The impact of a dedicated lane for connected and automated vehicles on the behaviour of drivers of manual vehicles

Connected and automated vehicles (CAVs) are expected to enhance traffic efficiency by driving at shorter time headways, and traffic safety by shorter reaction times. However, one of the main concerns regarding their deployment is the mixed traffic situation, in which CAVs and manually driven vehicles (MVs) share the same road.This study investigates the behavioural adaptation of MV drivers in car-following and lane changing behaviour when they drive next to a dedicated lane (DL) for CAVs and compares that to a mixed traffic situation. The expectation is that in a mixed traffic situation, the behavioural adaptation of MV drivers is negligible due to lower exposure time and scarce platoons, while concentrating the CAVs on one dedicated lane may cause significant behavioural adaptation of MV drivers due to a higher exposure time and conspicuity of CAV platoons.Fifty-one participants were asked to drive an MV on a 3-lane motorway in three different traffic scenarios, in a fixed-base driving simulator: (1) Base, only MVs were present in traffic, (2) Mixed, platoons of 2–3 CAVs driving on any lane and mixed with MVs, (3) DL, platoons of 2–3 CAVs driving only on a DL. The DL was recognizable by road signs and a buffer demarcation which separated the DL from the other lanes. A moderate penetration rate of 43% was assumed for CAVs.During the drives, the car following headways and the accepted merging gaps by participants were collected and used for comparisons of driving behaviour in different scenarios.Based on the results, we conclude that there is no significant difference in the driving behaviour between Base and Mixed scenarios at tested penetration rate, confirming our research expectation. However, in DL scenario, MV drivers drove closer to their leaders specially when driving on the middle lane next to the platoons and accepted shorter gaps (up to 12.7% shorter at on-ramps) in lane changing manoeuvres. Dedicating a lane to CAVs increases the density of CAV platoons on one lane and consequently their conspicuity becomes higher. As a result, MV drivers are influenced by CAV platoons on a DL and imitate their behaviour.The literature suggests that dedicating a lane to CAVs improves the traffic efficiency by providing more possibilities for platooning. This study shows that implementing such a solution will affect the driving behaviour of human drivers. This should be taken into consideration when evaluating the impacts of dedicated lanes on traffic efficiency and traffic safety.     

A driving simulator study to assess driver performance during a car-following maneuver after switching from automated control to manual control

A review of the literature on autonomous vehicles has shown that they offer several benefits, such as reducing traffic congestion and emissions, and improving transport accessibility. Until the highest level of automation is achieved, humans will remain an important integral of the driving cycle, which necessitates to fully understand their role in automated driving. A difficult research topic involves an understanding of whether a period of automated driving is likely to reduce driver fatigue rather than increase the risk of distraction, particularly when drivers are involved in a secondary task while driving. The main aim of this research comprises assessing the effects of an automation period on drivers, in terms of driving performance and safety implications. A specific focus is set on the car-following maneuver. A driving simulator experiment has been designed for this purpose. In particular, each participant was requested to submit to a virtual scenario twice, with level-three driving automation: one drive consisting of Full Manual Control Mode (FM); the other comprising an Automated Control Mode (AM) activated in the midst of the scenario. During the automation mode, the drivers were asked to watch a movie on a tablet inside the vehicle. When the drivers had to take control of the vehicle, two car-following maneuvers were planned, by simulating a slow-moving vehicle in the right lane in the meanwhile a platoon of vehicles in the overtaking lane discouraged the passing maneuver. Various driving performances (speeds, accelerations, etc.) and surrogate safety measures (PET and TTC) were collected and analysed, focusing on car-following maneuvers. The overall results indicated a more dangerous behavior of drivers who were previously subjected to driving automation; the percentage of drivers who did not apply the brakes and headed into the overtaking lane despite the presence of a platoon of fast-moving vehicles with unsafe gaps between them was higher in AM drive than in FM drive. Conversely, for drivers who preferred to brake, it was noted that those who had already experienced automated driving, adopted a more careful behavior during the braking maneuver to avoid a collision. Finally, with regard to drivers who had decided to overtake the braking vehicle, it should be noted that drivers who had already experienced automated driving did not change their behavior whilst overtaking the stopped lead vehicle.     

