National Highway Traffic Safety Administration (NHTSA) defines Advanced Driver Assistance Systems (ADAS) are in-vehicle technologies designed to provide drivers with alerts, automated interventions, or supports intended to reduce human error in the driving task. Common ADAS features include forward collision warning (FCW), automatic emergency braking (AEB - a system that helps you break in exceptional circumstances), lane departure warning (LDW), adaptive cruise control (ACC), blind spot detection (BSD), and parking assist systems (PAS). These systems vary in automation level, from purely advisory alerts to partial control interventions.  

• Euro NCAP defines FCW as an audiovisual warning automatically provided by the vehicle in response to detection of a likely collision. 
• Euro NCAP defines AEB as braking applied automatically by the vehicle in response to a likely collision to reduce speed and potentially avoid the collision 
• IIHS (iihs.org) defines LDW as using camera to track lane position and alerting the driver if the vehicle strays across lane markings without the turn signal activated 
• NHTSA describes ACC as cruise control that automatically adjusts vehicle speed to maintain a preset following distance from the vehicle ahead. 
• IIHS defines BSD as using sensors to monitor areas behind the vehicle and alerting the driver when a vehicle is detected in an adjacent lane blind spot or rapidly approaching 

NHTSA’s driver- assistance technology overview includes parking assistance and rear cross-traffic warning as low-speed maneuvering aids that help drivers detect objects or approaching vehicles when revering or parking. 

ADAS enhances safety by mitigating driver errors and compensating for functional deficits, particularly among disabled and older drivers.   

Current research and legislation show that although ADAS may enhance safety it should not be used as a replacement for driver function and capability  

For example, features like automatic braking can compensate for delayed reaction times, while lane keeping and blind spot assist enhance spatial awareness.  

Understanding the interface and interaction between ADAS and driver is critical for clinicians assessing medical fitness to drive and supporting driver rehabilitation. 

Clinicians must ensure that ADAS features align with individual capabilities, considering sensory, motor, and cognitive limitations. 

Research indicates that older drivers appreciate the safety potential of these systems but may experience barriers to adoption, including trust and complexity of use (Wood et al., 2024; Biassoni et al., 2024).  

In medical fitness to drive evaluations, ADAS can be considered both as a mitigating factor and as a potential source of new challenges. Assessors should evaluate the driver’s understanding, response, and adaptation to ADAS. Integration into assessments may involve clinical examination, on-road or simulator-based trials, and exploration of system reliance. ADAS can support risk reduction but must not replace clinical judgement on driving capacity (Urlings et al., 2018; Samuelsson et al., 2022). Clinicians should also identify behavioural adaptation or overreliance on automation (AAA Foundation, 2017). 

Clients with cognitive impairment (e.g., dementia, acquired brain injury, MCI) may struggle with ADAS comprehension, alert interpretation, and trust calibration.  

Systems that rely on quick interpretation may inadvertently increase cognitive workload (Béquet et al., 2020).  

Poor insight and fluctuating attention can reduce safe use. Drivers may also suffer from overstimulation when being exposed to safety or warning alarms, leading to unwanted side effects. 

Interfaces must be evaluated for accessibility, ensuring that touchscreen, auditory, and visual cues are usable by clients with cognitive or sensory limitations. 

The inputs (visual, auditory and haptic) should be tailored to individual needs of clients. 

ADAS may support drivers by reducing demand in specific driving tasks, including collision avoidance, lane maintenance, parking maneuvers, and speed/headway control. These features can help a driver to compensate for functional declines in attention, reaction time, and visual processing, particularly in older or medically impaired drivers (Davidse, 2006; AAA Foundation, 2015, Xu et al., 2023). However, there is limited evidence that ADAS directly facilitates transition from driver to non-driver. Instead, successful driving cessation is best supported through proactive planning, shared decision making, and access to alternative transport options (Dickerson et al., 2024). Therefore, ADAS should be considered as supportive tools to extend safe driving within defined limits, rather than a mechanism for enabling transition to non-driving. 

Despite the proven safety benefits and technological advances of Advanced Driver Assistance Systems (ADAS), a number of limitations persist that constrain their effectiveness — particularly for disabled and older drivers. Recognising these limitations helps clinicians, policymakers, manufacturers, and researchers develop strategies for more inclusive, equitable, and safe use. 

