MAG: "Motorcyclists' Lives Depend on Getting Automated Vehicles Right"
The Motorcycle Action Group (MAG) today submitted our response to the Government's consultation on automated vehicle safety principles. We propose a practical framework to help deliver promised road safety benefits with specific measurable standards ensuring motorcyclists benefit from these improvements.
Our submission addresses a critical gap in current automated vehicle regulation. The law requires vehicles to match "careful and competent human drivers" but provides no measurable definition of that standard.
With motorcyclists making up 315 of 1,695 total road deaths in 2023 despite being less than 1% of traffic, we believe current human driving standards are inadequate for protecting vulnerable road users.
Objective Standards for Safety
We propose adopting Stephen Haley's Speed, Space, Surprise, Consequence (SSSC) model to define competent driving objectively. Haley detailed this model in his book "Mind Driving." The model gained widespread support when first published but failed adoption due to institutional inertia within driving training establishments.
The SSSC model provides measurable criteria including dynamic speed management, proactive hazard anticipation, and consequence-aware decision-making.
Colin Brown, Director of Campaigns & Political Engagement, said:
"Government has set ambitious goals for automated vehicle safety benefits. We offer a practical framework to help achieve those goals with measurable outcomes. When automated vehicles demonstrate superior performance in protecting motorcyclists, that proves the technology works and benefits all road users."
We identified "failed to look properly" as the most common factor in motorcycle collisions. This represents systematic failure in hazard anticipation that current driver training fails to address.
New Safety Principles Needed
Our response recommends several new principles for the Government's Statement of Safety Principles:
- Anticipatory Safety requiring proactive hazard detection
- Dynamic Risk Management based on actual conditions rather than speed limit compliance
- Consequence-Aware Decision-Making prioritising vulnerable road user protection
- Predictable Behaviour helping other road users safely adjust to vehicle actions
Bidirectional Safety Enhancement
We propose using automated vehicle standards to drive improvements in human driver training. This creates what we term "bidirectional safety enhancement."
Colin Brown explained:
"We can define what careful and competent driving looks like for machines. Why should we accept lower standards for humans? Stephen Haley's SSSC model offered a solution to driver training deficiencies years ago. Institutional resistance prevented its adoption. Automated vehicle regulation now presents a unique opportunity to implement proven safety frameworks that benefit all road users."
Expert Collaboration
Stephen Haley, author of "Mind Driving" and developer of the SSSC model, provided input to help develop our response. He said:
"The fundamental question is whether automated vehicles will genuinely adapt to human road users. Will humans be expected to adapt to technology limitations instead? Motorcyclists especially need automated vehicles that anticipate surprise situations and respond predictably. These vehicles must help other road users adjust safely rather than creating new hazards. If technology cannot co-exist safely with vulnerable road users, we must question whether it's ready for deployment."
We thank Stephen Haley for his valuable contribution to our consultation response.
Explicit Motorcyclist Recognition Required
We argue that automated vehicle safety principles must specifically name motorcyclists rather than using generic "vulnerable road user" terminology. Historical experience shows this generic language leads to exclusion from targeted safety considerations.
Unlike pedestrians or cyclists, motorcyclists share all road types and the full velocity range with cars. This presents unique detection and interaction challenges for automated systems.
Comprehensive Monitoring Proposed
Our submission calls for comprehensive scenario-based testing, continuous real-world performance monitoring, and stakeholder engagement to ensure automated vehicles deliver measurable safety improvements.
We propose annual reporting requirements comparing automated vehicle and human driver performance, with data separated by road user type to ensure motorcyclist safety outcomes remain transparent.
Colin Brown added: "This consultation represents a critical moment. We want to help Government succeed in delivering genuine safety improvements for the most vulnerable road users. Our framework provides the tools to achieve that goal."
What Happens Next
The consultation on the Statement of Safety Principles closes on 1st September 2025. Our submission forms part of the evidence base that will inform the final regulatory framework for automated vehicle deployment in the UK.
We look forward to working with Government to implement these proposals and deliver the road safety revolution that automated vehicles promise.
Comments