility intelligence.

Threat:

Algorithm reliability under edge scenarios

A significant threat is the challenge of ensuring algorithm reliability under edge-case scenarios such as rare weather conditions, unpredictable pedestrian behavior, or sensor anomalies. These situations can compromise decision-making logic, leading to safety failures. The lack of standardized datasets and limited real-world exposure to edge cases hampers algorithm robustness. Vendors must invest in simulation-based validation, redundancy mechanisms, and fail-safe architectures to mitigate this threat and maintain trust in autonomous and semi-autonomous safety systems.

Covid-19 Impact:

The COVID-19 pandemic temporarily disrupted R&D and deployment timelines for mobility safety algorithms due to supply chain constraints and reduced automotive production. However, it also accelerated interest in contactless, autonomous mobility and digital safety platforms. OEMs shifted focus toward software-defined architectures and remote diagnostics, boosting demand for intelligent safety logic. Post-pandemic recovery has seen renewed investment in AI-driven safety systems, with increased emphasis on resilience, adaptability, and predictive capabilities across both personal and commercial mobility segments.

The collision avoidance algorithms segment is expected to be the largest during the forecast period

The collision avoidance algorithms segment is expected to account for the largest market share during the forecast period, driven by its critical role in preventing accidents and enhancing real-time decision-making. These algorithms process multi-sensor inputs to detect threats and initiate corrective actions such as braking or steering. Their integration into ADAS and autonomous platforms is becoming standard across vehicle categories. Regulatory mandates and consumer demand for safer driving experiences are further propelling widespread adoption globally.

The software platforms segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the software platforms segment is predicted to witness the highest growth rate, propelled by the shift toward modular, upgradable safety architectures. These platforms enable seamless integration of AI models, sensor data, and decision logic across diverse vehicle systems. Cloud connectivity, edge processing, and OTA updates enhance scalability and performance. As OEMs prioritize software-defined vehicles, demand for robust, secure, and adaptive safety platforms is surging, making this segment the fastest-growing in the market.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, attributed to its dominant automotive manufacturing base, rapid urbanization, and strong regulatory push for vehicle safety. Countries like China, Japan, and South Korea are leading in ADAS deployment and autonomous vehicle trials. Local OEMs are integrating advanced safety algorithms into mass-market vehicles, while regional governments support smart mobility initiatives. This ecosystem positions Asia Pacific as the global leader in adoption.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR associated with aggressive innovation in autonomous driving, strong regulatory frameworks, and early adoption of AI-based safety technologies. The U.S. leads in R&D investments, pilot programs, and partnerships between tech firms and automotive OEMs. Rising demand for intelligent fleet safety, coupled with robust infrastructure for edge computing and cloud integration, is driving rapid growth of mobility safety algorithms across the region.

Key players in the market

Some of the key players in Next-Gen Mobility Safety Algorithms Market include Mobileye, Bosch Mobility Solutions, Continental AG, Aptiv PLC, ZF Friedrichshafen AG, Valeo SA, NVIDIA Corporation, Qualcomm Technologies, Intel Corporation, Renesas Electronics, Autoliv Inc., Magna International, Veoneer Inc., TTTech Auto, BlackBerry QNX, dSPACE GmbH, MathWorks and KPIT Technologies.

Key Developments:

In Sep 2025, IAA Mobility, Munich ADAS and autonomous driving took center stage, with companies showcasing scalable, mass-market safety solutions. Hardware, software, and human like AI models converged to deliver safer, smarter driving platforms

In Aug 2025, Mobileye unveiled its next-generation EyeQ6 chip with enhanced safety algorithms for real-time hazard detection and adaptive driving assistance, strengthening autonomous vehicle safety capabilities.

In July 2025, Bosch Mobility Solutions introduced an AI-driven predictive safety platform integrating sensor fusion and machine learning to improve collision avoidance and lane-keeping accuracy in connected vehicles.

Algorithm Types Covered:

  • Collision Avoidance Algorithms
  • Predictive Risk Assessment Algorithms
  • Driver Monitoring Algorithms
  • Decision-Making Safety Logic

Components Covered:

  • Software Platforms
  • AI Models
  • Sensor Data Processing Units
  • Embedded Safety Controllers

Vehicle Types Covered:

  • Passenger Vehicles
  • Commercial Vehicles
  • Autonomous Shuttles
  • Two-Wheelers & Micro-Mobility

Technologies Covered:

  • Machine Learning
  • Deep Neural Networks
  • Real-Time Edge Computing
  • Simulation-Based Validation

Applications Covered:

  • Advanced Driver Assistance Systems
  • Autonomous Driving Systems
  • Commercial Fleet Safety
  • Intelligent Transportation Systems

End Users Covered:

  • Automotive OEMs
  • Autonomous Vehicle Developers
  • Tier-1 Automotive Suppliers
  • Mobility Service Providers

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Next-Gen Mobility Safety Algorithms Market, By Algorithm Type

