The Future of Intelligent Mobility and its Impact on Transportation

Beyond Automated Driving—Congestion Cut by 25% and Pollution 15% by 2035

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While cooperative-driving (V2X-based) is a dependency-based model and automated driving (sensor-based) is a self-sufficient model, these roads converge and complement, thereby leading to intelligent mobility. Moreover, intelligent mobility integrates automated, connected driving with new mobility business models, helping to reduce fatalities, traffic congestion, and per capita carbon footprint. This study outlines the need for intelligent mobility, an ideology that drives people from origin to destination, yet reduces traffic congestion, pollution, and road fatalities by leveraging state-of-the-art automotive technologies. The 3 key regions covered are Europe, North America, and Japan. The study period is 2015 to 2035.

Table of Contents

Executive Summary5 Key Tangible Benefits of Intelligent MobilityIntelligent Mobility—An Emerging Concept that Revolutionizes MobilityIntelligent Mobility—A Multi-faceted Sustainable SolutionImpacts of Intelligent MobilityKey Findings and Future OutlookExecutive Summary—Associated MultimediaResearch Scope, Objectives, Background, and MethodologyResearch ScopeResearch Aims and ObjectivesKey Questions this Study will AnswerResearch BackgroundResearch MethodologyKey Participant Groups Compared in this StudyDefinitions and OverviewDetailed Definition of the 3 Key PillarsBusiness Case for Intelligent MobilityBuilding Blocks of Intelligent MobilityIntelligent Mobility—Key Stakeholders of OperationIntelligent Mobility—Key Technology EnablersIntelligent Mobility—OEMs’ Competencies Compared with DisruptorsIntelligent Mobility Value StreamIntelligent Mobility—Ecosystem Stakeholder ImperativesConvergence of Intelligence, Connectivity, and MobilityEnhanced Mobility—Free-flowing Traffic Every MileEnhancing Electric Miles Covered by VehicleEnhancing Safety—Achieving the Zero-fatalities GoalApplications and Use Cases of Intelligent MobilityIntelligent Vehicles for Personal and Shared UseMerging of Personal and Shared Mobility ModesApplication of Smart Navigation in Intelligent MobilityApplying Gamification to Leverage Normative Driving BehaviorGamification—Leveraging Crowd Sourced NetworkIntelligent Driver Alerts for Intelligent MobilitySummary of Application and Use Cases of Intelligent MobilityIntelligent Mobility Outlook from 3 Key Regions: Europe, North America, and Japan Interpretation of Intelligent Mobility from 3 Key RegionsJapanese Vision of Intelligent MobilityEuropean Vision of Intelligent MobilityNorth American Vision of Intelligent MobilityIntelligent Mobility—A Summary of 3 Key RegionsChallenges in Intelligent Mobility ImplementationLack of Collaboration Among Intelligent Mobility StakeholdersProduct Liability and System ReliabilityLack of Clarity in Regulatory Framework and StandardisationThe Need for AI to Address Challenges Ahead of Intelligent MobilitySummary of Legislative and Industry ChallengesTechnology Trends and EvolutionAutomated Driving—Application Road MapComparative Analysis of Various Automotive SensorsV2V and V2I: Enablers of Automated DrivingIntelligent Mobility: Deployment Road MapTrue Type Learning Algorithm Based Self-learning CarFunctional Road Map Leading to Intelligent Mobility Summary of Technological TrendsOEM ActivityIntelligent Mobility—Summary of OEM Activity Case Study 1: Audi’s Approach to Intelligent Mobility Case Study 1: Audi’s Approach to Intelligent Mobility (continued) Case Study 2: Daimler’s Approach to Intelligent Mobility Case Study 2: Daimler’s Approach to Intelligent Mobility (continued) Case Study 3: Ford’s Approach to Intelligent Mobility Case Study 3: Ford’s Approach to Intelligent Mobility (continued) Case Study 4: Jaguar Land Rover’s Vision of Self Learning Car Case Study 4: Jaguar Land Rover’s Vision of Self Learning Car (continued)Case Study 5: Tesla’s Approach to Intelligent Mobility Case Study 5: Tesla’s Approach to Intelligent Mobility (continued) Case Study 6: Toyota’s Approach to Intelligent Mobility Case Study 6: Toyota’s Approach to Intelligent Mobility (continued) Case Study 7: Volvo’s Approach to Intelligent Mobility Case Study 7: Volvo’s Approach to Intelligent Mobility (continued) Conclusions and Future OutlookKey Conclusions and Future Outlook The Last Word—3 Big PredictionsLegal DisclaimerAppendixOverview of Cooperative and Autonomous DrivingLearn More—Next StepsResearch BackgroundRelevant ResearchMarket Engineering Methodology




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