Autonomous Vehicle Awareness & Acceptance Survey
Measure how urban commuters, fleet operators, and early adopters evaluate safety perceptions, technology trust, and regulatory readiness, so you can sharpen positioning, fix conversion gaps, and prioritize segment-level acquisition.
CONTEXT & RELEVANCE
Why run this survey now
Most AV program leads don't stall on technology readiness alone. They stall due to unmapped public trust thresholds, segment-level safety perception gaps, regulatory uncertainty, liability attribution confusion, and misaligned ride experience expectations, none of which fully show up in pilot telemetry data or OEM readiness reports.
If you are...
- AV product planning lead
- Fleet deployment strategy head
- Mobility policy or regulatory affairs lead
- EV and AV commercialization director
- Ride-hail or MaaS network head
You're likely facing...
- Public trust gap: safety vs. control
- Segment split: early adopters vs. skeptics
- Liability confusion slowing fleet uptake
- Regulatory lag vs. deployment timelines
- Willingness-to-pay ceiling, unclear
This will help answer...
- Acceptance drivers by rider segment
- Trust threshold by use case
- Segment-level adoption readiness
- Fare tolerance vs. autonomy level
- Switching triggers from human-driven
RESEARCH THEMES
What This Survey Investigates
Eight interconnected research themes that map the complete consumer journey from first AV exposure to full adoption.
AV Awareness & Exposure
- First AV information source
- Familiarity across SAE levels
Perception & Trust
- Safety perception by AV level
- Trust triggers and blockers
Adoption Readiness
- Willingness to ride vs. own
- Readiness timeline by segment
Feature Prioritisation
- Must-have vs. nice-to-have features
- Override control preferences
Pricing & WTP
- Premium tolerance by AV level
- Subscription vs. outright ownership
Regulatory & Liability
- Government readiness perception
- Liability attribution preferences
Data & Privacy
- Sensor data sharing comfort
- Consent and opt-out expectations
Competitive Positioning
- OEM vs. tech brand preference
- Switching triggers across platforms
SAMPLING STRATEGY
Tell us about your ideal sample
Help us understand your target respondent profile. Select what applies, we'll design the optimal sample plan based on your inputs.
METHODOLOGY
Survey approach
For the Autonomous Vehicle Awareness and Acceptance Survey, we recommend a quant-first design with flexible data-collection modes to balance reach, depth, and verification across consumer and fleet segments.
EXECUTION PROCESS
How we execute
A proven 9-step process from scoping to delivery, designed to ensure quality, speed, and actionable insights.
Define the decision frame
Confirm objectives, target cohorts, geographies, and reporting cuts
Define the decision frame
Design the instrument
Build workstream modules mapped to outputs (drivers, friction, pricing, retention, trust)
Design the instrument
Lock the questionnaire
Review wording, sequencing, LOI, and competitive context; approve final version
Lock the questionnaire
Pilot and calibrate
Test comprehension and ease quality; refine quotas and remove friction where needed
Pilot and calibrate
Run fieldwork
Execute collection with active quota management and feasibility controls
Run fieldwork
Assure quality
Dedupe, attention checks, speed/consistency rules, removals with audit trail
Assure quality
Prepare the dataset
Clean data and deliver codebook/variable definitions
Prepare the dataset
Analyse and synthesise
Driver ranking, leakage diagnostics, pricing bands, segment insights
Analyse and synthesise
Deliver and align
Executive deck (optional dashboard) and leadership readout with recommendations
Deliver and align
COMMERCIAL TERMS
Request a Commercial Proposal
Pricing depends on cohort, geography, sample size, approach, LOI, and deliverables. Configure below for an indicative estimate.
Select Sample Size
Geography
Select Mode of Survey
Length of the Interview
$0.00
+ applicable taxes
Cost Breakdown
Note: Estimate is indicative only. Final pricing is subject to scope finalization after discovery call.
REFERENCE CASELETS
Reference
Real-world examples of survey work in the autonomous and connected mobility space.
ADAS feature prioritisation & willingness-to-pay (India)
OBJECTIVE
WHAT WE DID
DELIVERED
ADAS feature prioritisation & willingness-to-pay (India)
Driverless shuttle acceptance & route comfort mapping (Southeast Asia)
ADAS feature prioritisation & willingness-to-pay (India)
OBJECTIVE
A pan-India passenger vehicle OEM needed to rank which ADAS features drove purchase intent across first-time new-car buyers and upgrade-cycle owners , and identify the price ceiling each segment would accept before switching to a base variant.
WHAT WE DID
Ran a structured quant survey across 6 cities with 480 respondents, capturing feature salience rankings, stated willingness-to-pay corridors, trust triggers, and variant trade-off decisions using a conjoint-style choice exercise embedded in the questionnaire.
DELIVERED
A feature priority matrix by segment, a pricing corridor for each ADAS bundle tier, a ranked trust barrier list by buyer type, and a segment framework mapping feature appetite to household income and prior vehicle ownership history.
FREQUENTLY ASKED QUESTIONS
Common Questions
Answers to frequently asked questions about this survey mandate.
What decisions will this survey enable?
Who is the buyer vs who are the respondents?
Can we see differences between early adopters, cautious mainstream drivers and fleet operators?
How will you measure autonomous vehicle acceptance beyond simple ratings?
Will the survey map the full autonomous vehicle consideration journey and drop-offs?
Can this survey inform product and pricing strategy?
How will findings improve our go-to-market sequencing for autonomous vehicle launches?
Still have questions?
Schedule a discovery call to discuss your specific needs and get a custom quote.