How Connected Vehicles are Changing Mobility
The rise of connected and autonomous vehicles (CAVs) is often framed as a technological revolution—a leap toward a future of safer roads, smarter cities, and seamless mobility. But as the rubber meets the road, we find ourselves grappling with deeper questions:
- Who benefits from this transformation?
- What happens to the vast amounts of data these vehicles generate? and
- How are public roads, funded by taxpayers and meant for the common good, being reimagined as data pipelines for private gain?
A Brief History of Vehicle Connectivity
Vehicle connectivity didn’t begin with Teslas or robotaxis. As far back as the late 1980s, researchers at the Transport Research Laboratory (TRL) in the UK were pioneering early automated vehicle guidance systems. By the late 1990s and early 2000s, the automotive industry began commercialising telematics systems like GM’s OnStar. These early systems connected vehicles to emergency services and basic navigation support via satellite and cellular networks. In Europe, this trend culminated in the EU-mandated eCall system (introduced in 2018), which automatically contacts emergency services in the event of a serious accident, transmitting location and crash data even if occupants are unable to do so.
By the 2010s, connectivity expanded dramatically with the widespread integration of GPS, Bluetooth, and 4G LTE. Vehicles started syncing with smartphones, providing real-time traffic updates and remote diagnostics. Today, many new cars ship with embedded SIM cards, constant cloud connectivity, and over-the-air (OTA) update capabilities. Cars have evolved from mechanical horses into rolling computers—and more recently, into mobile data centres loaded with sensors.
What Data Do Connected Vehicles Generate?
Modern CAVs collect an astonishing array of data. Some of it is critical to vehicle performance, some improves driver convenience, and some, increasingly, feeds into a broader commercial ecosystem. Here’s what a typical connected car might track:
- Location and Route Data: Real-time GPS coordinates, destinations, trip history, and speed.
- Telemetry: Engine performance, braking patterns, acceleration, battery levels (for EVs), and maintenance data.
- Driver Behaviour: Seat position, seatbelt use, in-cabin activity, driver ID, and biometrics.
- Surroundings: LIDAR, radar, and camera footage used for autonomous navigation and object detection.
- Infotainment & Mobile Integration: Voice commands, music preferences, call history, messages, and app usage.
- Environmental Context: Road conditions, weather data, and traffic patterns.
But the data collection doesn’t stop there. Several automotive manufacturers have ventured into more controversial territory:
- Personal Communications: Some vehicles now scan and store text messages and emails when phones are connected, ostensibly to enable hands-free usage but potentially exposing sensitive personal correspondence.
- Driver Monitoring Systems: Interior cameras track driver alertness but can also record facial expressions, eye movements, and passenger behavior—even conversations. BMW and Tesla have faced scrutiny for their in-cabin monitoring systems that can record occupants without obvious notification.
- Financial Data: Payment information stored for toll systems, parking apps, and in-car purchases creates a profile of spending habits tied to location data.
- Weight Sensors: Some vehicles track and record the weight of occupants, supposedly for safety systems but creating potential privacy concerns around health data.
- Emotional State Analysis: Mercedes and BMW have implemented systems that analyze voice patterns to determine driver mood and stress levels.
- Sexual Activity Detection: A 2023 patent filing from one major manufacturer described sensors that could detect “intimate activities” in vehicles—purportedly to redirect autonomous vehicles to appropriate locations but raising serious privacy questions.
- Impairment Detection Systems: Some manufacturers are developing driver impairment detection systems that monitor driving patterns, eye movements, and reaction times. Companies like Volvo are working on camera-based technology that could detect signs of intoxication and automatically slow vehicles or contact assistance. While these systems don’t directly measure alcohol consumption, they create behavioural data that raises questions about who might access these impairment assessments—potentially insurance companies or law enforcement.
- Extended Data Retention: While many manufacturers claim data collection is temporary, investigations have revealed some OEMs storing personal data for years without clear user consent or knowledge.
Some of this data is anonymised, but much of it can be tied to individual drivers or passengers, especially when combined with other data sources. Recent TRL research suggests that the average modern vehicle produces upwards of 25 gigabytes of data per hour—equivalent to about a dozen HD films.
The Promise of Connected and Autonomous Vehicles
CAVs are pitched as solving many of the chronic issues that plague modern transportation:
- Safety: Human error causes over 90% of traffic accidents. Autonomous systems, in theory, could drastically reduce fatalities.
- Efficiency: Smart routing and traffic optimisation could reduce congestion, lower emissions, and improve commute times.
- Accessibility: AVs promise mobility for those who can’t drive—the elderly, disabled, or people without licences.
- Environmental Impact: Connected electric vehicles can contribute to a cleaner, more sustainable transportation system.
- Convenience: Features like remote start, automatic parking, and personalised settings improve the user experience.
Cities are also told they will benefit. With detailed vehicle data, urban planners can make more informed decisions, optimise traffic flow, and enhance infrastructure planning. The UK’s Centre for Connected and Autonomous Vehicles estimates that CAVs could deliver billions in economic benefits while transforming urban mobility patterns.
The Catch: Who Owns the Data?
Here’s where the story shifts from utopia to something more murky. As vehicles generate more data, a fundamental question emerges: who owns it?
