The Future of Intelligent Mobility and its Impact on Transportation
The Future of Intelligent Mobility and its Impact on Transportation
Beyond Automated Driving—Congestion Cut by 25% and Pollution 15% by 2035
26-May-2015
North America
Description
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
5 Key Tangible Benefits of Intelligent Mobility
Intelligent Mobility—An Emerging Concept that Revolutionizes Mobility
Intelligent Mobility—A Multi-faceted Sustainable Solution
Impacts of Intelligent Mobility
Key Findings and Future Outlook
Executive Summary—Associated Multimedia
Research Scope
Research Aims and Objectives
Key Questions this Study will Answer
Research Background
Research Methodology
Key Participant Groups Compared in this Study
Detailed Definition of the 3 Key Pillars
Business Case for Intelligent Mobility
Building Blocks of Intelligent Mobility
Intelligent Mobility—Key Stakeholders of Operation
Intelligent Mobility—Key Technology Enablers
Intelligent Mobility—OEMs’ Competencies Compared with Disruptors
Intelligent Mobility Value Stream
Intelligent Mobility—Ecosystem Stakeholder Imperatives
Convergence of Intelligence, Connectivity, and Mobility
Enhanced Mobility—Free-flowing Traffic Every Mile
Enhancing Electric Miles Covered by Vehicle
Enhancing Safety—Achieving the Zero-fatalities Goal
Intelligent Vehicles for Personal and Shared Use
Merging of Personal and Shared Mobility Modes
Application of Smart Navigation in Intelligent Mobility
Applying Gamification to Leverage Normative Driving Behavior
Gamification—Leveraging Crowd Sourced Network
Intelligent Driver Alerts for Intelligent Mobility
Summary of Application and Use Cases of Intelligent Mobility
Interpretation of Intelligent Mobility from 3 Key Regions
Japanese Vision of Intelligent Mobility
European Vision of Intelligent Mobility
North American Vision of Intelligent Mobility
Intelligent Mobility—A Summary of 3 Key Regions
Lack of Collaboration Among Intelligent Mobility Stakeholders
Product Liability and System Reliability
Lack of Clarity in Regulatory Framework and Standardisation
The Need for AI to Address Challenges Ahead of Intelligent Mobility
Summary of Legislative and Industry Challenges
Automated Driving—Application Road Map
Comparative Analysis of Various Automotive Sensors
V2V and V2I: Enablers of Automated Driving
Intelligent Mobility: Deployment Road Map
True Type Learning Algorithm Based Self-learning Car
Functional Road Map Leading to Intelligent Mobility
Summary of Technological Trends
Intelligent 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)
Key Conclusions and Future Outlook
The Last Word—3 Big Predictions
Legal Disclaimer
Overview of Cooperative and Autonomous Driving
Learn More—Next Steps
Research Background
Relevant Research
Market Engineering Methodology
Related Research
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Popular Topics
No Index | No |
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Podcast | No |
Author | Kamalesh Mohanarangam |
Industries | Automotive |
WIP Number | MAF4-01-00-00-00 |
Is Prebook | No |
GPS Codes | 9800-A6,9807-A6,9813-A6,9A57-A6,9AF6-A6,9A3B,9B07-C1,9B13-A6 |