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  4. > 2011 European Consumers’ Desirability and Willingness to Pay for Advanced Driver Assistance and Driving Dynamics Technologies 

Consumers' Willingness to Pay for Driver Warning, Assistance, and Information Systems

The primary aim of this study is to evaluate European consumer perceptions, understanding, expectations, motivation, and willingness to pay for driver assistance systems and active safety features. Overall, European vehicle owners continue to rank reliability and safety as the most important features when choosing a new car. More than half of vehicle owners are interested in safety features that automatically act in emergency situation. Although only 2 out of 10 drivers have experienced an accident in the last 3 years, the type of accident experienced has a significant effect on the types of safety systems desired in their cars.

Study Objectives

The primary aim of this study is to evaluate European consumer perceptions, understanding, expectations, motivation, and willingness to pay for driver assistance systems and active safety features, and also to track the changes in their preferences since Frost & Sullivan’s 2006 study on active and passive safety systems.

The specific objectives are:
•Analyze consumer awareness and interest towards:
oDriver warning, assistance, and map-enabled systems
oHMI (human/machine interface) preferences and user-friendliness of current safety systems
oPerceived benefits of integration with chassis and powertrain
oOther future safety systems and technologies (V2V [vehicle-to-vehicle] or V2I [vehicle to infrastructure] communications)
•Evaluate consumer perceptions, desirability, and willingness to pay for different types of driver warning and driving assistance systems, and systems that perform safety driving maneuvers
•Track the evolution of consumers’ perceptions, preferences, and willingness to pay since Frost & Sullivan’s 2006 study
•Identify differences by consumer demographics, vehicle segments, and by country
•Determine consumers’ associations of vehicle brands with safety
•Define an optimal service package and acceptable business model
•Recommend ideal products, features, and pricing points for OEMs (original equipment manufacturers), safety system suppliers, and navigation system and map suppliers.

Feature Coverage

Driver Warning and Information Systems
•Obstacle detection or potential collision warning
•Pre-charging of brakes for emergency performance if an emergency occurs
•Collision avoidance system that brings vehicle to partial or complete halt
•Blind-spot detection system
•Lane departure warning
•Monitoring of driver’s attention or sleepiness
•Camera-based road monitoring system
•Parking-assist system with audio warning
•Semi-autonomous parking system
•Parking-assist system with help of rearview camera
•Autonomous parking system
•Night-vision system
•Alcohol interlock system
•Traffic-sign recognition camera
•Automatic emergency braking system
•Cross-traffic warning system

Driving Assistance and Collision Avoidance
•Advanced cruise-control system with stop and go functionality
•Lane-keeping assistance system
•Electronic stability control (ESC) system
•Emergency braking assistance system
•Active-steering system
•Adaptive suspension
•Adaptive or intelligent front lighting
•Daytime running lights
•Lane-change assistance
•Adjustable speed limiter
•360 degree view camera
•Post-crash braking

Predictive and Map-based Information Assistance
•Sharp-corner warning if speed exceeds curve speed
•Speed alert
•Accident hotspot
•Map-enabled adaptive cruise control
•Map-based lane guidance
•Intersection alert
•Map-based adaptive light control
•Adaptive brake light

Methodology

Online panel-based survey of vehicle owners
•To conduct this research, we used an online panel-based methodology. This allowed us to provide images and other stimuli to test consumer perceptions of the issues associated with advanced safety features and technologies, including user interface and input/output features. Research conducted by Frost & Sullivan using this approach has proven the high quality in data collected versus computer-assisted telephonic interview (CATI) or on-street intercept surveys. We used panels specifically assembled for market research purposes. Therefore, panel quality is maintained.

Benefits of on-line panel-based surveys
•Improved and more effective screening capabilities
•Respondents typically are provided with incentives; even if screened out, they receive points, so they are more willing to answer honestly
•Questionnaires can include improved and advanced skip/branch logic and stimuli
•Responses are not left open to individual interpretation (by the interviewer)
•Faster data collection, as invitations are sent in parallel
•Generally more cost-effective than CATI or on-street intercept surveys

Key issues covered

Based on client discussions and feedback, past studies, and Frost &Sullivan’s vehicle safety analysts, the study captures:
•Consumer attitude towards safety, and segmentation based on safety attitudes
•Driving environment and driving behavior
•Awareness of advanced safety technologies and systems
•Satisfaction with the safety of current vehicle
•Importance of safety in vehicle purchase decision and purchase influences
•Importance of safety features by active system type and purchase priorities
•Determination of interaction of driver with safety systems and user interface preferences
•Willingness of driver to be monitored
• Safety feature purchase likelihood and willingness to pay for safety features
•Key differences by vehicle segments and other key demographics

Sample Size and Respondent Qualification

Sample Size:
• Total respondents

Respondent Qualifications:
• Residents of France, Germany, United Kingdom, Italy, and Spain (quotas assured equal distribution of respondents across these countries and across vehicle segments)
• Minimum years old
• Licensed drivers
• Likely to purchase a new vehicle within the next three years

Vehicle Types:
• Sedan
• Hatchback (3- or 5-door)
• Estate (station wagon)
• SUV (sport utility vehicle)
• MPV (multi-purpose vehicle)
• Other (coupe, CC)

MaxDiff Trade-Off Analysis

MaxDiff Trade-Off Analysis:
•The MaxDiff approach to trade-off analysis provides relative importance values for each feature that allow direct comparison to any other feature.
•In contrast to traditional conjoint approaches, this can compare the relative importance of features across different attributes.
•For example, MaxDiff can tell us the relative importance of the driver drowsiness warning and active steering versus blind spot detection by vehicle segment or country.
•In addition, segmentation analysis of respondents’ relative importance values across features can reveal meaningful consumer segments.
•Segments can then be cross-tabulated against focal questions to profile each group and to discover the characteristics that define each group (age, gender, vehicle segment, overall purchase priorities, willingness to pay for specific features).

MaxDiff Approach:
•MaxDiff was used to estimate the overall purchase influence or importance of each attribute vis-à-vis each attribute or feature—for example, to establish the importance of active steering or run-flat tires compared to ESP (electronic stability control) or ABS (antilock brake system).
•Importance scores range from to —the nearer to , the more important the feature is to the respondent.
•Respondents were presented with lists of features. Through complex mathematical algorithms, their choices identified most- and least-desired features.
•Based on respondents’ selections of different option combinations, an importance rating was calculated for each feature.
•The example on this screen illustrates the type of choices respondents were given.

Table Of Contents

2011 European Consumers’ Desirability and Willingness to Pay for Advanced Driver Assistance and Driving Dynamics Technologies 
Table of Contents

1. Research Objectives, Methodology, and Background
2. Executive Summary
3. General Attitudes
4. Steering Systems
5. Suspension Systems
6. Awareness of Advanced Driver Assistance Systems
7. MaxDiff Scaling—Trade-off Analysis, Total Sample and Country Analysis
8. MaxDiff Scaling—Trade-off Analysis, Vehicle Segment Analysis
9. MaxDiff Scaling—Trade-off Analysis, Cluster Analysis
10. Driver Warning and Information Systems
11. Driving Assistance and Collision-avoidance Systems
12. Predictive and Map-based Information Assistance Systems
13. Brand Perceptions
14. Demographics
15. Driving Behavior and Vehicle Use
16. Appendices
17. The Frost and Sullivan Story

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