In many jurisdictions, including the UK, the answer isn’t clear. Automakers and tech companies have generally taken the position that they own or control the data. Vehicle owners rarely have access to all of it, and often aren’t even aware of what’s being collected. Recent surveys suggest that over 70% of drivers don’t know the extent of data their vehicles gather.
This data is immensely valuable. Insurers want it to price premiums based on real-time driving behaviour. Advertisers crave it to target consumers based on location and habits. City governments want it for traffic management. And tech firms monetise it to feed algorithms and refine products.
Meanwhile, the infrastructure that makes all this possible—roads, traffic lights, public transit systems—is built and maintained by public funds. Yet the value extracted from mobility data largely accrues to private firms. In what other context would we allow such privatisation of public resource benefits?
A Tipping Point in Mobility Governance
The rise of CAVs is reshaping the very nature of what it means to travel in public space. As vehicles become data hubs, every trip becomes a transaction—not just of movement, but of information. The public, which bears the cost of infrastructure and policy development, is often excluded from the value chain.
This asymmetry raises significant concerns:
- Lack of Transparency: Users have little visibility into what data is collected or how it’s used.
- Loss of Control: Individuals can’t easily opt out or reclaim their data.
- Commercialisation of Public Space: Streets become testing grounds and data mines for private entities.
- Policy Lag: Regulations often struggle to keep pace with rapid tech innovation.
What Comes Next?
To ensure that CAVs truly serve the public interest, a shift in governance and values is needed. This might include:
- Mandating data transparency and user control.
- Treating mobility data as a public resource, especially when derived from public roads.
- Encouraging open standards and interoperability.
- Involving communities in the design and regulation of smart mobility systems.
The UK’s work through initiatives like the TRL GATEway project demonstrates possibilities for more community-centred approaches to CAV development, but much more needs to be done.
As we stand on the brink of a new era in transportation, the choices we make today will shape the mobility landscape for decades to come. Will we allow public roads to become privatised data conduits, or will we reclaim them as shared assets that serve everyone?
This is the road ahead—and it’s one worth navigating carefully.
Next in the series: “Public Infrastructure, Private Profits” will explore how publicly funded roads are being used as platforms for data extraction by private companies.
TRL’s Early Work (1980s-1990s)
Blythe, P. T., & Knight, P. (1995). “PROMETHEUS and DRIVE: Their implications for traffic managers.” Traffic Engineering & Control, 36(9), 472-477.
Carsten, O. M. J., & Tate, F. N. (2000). “Intelligent speed adaptation: The best collision avoidance system?” Proceedings of the 17th International Technical Conference on the Enhanced Safety of Vehicles, Amsterdam.
Stevens, A. (2000). “Safety implications of the PROMETHEUS and DRIVE programmes.” TRL Report 453, Transport Research Laboratory.
Crabtree, M. (1995). “Smart Vehicle Demonstrations.” TRL Project Report 157, Transport Research Laboratory.
TRL’s Recent CAV Research
Reed, N., & Flament, M. (2019). “Taxonomy of CAVs and vulnerable road users.” TRL Report PPR888, Transport Research Laboratory.
TRL (2017). “The GATEway Project: Automated vehicles in cities.” TRL PPR771, Transport Research Laboratory.
Thomas, P., & Morris, A. (2018). “CAV safety: UK research opportunities.” TRL PPR875, Transport Research Laboratory.
Fordham, C., & Fowkes, M. (2020). “A feasibility study for a CAV test track at MIRA Technology Park.” TRL CPR2631, Transport Research Laboratory.
Vehicle Data Collection and Privacy
Hubaux, J. P., Capkun, S., & Luo, J. (2004). “The security and privacy of smart vehicles.” IEEE Security & Privacy, 2(3), 49-55.
Awad, E., Dsouza, S., et al. (2018). “The Moral Machine experiment.” Nature, 563(7729), 59-64.
UK Government and Regulatory Perspectives
Department for Transport (2022). “Connected and Automated Mobility 2025: Realising the benefits of self-driving vehicles in the UK.”
Centre for Connected and Autonomous Vehicles (2018). “UK Connected and Autonomous Vehicle Research and Development Projects.”
Historical Context of Vehicle Connectivity
Walker Smith, B. (2014). “Proximity-driven liability.” Georgetown Law Journal, 102, 1777-1820.
Gerla, M., Lee, E. K., Pau, G., & Lee, U. (2014). “Internet of vehicles: From intelligent grid to autonomous cars and vehicular clouds.” IEEE World Forum on Internet of Things.
Data Ownership and Governance
Tanczer, L. M., Brass, I., Elsden, M., et al. (2018). “The United Kingdom’s Emerging Internet of Things (IoT) Policy Landscape.” UCL Public Policy Briefing.
OECD (2021). “Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across Societies.”
Public Infrastructure and Private Benefit
Sadowski, J. (2020). “The Internet of Landlords: Digital Platforms and New Mechanisms of Rentier Capitalism.” Antipode, 52(2), 562-580.
Zuboff, S. (2019). “The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power.” Profile Books.
Economic Impact and Value of Vehicle Data
McKinsey & Company (2021). “Unlocking the full life-cycle value from connected-car data.”
Transport Systems Catapult (2017). “Market forecast for connected and autonomous vehicles.” UK Department for Transport.