Investigating the effectiveness of perceptual treatments on a crest vertical curve: A driving simulator study

Rural roads are characterized by a high percentage of run-off-the-road accidents and head-on collisions, mainly caused by inappropriate speeds and failure to maintain a proper lateral position along the roadway alignment. Among several road safety treatments, low-cost perceptual measures are considered an effective tool, as they generally increase the risk perceived by drivers, or even alter the drivers’ speed perception, and consequently tempting them to decrease their speeds. Their effectiveness has been widely recognized in a number of studies, especially with respect to road intersections and curves.The overall aim of this study is to investigate the effects of different perceptual treatments on driving speed, along a crest vertical curve of an existing two-lane rural road, in order to identify the most effective measure to reduce speed and define its subsequent implementation in the field. Three perceptual treatments were tested using a driving simulator: white peripheral transverse bars, red peripheral transverse bars and optical speed bars, with each one being painted along the approaching tangent to the crest vertical curve. The effects of these speed-reducing measures were investigated using a sample of forty-four participants, by comparing the driving speeds with those recorded under a baseline condition (without a treatment); these were also used to validate the driving simulator’s speed measurements with those found in the field. Moreover, subjective measures were collected, consisting of the driver’s static evaluation of the desired speed, risk perception and markings comprehension, based on screen shot pictures that represented the simulated configurations of the treatments.The findings demonstrated an overall effectiveness of the perceptual treatments, although only the red peripheral transverse bars were found to significantly reduce the driving speeds (−6 km/h). The analysis of the questionnaire yielded interesting information and demonstrated the importance of performing driving simulation tests for evaluating the effectiveness of perceptual treatments.Finally, the results confirmed the enormous potential of using driving simulators to pinpoint a number of speed-reducing measures, and consequently select the most effective one that reduces cost and promotes safety before its actual implementation in the field.     

The effects of adaptive cruise control (ACC) headway time on young-experienced drivers' overtaking tendency in a driving simulator

The preference to maintain a certain desired speed is perhaps the most prevalent explanation for why a driver of a manually driven car decides to overtake a lead vehicle. Still, the motivation for overtaking is also affected by other factors such as aggressiveness, competitiveness, or sensation-seeking caused by following another vehicle. Whether such motivational factors for overtaking play a role in partially automated driving is yet to be determined. This study had three goals: (i) to investigate whether and how a driver's tendency to overtake a lead vehicle changes when driving a vehicle equipped with an adaptive cruise control (ACC) system. (ii) To study how such tendencies change when the headway time configuration of the ACC system varies. (iii) To examine how the manipulation of the speed and speed variance of the lead vehicle affect drivers' tendencies to overtake a lead vehicle. We conducted two different experiments, where the second experiment followed the first experiment's results. In each experiment, participants drove three 10–12 min simulated drives under light traffic conditions in a driving simulator under manual and level one (L1) automation driving conditions. The automation condition included an ACC with two headway time configurations. In the first experiment, it was 1 sec and 3 secs, and in the second, it was 1 sec and 2 secs. Each drive included six passing opportunities representing three different speeds of the lead vehicle (−3 km/h, +3 km/h, +6 km/h relative to the participant), with or without speed variance. Results show that drivers tended to overtake a lead vehicle more often in manual mode than in automated driving modes. In the first experiment, ACC with a headway time of 1 sec led to more overtaking events than ACC with 3 secs headway time. In addition, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies. In the second experiment, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies only when interacting with each other and with driving configuration. When the speed of the lead vehicle was +3 km/h and included variability, more overtaking events occurred in manual mode than both automation modes. This work has shown that driving with ACC might help reduce overtaking frequencies and more considerable when the headway time is set to 3 secs.     

An evaluation of the effectiveness of countermeasures for improving the safety of dilemma zones: A driving simulator study

The main objective of this driving simulator study is to analyze the behavior of the driver at the start of the yellow signal of a signalized rural intersection and identify the most effective countermeasures for tackling the dilemma zone, namely an area on the intersection approach where vehicles at the start of the yellow phase can neither safely stop before the stop line nor cross the intersection. The following countermeasures were tested in the study on a sample of 48 drivers: green signal countdown timers, GSCT (C₁); a new pattern of vertical and horizontal warning signs (C₂); and an advanced on-board driver assistance system based on augmented reality (AR) and connected vehicle technologies (C₃). These countermeasures were tested and compared to a baseline condition (B) where no countermeasures were applied. Based on the results of this study, the C₂ and C₃ countermeasures have proven to be valid tools for reducing driver indecision when approaching signalized intersections at the start of the yellow signal. In fact, using C₂ and C₃, the length of the dilemma zone was equal to 30 m and 36 m, respectively, with a reduction of about 50%, as compared to the baseline condition (B). Moreover, a reduced number of false behaviors was recorded, as well as a greater consistency in driver decision-making behaviors. Conversely, the C₁ countermeasure did not lead to a significant improvement in the dilemma zone: an unnecessary increase in early stop rates was recorded, resulting in reduced intersection efficiency and operations.     

