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

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.

5 Key Tangible Benefits of Intelligent Mobility
Intelligent mobility builds on the foundation of intelligent transportation to address key goals of the automotive industry: Save lives, save the environment, and reduce commuting effort.

1 A paradigm shift to a new normal introduces the subscription and user model of accessing vehicles that will coexist alongside the traditional sales and ownership model of possessing vehicles, thereby enabling mobility-on-demand solutions for every commuting need.

2 The future mobility ecosystem will draw inspiration from the smartphone business model, which is strongly user-interface oriented and service-driven, thereby rendering car ownership an option particular to consumers for which a vehicle is a prized possession.

3 Intelligent mobility holds potential to achieve up to % crash reduction using effective incident management and by means of enhanced collision avoidance.

4 Emergence of new mobility modes like ride sharing/car sharing and rapid transits can offer up to % travel time reduction in major cities while also slashing mobility spending by up to $ billion.

5 Fuel saving potential in an intelligent mobility network is likely to be catapulted by an increase in average travel speed and better optimization of traffic flow. The combined effects of which are likely to supplement an average reduction in travel stops by % and an overall % CO2 reduction.

Table Of Contents

The Future of Intelligent Mobility and its Impact on Transportation
1. Executive Summary

Executive Summary
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

2. Research Scope, Objectives, Background, and Methodology


Research Scope, Objectives, Background, and Methodology
Research Scope

Research Aims and Objectives

Key Questions this Study will Answer

Research Background

Research Methodology

Key Participant Groups Compared in this Study

3. Definitions and Overview


Definitions and Overview
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

4. Applications and Use Cases of Intelligent Mobility


Applications and Use Cases of Intelligent Mobility
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

5. Intelligent Mobility Outlook from 3 Key Regions: Europe, North America, and Japan

Intelligent Mobility Outlook from 3 Key Regions: Europe, North America, and Japan
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

6. Challenges in Intelligent Mobility Implementation


Challenges in Intelligent Mobility Implementation
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

7. Technology Trends and Evolution


Technology Trends and Evolution
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

8. OEM Activity


OEM Activity
Intelligent Mobility—Summary of OEM Activity

Case Study 1: Audi's Approach to Intelligent Mobility

Case Study 2: Daimler's Approach to Intelligent Mobility

Case Study 3: Ford's Approach to Intelligent Mobility

Case Study 4: Jaguar Land Rover's Vision of Self Learning Car

Case Study 5: Tesla's Approach to Intelligent Mobility

Case Study 6: Toyota's Approach to Intelligent Mobility

Case Study 7: Volvo's Approach to Intelligent Mobility

9. Conclusions and Future Outlook

Conclusions and Future Outlook
Key Conclusions and Future Outlook

The Last Word—3 Big Predictions

Legal Disclaimer

10. Appendix


Appendix
Overview of Cooperative and Autonomous Driving

Learn More—Next Steps

Research Background

Relevant Research

Market Engineering Methodology


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