Ashleigh J. Filtness

Modern train cabs have multiple technological systems aiming to minimise the risk of an incident. This qualitative study of train driver instructors investigated: what in-cab systems and warnings are perceived to be the most helpful for train drivers? And, what themes best describe the relationship between train driving and in-cab technology?. Five online focus groups with train driver instructors (n = 19) involved participants undertaking a two-part prioritisation exercise considering the current technologies and safety features in the train cab and ranking the three they considered to be most helpful and most unhelpful. Open discussion about the importance of the technologies in supporting safety, the driver instructors’ opinions about using the technologies, and any safety gaps followed. The safety systems considered most helpful were the AWS (Automatic Warning System), Vigilance, DRA (Driver Reminder Appliance), and TPWS (Train Protection Warning System). Three key themes were identified. “The patchwork cab”, highlights the participants’ experience of using the numerous and sometimes overlapping in function in-cab technologies; “eyes, ears, and staying aware in the cab”, highlights challenges around distraction; and “balancing alerts and silence” highlights workload dynamics and task engagement. Additions of new safety features while retaining legacy systems has resulted in a patchwork like cab design that may not effectively support the driver in their work and decision making. The management of acknowledged distractions has become normalised and is accepted rather than designed out of the cab. In-cab technology has an important role to play in safe vehicle operations as humans and machines become essential team-mates. However, saturation point has been reached for this patchwork approach to in-cab technology, and it will be a challenge to the industry to change this method and redesign systems rather than adding to them.

Passenger transport is frequently associated with high-fatality crashes, highlighting the need for enhanced risk management. However, most risk-assessment approaches rely on cross-sectional data and fail to capture the cumulative nature of unsafe driving patterns. This study developed a static Bayesian network and a dynamic Bayesian network using violation and crash records from 9,894 coach drivers in Shanghai (2021–2024) to examine causal factors and cumulative crash risk. Overall, 14.75% of drivers were involved in one crash and 6.64% were involved in multiple crashes, while 24.83% committed one violation and 53.95% committed repeated violations. Violations were classified into five categories covering unsafe conditions and behavioral faults. A static Bayesian network identified a key causal pathway: License type/Company size → Passenger-transport violations → Roadway maneuver violations → At-fault crash. Sensitivity analysis showed large variability in crash probability (0.063–0.152), with no violations and consistently compliant operations as the strongest protective factors. Granger causality analysis identified habitual violation patterns ( p <0.05), including improper lighting use and poor speed control, which were associated with increased subsequent crash risk. These findings informed an empirical dynamic Bayesian network, which achieved strong performance (Mean Absolute Error = 1.56%, Mean Relative Error = 19.02%) and over 80% predictive consistency. Overall, the study provides a behaviorally interpretable and temporally grounded approach for identifying high-risk drivers, enabling dynamic risk classification and supporting proactive safety-management strategies in coach-transport operations.

Driver sleepiness contributes to a substantial proportion of road crashes. Drivers experiencing sleepiness are advised to take a break and have a caffeinated drink followed by a short nap (caffeine nap). However, previous research advocating this countermeasure has not considered participants with obstructive sleep apnoea (OSA), the most prevalent sleep disorder. Across three studies the effectiveness of caffeine, nap opportunity and caffeine nap countermeasures on subjective sleepiness (KSS), objective sleepiness (Alpha and Theta activity) and driving performance (standard deviation of lateral position and out-of-lane events) are considered. Twenty-one CPAP treated OSA participants (mean age = 59 years) engaged with a protocol of six laboratory visits: one after a normal night’s CPAP-treated sleep and five after sleep restriction (4 h CPAP-treated sleep), driving a monotonous simulated scenario before and after a countermeasure. Results showed that two cans of coffee (255 mg caffeine) mitigated driver sleepiness more than one can (127.5 mg) and little benefit to 30 min compared with 15 min nap opportunity. An optimised caffeine nap of two coffees followed by a 15 min nap opportunity provides some temporary benefit, but for OSA drivers a caffeine nap offers little practical improvement compared to two coffees alone. All countermeasures are temporary and cannot replace a good night of sleep before driving.