Driver's avoidance characteristics to hazardous situations: A driving simulator study

When analyzing the causes of an accident, it is critical to determine whether the driver could have prevented the accident. In previous studies on the reaction times of drivers, the definition and values of reaction times vary, so applying reaction time is difficult. In such analysis, the driver’s reaction time from perception is required to determine whether the driver could have prevented the accident, but past studies are difficult to utilize in accident analysis as reaction time measurements were taken after the occurrence of hazardous situations. In this study, 93 subjects from age groups ranging from 20 s to 40 s participated in an experiment inside a full-scale driving simulator, to determine reaction time values that can be practically applied to accident analysis. A total of 4 hazardous accident situations were reproduced, including driving over the centerline, pedestrian jaywalking, a vehicle cutting in, and intersection traffic signal violation. The Time-To-Collision (TTC) was 2.5 s and the driving speed was set to the common city road speed limits of 60 and 80 km/h. An eye tracker was used to determine the driver’s Saccade Latency (SL) during hazardous situations. Brake Reaction Time from Perception (BRT_P), Steer Reaction Time from Perception (SRT_P), and Driver Reaction Time from Perception (DRT_P) were derived, and the measurements were statistically analyzed to investigate differences by age group, gender, speed, and type of hazardous situation. Most participants were found to avoid collisions by braking first rather than steering for the presented hazardous situations, except for the cutting in situation. Also, to determine a reaction time that would cover most drivers, the 85th percentile of DRT_P was calculated. The 85th percentile of DRT_P was in the range of 0.550 – 0.800 s. Specifically for each hazardous situation, it was 0.650 s for driving over the centerline, 0.800 s for the pedestrian jaywalking, 0.660 s for cutting in, and 0.550 s for the intersection traffic signal violation. For all 4 hazardous situations combined, the 85th percentile of DRT_P was 0.646 s. The findings can be utilized to determine the driver’s likelihood of avoiding accidents when faced with similar hazardous situations.     

Can infrastructure improvements mitigate unsafe traffic safety culture: A driving simulator study exploring cross cultural differences

This paper presents the results of a cross-cultural study to investigate the influence of traffic safety culture and infrastructure improvements on driver behaviour. To achieve this, the driving style of UK drivers was compared with that of Nigerians with and without experience of driving in the UK. A driving simulator experiment compared the actual driving style of these three groups of drivers in different safety critical scenarios. The simulated road environment varied depending on how much infrastructure was provided (low or high infrastructure). In addition, the Driver Behaviour Questionnaire was used to collect self-reported data on violations, errors and lapses. It was hypothesised that Nigerian drivers with no experience of driving in a UK road system would report and engage in more unsafe driving behaviour compared to the other two groups, and that increasing infrastructure would have little positive benefit. Overall, the results supported these hypotheses, indicating that the behaviours of drivers are interpretable in relation to their traffic safety culture, compared to changes in their driving environment.     

Transition patterns of driving style from a traditional driving environment to a connected vehicle environment: A case of an extra-long tunnel road

To provide a better understanding of individual driver’s driving style classification in a traditional and a CV environment, spatiotemporal characteristics of vehicle trajectories on a road tunnel were extracted through a driving simulator-based experiment. Speed, acceleration, and rate of acceleration changes are selected as clustering indexes. The dynamic time warping and k-means clustering were adopted to classify participants into different risk level groups. To assess the driver behavior benefits in a CV environment, an indicator BI (behavior indicator, BI) was defined based on the standard deviation of speed, the standard deviation of acceleration, and the standard deviation of the rate of acceleration change. Then, the index BI of each driver was calculated. Furthermore, this paper explored driving style classification, not in terms of traditional driving environment, but rather the transition patterns from a traditional driving environment to a CV environment. The results revealed that inside a long tunnel, 80 % of drivers benefited from a CV environment. Moreover, drivers might need training before using a CV system, especially female drivers who have low driving mileage. In addition, the results showed that the driving style of 69 % of the drivers’ transferred from a high risk-level to a low risk-level when driving in a CV environment. The study results can be expected to improve driving training education programs and also to provide a valuable reference for developing individual in-vehicle human-machine interface projects and other proactive safety countermeasures.     