  • 5.1 Introduction
  • 5.2 Collision Avoidance Algorithms
  • 5.3 Predictive Risk Assessment Algorithms
  • 5.4 Driver Monitoring Algorithms
  • 5.5 Decision-Making Safety Logic

6 Global Next-Gen Mobility Safety Algorithms Market, By Component

  • 6.1 Introduction
  • 6.2 Software Platforms
  • 6.3 AI Models
  • 6.4 Sensor Data Processing Units
  • 6.5 Embedded Safety Controllers

7 Global Next-Gen Mobility Safety Algorithms Market, By Vehicle Type

  • 7.1 Introduction
  • 7.2 Passenger Vehicles
  • 7.3 Commercial Vehicles
  • 7.4 Autonomous Shuttles
  • 7.5 Two-Wheelers & Micro-Mobility

8 Global Next-Gen Mobility Safety Algorithms Market, By Technology

  • 8.1 Introduction
  • 8.2 Machine Learning
  • 8.3 Deep Neural Networks
  • 8.4 Real-Time Edge Computing
  • 8.5 Simulation-Based Validation

9 Global Next-Gen Mobility Safety Algorithms Market, By Application

  • 9.1 Introduction
  • 9.2 Advanced Driver Assistance Systems
  • 9.3 Autonomous Driving Systems
  • 9.4 Commercial Fleet Safety
  • 9.5 Intelligent Transportation Systems

10 Global Next-Gen Mobility Safety Algorithms Market, By End User

  • 10.1 Introduction
  • 10.2 Automotive OEMs
  • 10.3 Autonomous Vehicle Developers
  • 10.4 Tier-1 Automotive Suppliers
  • 10.5 Mobility Service Providers

11 Global Next-Gen Mobility Safety Algorithms Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Mobileye
  • 13.2 Bosch Mobility Solutions
  • 13.3 Continental AG
  • 13.4 Aptiv PLC
  • 13.5 ZF Friedrichshafen AG
  • 13.6 Valeo SA
  • 13.7 NVIDIA Corporation
  • 13.8 Qualcomm Technologies
  • 13.9 Intel Corporation
  • 13.10 Renesas Electronics
  • 13.11 Autoliv Inc.
  • 13.12 Magna International
  • 13.13 Veoneer Inc.
  • 13.14 TTTech Auto
  • 13.15 BlackBerry QNX
  • 13.16 dSPACE GmbH
  • 13.17 MathWorks
  • 13.18 KPIT Technologies

List of Tables

  • Table 1 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Algorithm Type (2024-2032) ($MN)
  • Table 3 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Collision Avoidance Algorithms (2024-2032) ($MN)
  • Table 4 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Predictive Risk Assessment Algorithms (2024-2032) ($MN)
  • Table 5 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Driver Monitoring Algorithms (2024-2032) ($MN)
  • Table 6 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Decision-Making Safety Logic (2024-2032) ($MN)
  • Table 7 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Component (2024-2032) ($MN)
  • Table 8 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Software Platforms (2024-2032) ($MN)
  • Table 9 Global Next-Gen Mobility Safety Algorithms Market Outlook, By AI Models (2024-2032) ($MN)
  • Table 10 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Sensor Data Processing Units (2024-2032) ($MN)
  • Table 11 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Embedded Safety Controllers (2024-2032) ($MN)
  • Table 12 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Vehicle Type (2024-2032) ($MN)
  • Table 13 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Passenger Vehicles (2024-2032) ($MN)
  • Table 14 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Commercial Vehicles (2024-2032) ($MN)
  • Table 15 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Autonomous Shuttles (2024-2032) ($MN)
  • Table 16 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Two-Wheelers & Micro-Mobility (2024-2032) ($MN)
  • Table 17 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Technology (2024-2032) ($MN)
  • Table 18 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Machine Learning (2024-2032) ($MN)
  • Table 19 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Deep Neural Networks (2024-2032) ($MN)
  • Table 20 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Real-Time Edge Computing (2024-2032) ($MN)
  • Table 21 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Simulation-Based Validation (2024-2032) ($MN)
  • Table 22 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Application (2024-2032) ($MN)
  • Table 23 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Advanced Driver Assistance Systems (2024-2032) ($MN)
  • Table 24 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Autonomous Driving Systems (2024-2032) ($MN)
  • Table 25 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Commercial Fleet Safety (2024-2032) ($MN)
  • Table 26 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Intelligent Transportation Systems (2024-2032) ($MN)
  • Table 27 Global Next-Gen Mobility Safety Algorithms Market Outlook, By End User (2024-2032) ($MN)
  • Table 28 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Automotive OEMs (2024-2032) ($MN)
  • Table 29 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Autonomous Vehicle Developers (2024-2032) ($MN)
  • Table 30 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Tier-1 Automotive Suppliers (2024-2032) ($MN)
  • Table 31 Global Next-Gen Mobility Safety Algorithms Market Outlook, By Mobility Service Providers (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.