K E P L E R

L A B S

Project Vector

User Experience and Usability Research at Jaguar Land Rover

ResearchUser TestingMachine LearningHMI

User Perceptions

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Safety Statistics82% of users believe autonomous vehicles could significantly enhance their safety during late-night travel, particularly women and those with safety concerns about traditional transportation methods.
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Reliability Perception76% of users feel that autonomous vehicles will provide a more reliable and stress-free commuting experience compared to traditional driving, citing concerns about human error.
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Environmental Impact69% of users are more likely to consider adopting autonomous vehicles due to their potential for reducing carbon emissions, particularly environmentally-conscious individuals.
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Accessibility Benefits85% of users with mobility challenges see autonomous vehicles as a key solution for regaining independence and improving accessibility in their daily lives.

As cities explore autonomous vehicles (AVs) to solve urban mobility challenges, dominant narratives position AVs as a universal fix: safer streets, reduced congestion, and equitable access. But a research team sought to test this assumption. Could AVs truly serve as a like-for-like replacement for private vehicles—or would their real value lie elsewhere?

The goal was to understand whether autonomous vehicles could replace current travel patterns without reproducing the same inefficiencies, or if they might better serve as a complementary solution within a broader mobility ecosystem. The project examined when and where AVs might offer real benefit—especially in light of existing behaviors, preferences, and infrastructure constraints.

The team conducted mixed-methods research, analyzing both quantitative mobility data (trip frequency, solo vs. shared rides, return leg inefficiencies) and qualitative insights (user perceptions of safety, reliability, and car ownership values). The study revealed that while AVs are statistically safer than human-driven cars, they often face disproportionate scrutiny. Crucially, the findings showed that the biggest barriers to systemic efficiency were not technological—but behavioral and infrastructural:

Solo usage and deadhead trips reduced system efficiency.
Cultural attachment to private cars remained strong.
Induced demand risked exacerbating congestion if AVs were deployed without policy coordination.

Instead, the team identified niche but high-impact use cases: AVs could provide critical coverage in low-emission zones, underserved transit areas, and as first/last-mile connectors from public transport.

The case study shifted the strategic framing of AV deployment from “replacement” to “reinforcement.” AVs were no longer positioned as the primary mode of future mobility but as precision tools—deployed where public transport and active travel modes fall short. This reframing helped city planners and policy designers see AVs not as a silver bullet, but as one gear in a more human-centric, efficient, and multimodal system.