A study of the compliance level of connected vehicle warning information in a fog warning system based on a driving simulation

The accidents in the freeway are frequent and more serious on foggy days. Connected vehicle (CV) technology as a new technology can inform drivers of fog conditions in advance so the drivers can adjust their driving behaviors through Human Machine Interface (HMI) and Dynamic Message Sign (DMS) in the fog warning system. The level of driver's compliance with a fog warning system is the key to assessing the effectiveness of the fog warning system. To evaluate the compliance level of fog warning system, the study established a CV system testing platform based on driving simulator, and analyzed the changes in driving behavior and influencing factors for drivers under three different visibility conditions (No fog, light fog and heavy fog) based on the platform, finally, comprehensive evaluation of the optimal fog warning system under different foggy conditions based on the compliance level were made. Research indicators are divided into three aspects: 1) the response degree, including the mean speed, the minimum speed in the fog zone, the difference of the speeds when entering and leaving the fog zone, the proportion of speed following, and the speed reduction proportion prompt; 2) the response start time, which is the time to start slowing down to the speed limit; and 3) the response time duration, namely, the time in which the speed limit is followed. The results show that the response degree of the driver to the fog warning system is high, the fog warning system can effectively reduce the driving speed of the drivers and improve the speed following proportion of the drivers, the deceleration ratio of the driver at each warning point is relatively high, and the influencing factors of various indicators are complex but are mostly related to visibility and technical level. Comprehensive evaluation results show that the warning mode of the combined HMI and DMS has the highest level of compliance under light fog conditions, and when fog concentration increases, compliance level of fog warning system with HMI only is higher than others. The study establishes a reference platform for CV system and provides methods and index system for the compliance level of CV research.     

Exploring the effects of the location of the lane-end sign and traffic volume on multistage lane-changing behaviors in work zone areas: A driving simulator-based study

The lane-changing behavior in work zone areas has special features than a regular lane change as the former is usually compulsively motivated involving complicated cognitive processes with drivers’ perception of work-zone control devices. Toward this end, this study conducted a driving simulator-based experiment to understand the effects of lane-end sign distance and traffic volume on driving behaviors. A conceptual model was also proposed to partition the whole lane-changing process into three stages, i.e. the perception, preparation and action stages, reflecting different cognitive and manipulative activities of drivers. In addition to the lane-end sign distance and traffic volume, gender and profession of drivers were adopted as covariates. In this experiment, a complete combination of lane-end sign distance and traffic volume served as treatments. The results verify the impacts of those factors on driving behaviors in and across different stages. For example, the location of the lane-end sign had a profound influence on drivers' perception of the imminent work-zone situation, but the influence continued to diminish in the following two stages. On the other hand, male or taxi drivers tended to act earlier than female or regular drivers respectively, for all the three stages. According to the analysis, several practical implications were also provided. In specific, the lane-end sign is recommended to be installed 500 m upstream to the lane dropping point of work zones. It is a pioneer study toward investigating multistage driving behaviors in work zone areas, which is expected to provide references and guidance for the design of traffic control devices and other driving simulator-based studies.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

Driving and gaze behavior while texting when the smartphone is placed in a mount: A simulator study

The aim of this study was to investigate how texting when the smartphone in a mount next to the wheel, negatively affects safe driving behavior and gaze behavior. In most countries hand-held phone use while driving is prohibited. However, when texting is not explicitly forbidden and only hand-held use is not allowed, drivers can still legally operate their smartphone with their fingers when it is placed in a mount which is attached to the dashboard or the windscreen. The effects on driving and gaze behavior of ‘dashboard-mount’ texting have hardly been investigated. Twenty-seven participants drove three short identical drives in a simulator while their driving behavior and gaze behavior was measured. This was a drive in which participants did not text (baseline drive), a drive while they texted with a smartphone in one hand (hand-held drive), and a drive in which they texted while the phone was placed in a dashboard-mount (dashboard-mount drive). Participants looked significantly more often at the smartphone during the dashboard-mount than during the hand-held drive. Total dwell time at the smartphone was significantly longer during the dashboard-mount than during the hand-held drive. There were no significant differences between the two texting drives in the number of glances longer than 2 s, the longest glance of each participant, and mean fixation duration at the smartphone. Total dwell time in the mirrors was significantly shorter during the two texting drives than in the baseline drive but did not differ between the two texting drives. The drivers showed poorer lateral control and varied their speed more in the two texting drives than in the baseline drive. They also drove significantly slower in the two texting drives than in the baseline drive. Finally, subjective workload was much higher in the two texting drives than in the baseline drive. The results indicate that dashboard-mount texting deteriorates the safe execution of the driving task to at least the same extend as hand-held texting does.     