6.1: Technical and System Limitations 

• Sensor and environmental dependence: ADAS functions rely heavily on sensor accuracy. Adverse weather, low light, dirty cameras, or road markings can compromise performance, causing system disengagement or false alerts (Ayoub et al., 2022). Inconsistent behaviour across manufacturers: Variations in naming, interface design, and operational boundaries between brands create confusion among drivers.
• Partial automation gaps: Many systems require instantaneous 'takeover’ from automation back to the driver, yet evidence shows humans take several seconds to regain situational awareness (Carsten & Martens, 2019). 
• Limited ability to detect complex hazards: Vulnerable Road users or unmarked or temporary lanes can challenge current algorithms, particularly in mixed traffic environments. 

. 6.2: Human and Behavioural Limitations

• Over-reliance on automation: Reliable system performance can lead drivers to reduce vigilance and increasing risk (AAA Foundation, 2017). Trust calibration issues: Drivers may either distrust or over-trust ADAS, both of which can increase risk. 
• Training gaps: Most drivers receive little formal instruction on ADAS at purchase, leading to no use or unsafe use.  
• Accessibility and interface design: Many human–machine interfaces lack inclusive design for older or disabled users (Stulce & Antin, 2024).  

6.3: Organisational and Policy Limitations (in the context of driving assessments rather than driving test):  

(A driving test is a standardised, pass-fail evaluation conducted by licensing authorities to determine whether an individual meets the minimum legal requirements to drive, whereas a driving assessment is a holistic, clinician –led evaluation of functional ability, risk, and adaptation, including the safe use of vehicle technologies (Driver & Vehicle Standards Agency; Driving Mobility; Dickerson & Schold Davis, 2014)

• Absence of standardised clinical guidance linking ADAS to driver assessment pathways. 
• Limited awareness among clinicians and licensing bodies about ADAS implications. 
• Inequitable access: Cost and availability restrict access to modern vehicles for disabled drivers. 

Clinicians and Driver Assessors: 

• Integrate ADAS education into clinical assessments. 
• Counsel clients about system limitations, for example when using self-parking feature. 
• Promote simulator or instructor-led familiarization in their own car. 

Manufacturers, such as Adaptation Companies and Designers: 

• Adapt to universal design for Human Machine Interfaces (HMIs) and alerts. 
• Use consistent labeling and terminology. 
• Develop adjustable assistance profiles tailored to user needs. 

Policy Makers and Licensing Authorities: 

• Embed ADAS awareness in licensing and evaluation authorities with guidance and professional training. 
• Provide clear consumer information at vehicle sales. 
• Support equitable access via schemes such as the Motability in the UK or similar. 

The Motability scheme is a UK programme that allows eligible disabled people to use a qualifying mobility allowance to lease a car, wheelchair accessible Vehicle, Mobility Scooter, or powered wheelchair, with insurance, servicing, maintenance, and breakdown cover included; some vehicles can also be adapted to meet individual needs. Eligibility is based on receiving a qualifying mobility benefit with at least 12 months remaining, making the scheme an important policy mechanism for improving equitable access to mobility and appropriate vehicle adaptations (Motability, 2026)

Researchers and Educators:

• Expand studies on ADAS use among disabled drivers. 
• Investigate long-term behavioural adaptation. 
• Foster collaboration between engineers and clinicians. 

The transition toward semi- and fully autonomous vehicles underscores the need for inclusive design and evidence-led adoption. Ensuring that ADAS supports all drivers equitably — regardless of age, health, or disability — requires coordinated efforts from technology developers, health professionals, and policymakers. Clinicians are uniquely positioned to advocate for systems that promote both safety and independence. 

Key resources for clinicians seeking deeper understanding of ADAS, driver assessment, and rehabilitation include:

• Stulce & Antin (2024). Assessing the Impact of Disability on Drivers’ Equitable Use of ADAS. 
• Wood et al. (2024). Exploring perceptions of ADAS among older drivers. 
• Biassoni et al. (2024). Systematic Review of ADAS Adoption in Older Adults. 
• Urlings et al. (2018). Screening medical professionals’ role in fitness-to-drive. 
• AAA Foundation (2017). Behavioural Adaptation to ADAS. 
• Clinician’s Guide to Assessing and Counselling Older Drivers (Safe Mobility Florida).