This paper presents a focused look at findings related to driver fatigue from Use Case A (UCA) of EU project PANACEA (grant agreement number 953426). UCA considers safety drivers of autonomous shuttles. For safety and regulation reasons all shuttles have a driver present ready to intervene if needed. In practice, this means that the safety driver is responsible for ensuring the safety of both passengers and surrounding road users. 8 shuttle safety drivers (100% of those available) participated. Subjective driver sleepiness was reported daily at the start and end of each shift using the Karolinska Sleepiness Scale. Potential risk for driver sleepiness was calculated using the Bordeaux Sleepiness Scale (BOSS). Overall, sleepiness was a rare experience (mean KSS start shift = 3, mean KSS end shift = 3.1). However, those identified as potentially at-risk using BOSS had some experiences of sleepiness (KSS = 7) on some shifts. The PANACEA system uses input from sensors in the vehicle, workplace depot and on the driver, creating a holistic monitoring and assessment system. This detects professional drivers who are not fit to drive and supports them and their employers to manage the situation and adopt preventive measures.

The i-DREAMS project introduced the concept of a ‘Safety Tolerance Zone’, i.e., a context-aware safety envelope designed to assist drivers in maintaining self-regulated control within the boundaries of safe operations. Using an ecosystem of sensors, i-DREAMS technology continuously monitors factors determining driving task complexity and available coping capacity and calculates risk levels in real-time. Based on this information, both real-time and post-trip interventions are tailored to keep drivers from getting too close to the boundaries of unsafe driving. Real-time interventions are provided via in-vehicle display, while post-trip interventions are delivered via a smartphone app (and web-dashboard) with provisions for gamification. This study focuses on post-trip interventions, specifically user engagement with the i-DREAMS app. Data from 49 Belgian and 51 UK car drivers over a 10-week period showed a steady decline in drivers’ engagement following the first day of app activation. However, when gamification features were activated, user interaction increased, suggesting they re-engaged users. UK drivers exhibited higher engagement than Belgians. Trips, scores and goals were the most visited features in both countries, while the leaderboard was popular among UK drivers only. Analysis showed a dose-response relationship, with intensive app users demonstrating better improvement in driving performance than less frequent users.

This paper presents a new conceptual framework, and stepwise approach to populate it, for informing countermeasure development to support fitness-to-drive for professional drivers. Professional drivers are vital to the transport network; however, the job is demanding and drivers are vulnerable to impairments which may impact safe driving. Countermeasures are any action or activity that mitigates the impact or frequency of occurrence of driver impairment. The framework proposes countermeasures to be delivered across three time points: Operational (during shift), Tactical (immediately after shift) and Strategic (outside of on-shift) and at multiple system levels, e.g., driver, manager, enforcement etc. The framework was successfully pilot tested with three different professional driver use cases: autonomous shuttles, taxi, and garbage truck drivers. This structured approach to countermeasure design offers potential to improve driver health and enhance road safety. The work was conducted within PANACEA, an EU project, grant agreement number 953426.

To investigate differences in the safety behaviours of distracted and non-distracted pedestrians crossing roads, an unobtrusive observational study was conducted in Leicestershire, UK. Video recordings were taken of 1409 pedestrians crossing roads at controlled and uncontrolled crossing sites, both on a university campus and in urbanised town centre locations. On average, 42% of pedestrians were visibly distracted while crossing, and distracted pedestrians demonstrated significantly fewer safety behaviours than non-distracted pedestrians. They generally took longer to cross the road and made fewer looks towards the traffic environment, particularly at controlled crossings. Of all distraction activities, talking to another pedestrian had the most negative impact on safety behaviours. The findings highlight areas requiring further investigation, including distraction behaviours such as engaging with other pedestrians and supervising children. The results also identify that controlled crossings may benefit from targeted interventions to improve pedestrian safety.

While a vehicle operator falling asleep at the controls is the most obvious symptom of fatigue in transportation operations, less extreme and apparent fatigue levels are reliably associated with performance impairments in, for example, attention, information processing, memory, and situation awareness. Compared to in other industries, fatigue in transportation is made more likely by challenges to the body's circadian rhythm caused by shiftwork and travel across time zones. While experiencing fatigue is a normal physiological and behavioral state, for drivers, pilots, mariners, and other vehicle operators, experiencing fatigue while operating a vehicle can have catastrophic consequences. Fatigue can also contribute to heightened, though less-direct, risk for those who support transport operations, such as shift schedulers, supervisors, and managers. This discussion panel will explore high risk and important human factors challenges to fatigue management facing transportation workers and their industries today, and some practical, and proven, ways to manage them.