 Predictive Traffic Information
Historical, Real-time, and Predictive Speed Profile Information The combination of probe-based road speed profiles and the modeling metadata such as planned events, weather, vehicle type and driving behavior will enable traffic providers such as INRIX, TrafficCast International, and Journey Dynamics to launch true predictive traffic solutions in 2009. Dynamic time-dependent routing for improved fastest route calculation and Estimated Time of Arrival (ETA) accuracy, up-front trip planning, mobile traffic alerts, and just-in-time confidence-based routing will allow consumers and professional users to save fuel and avoid wasting time. The reliability of traffic prediction models will contribute to an increased willingness to pay, and will drive uptake to more than 300 million users by 2013. This study provides definitions, benefits, and use cases for predictive traffic solutions. It describes the main market players, their traffic product roadmaps, business models, and the main barriers they are facing. Forecasts of the number of predictive traffic  What Questions Does This Report Answer?
Section 1.
EXECUTIVE SUMMARY Section 2. WHAT IS PREDICTIVE TRAFFIC INFORMATION? 2.1 Types of Traffic Information 2.1.1 Historical Traffic Information – Speed Profiles 2.1.2 Real-Time Traffic Information – Incidents and Average Speeds 2.1.3 Predictive Traffic Information 2.2 Toward a More Accurate Terminology 2.3 Traffic Information Types and Fastest Route Calculation 2.3.1 Incident Avoidance Routing 2.3.2 Static Speed Profile Routing 2.3.3 Dynamic Time-Dependent Routing 2.3.4 Confidence-Based Routing Section 3. ADVANCED PREDICTIVE TRAFFIC MODELING 3.1 Modeling and Metadata 3.2 Scheduled Events 3.3 Weather Information 3.4 Vehicle Type 3.5 Driver Profiles 3.5.1 Static Data 3.5.2 Dynamic Data Section 4. PREDICTIVE TRAFFIC INFORMATION 4.1 Main Benefits of Predictive Traffic Information 4.1.1 Accurate Fastest Route Calculation 4.1.2 Increased Accuracy of ETA 4.1.3 Lower Error Margin and Increased Confidence 4.2 Use Cases for Predictive Traffic Information 4.2.1 Upfront Trip Planning on Fixed Web Sites 4.2.2 Proactive and Personalized Traffic Alerts 4.2.3 Just-in-Time Journey Planning 4.3 User Segments 4.3.1 Consumers 4.3.2 Professional and Vertical Segments 4.3.3 Public Sector Section 5. IMPLEMENTATION AND USER INTERFACES 5.1 Traffic Prediction Technology 5.2 On-Board or Off-Board Implementations and Connectivity 5.3 User Interfaces Section 6. MAIN PREDICTIVE TRAFFIC INFORMATION PLAYERS 6.1 INRIX 6.2 Journey Dynamics 6.3 TrafficCast 6.4 Other Players 6.4.1 Dash 6.4.2 NAVTEQ Traffic Patterns 6.4.3 TomTom IQ Routes Section 7. DRIVERS, BARRIERS, AND BUSINESS MODELS 7.1 Drivers 7.2 Barriers 7.3 Business Models Section 8. PREDICTIVE TRAFFIC INFORMATION FORECASTS 8.1 In-Car Navigation 8.2 Internet Mapping Sites 8.3 Mobile Traffic Alerts 8.4 Vertical Applications Section 9. COMPANY DIRECTORY Section 10. ACRONYMS USE CASES AND SEGMENTS SCOPE OF STUDY SOURCES AND METHODOLOGY NOTES Tables
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