The impact of cognitive functioning on driving performance of older persons in comparison to younger age groups: A systematic review

Older drivers are at a severely higher risk for motor vehicle crash involvement. Due to the global aging of the population, this increased crash risk has a significant impact on society, as well as on an older individual’s quality of life. For this reason, there is a need for understanding how normal age-related changes in cognition and underlying brain dynamics impact driving performance to identify the functional and neurophysiological biomarkers that could be used to design strategies to preserve or improve safe driving behavior in older persons. This review provides an overview of the literature on age-related changes in cognitive functioning and brain dynamics that impact driving simulator performance of healthy persons. A systematic literature search spanning the last ten years was conducted, resulting in 22 eligible studies. Results indicated that various aspects of cognition, most importantly executive function, complex attention, and dual tasking, were associated with driving performance, irrespective of age. However, there was a distinct age-related decline in cognitive and driving performance. Older persons had a more variable, less consistent driving simulator performance, such as more variable speed adaptation or less consistent lane keeping behavior. Only a limited number of studies evaluated the underlying brain dynamics in driving performance. Therefore, future studies should focus on implementing neuroimaging techniques to further unravel the neural correlates of driving performance.     

Eye movements predict driver reaction time to takeover request in automated driving: A real-vehicle study

For automated driving at SAE level 3 or lower, driver performance in responding to takeover requests (TORs) is decisive in providing system safety. A driver state monitoring system that can predict a driver’s performance in a TOR event will facilitate a safer control transition from vehicle to driver. This experimental study investigated whether driver eye-movement measured before a TOR can predict driving performance in a subsequent TOR event. We recruited participants (N = 36) to obtain realistic results in a real-vehicle study. In the experiment, drivers rode in an automated vehicle on a test track for about 32 min, and a critical TOR event occurred at the end of the drive. Eye movements were measured by a camera-based driver monitoring system, and five measures were extracted from the last 2-min epoch prior to the TOR event. The correlations between each eye-movement measure and driver reaction time were examined, and a multiple regression model was built using a stepwise procedure. The results showed that longer reaction time could be significantly predicted by a smaller number of large saccades, a greater number of medium saccades, and lower saccadic velocity. The implications of these relationships are consistent with previous studies. The present real-vehicle study can provide insights to the automotive industry in the search for a safer and more flexible interface between the automated vehicle and the driver.     

Effects of environmental,vehicle and human factors on comfort in partially automated driving: A scenario-based study

Although it is key to improving acceptability, there is sparse scientific literature on the experience of humans as passengers in partially automated cars. The present study therefore investigated the influence of road type, weather conditions, traffic congestion level, vehicle speed, and human factors (e.g., trust in automated cars) on passenger comfort in an automated car classified as Level 3 according to the Society of Automotive Engineers (SAE). Participants were exposed to scenarios in which a character is driven by an SAE Level 3 automated car in different combinations of conditions (e.g., highway × heavy rain × very congested traffic × vehicle following prescribed speed). They were asked to rate their perceived comfort as if they were the protagonist. Results showed that comfort was negatively affected by driving in downtown (vs. highway), heavy rain, and congested traffic. Interaction analyses showed that reducing the speed of the vehicle improved comfort in these two last conditions, considered either individually or in combination. Cluster analysis revealed four profiles: trusting in automation, averse to speed reduction, risk averse, and mistrusting automation. These profiles were all influenced differently by the driving conditions, and corresponded to varying levels of trust in automated cars. This study suggests that optimizing comfort in automated cars should take account of both driving conditions and human profiles.     

Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence

Adaptive cruise control (ACC), a driver assistance system that controls longitudinal motion, has been introduced in consumer cars in 1995. A next milestone is highly automated driving (HAD), a system that automates both longitudinal and lateral motion. We investigated the effects of ACC and HAD on drivers’ workload and situation awareness through a meta-analysis and narrative review of simulator and on-road studies. Based on a total of 32 studies, the unweighted mean self-reported workload was 43.5% for manual driving, 38.6% for ACC driving, and 22.7% for HAD (0% = minimum, 100 = maximum on the NASA Task Load Index or Rating Scale Mental Effort). Based on 12 studies, the number of tasks completed on an in-vehicle display relative to manual driving (100%) was 112% for ACC and 261% for HAD. Drivers of a highly automated car, and to a lesser extent ACC drivers, are likely to pick up tasks that are unrelated to driving. Both ACC and HAD can result in improved situation awareness compared to manual driving if drivers are motivated or instructed to detect objects in the environment. However, if drivers are engaged in non-driving tasks, situation awareness deteriorates for ACC and HAD compared to manual driving. The results of this review are consistent with the hypothesis that, from a Human Factors perspective, HAD is markedly different from ACC driving, because the driver of a highly automated car has the possibility, for better or worse, to divert attention to secondary tasks, whereas an ACC driver still has to attend to the roadway.     

Adapting to the surface: A comparison of handwriting measures when writing on a tablet computer and on paper

Our study addresses the following research questions: Are there differences between handwriting movements on paper and on a tablet computer? Can experienced writers, such as most adults, adapt their graphomotor execution during writing to a rather unfamiliar surface for instance a tablet computer?We examined the handwriting performance of adults in three tasks with different complexity: (a) graphomotor abilities, (b) visuomotor abilities and (c) handwriting. Each participant performed each task twice, once on paper and once on a tablet computer with a pen.We tested 25 participants by measuring their writing duration, in air time, number of pen lifts, writing velocity and number of inversions in velocity. The data were analyzed using linear mixed-effects modeling with repeated measures.Our results reveal differences between writing on paper and on a tablet computer which were partly task-dependent. Our findings also show that participants were able to adapt their graphomotor execution to the smoother surface of the tablet computer during the tasks.     

A qualitative study of adaptation to the euro in the Republic of Ireland: I. attitudes,the ‘euro illusion’ and the perception of prices

This is the first of two reports of a study using semi‐structured, in‐depth interviews to explore the current and recollected experiences of Irish people for the period before, during, and after the introduction of euro notes and coins (1 January 2002). Twenty‐four adults, 12 males and 12 females, covering a range of ages and educational attainment, were interviewed between October 2002 and February 2003. We found that most had welcomed the new currency initially, though some had felt less positive about it, whilst current experiences were more mixed. People's explanations for their attitudes seemed to focus more on the economic and practical aspects of currency change rather than symbolic meanings. Initially, most had experienced a euro illusion (prices in euros seeming to be more expensive than in punts). However, for most, the strength of the illusion appeared to diminish quite quickly. Nonetheless, current prices were believed to be higher, and many respondents attributed this either directly or indirectly to the change of currency. Although independent evidence found that there had been price increases in certain sectors, it was concluded that perceived price rises were, in part, illusory, and driven by expectations and selective price monitoring. Copyright © 2005 John Wiley & Sons, Ltd.     

On-to-off-path gaze shift cancellations lead to gaze concentration in cognitively loaded car drivers: A simulator study exploring gaze patterns in relation to a cognitive task and the traffic environment

Appropriate visual behaviour is necessary for safe driving. Many previous studies have found that when performing non-visual cognitive tasks, drivers typically display an increased amount of on-path glances, along with a deteriorated visual scanning pattern towards potential hazards at locations outside their future travel path (off-path locations). This is often referred to as a gaze concentration effect. However, what has not been explored is more precisely how and when gaze concentration arises in relation to the cognitive task, and to what extent the timing of glances towards traffic-situation relevant off-path locations is affected. To investigate these specific topics, a driving simulator study was carried out. Car drivers’ visual behaviour during execution of a cognitive task (n-back) was studied during two traffic scenarios; one when driving through an intersection and one when passing a hidden exit. Aside from the expected gaze concentration effect, several novel findings that may explain this effect were observed. It was found that gaze shifts from an on-path to an off-path location were inhibited during increased cognitive load. However, gaze shifts in the other direction, that is, from an off-path to an on-path location, remained unaffected. This resulted in on-path glances increasing in duration, while off-path glances decreased in number. Furthermore, the inhibited off-path glances were typically not compensated for later. That is, off-path glances were cancelled, not delayed. This was the case both in relation to the cognitive task (near-term) and the traffic environment (far-term). There was thus a general reduction in the number of glances towards situationally relevant off-path locations, but the timing of the remaining glances was unaffected. These findings provide a deeper understanding of the mechanism behind gaze concentration and can contribute to both understanding and prediction of safety relevant effects of cognitive load in car drivers.