Effects of route guidance variable message signs (VMS) on driver behaviour

Effects of route guidance Variable Message Signs (VMS) on speed and route choice were investigated in a field study on two sites on motorways. Two VMS were used in the study, which displayed information about a closed road section downstream on the motorways and recommendations for alternative routes. Route choice, speed and braking behaviour were compared between vehicles approaching the VMS while they displayed messages and while they were left blank without message. There was high compliance with the messages on the VMS. About every fifth vehicle changed route choice according to the recommendation, and almost none drove as far as the closed road section. Speed measurements of 3342 vehicles showed large speed reductions, and video observations showed that large proportions of vehicles braked while approaching the VMS. The speed reductions and braking manoeuvres can partly be attributed to attention overload or distraction due to the information on the VMS. However, a proportion of the speed reductions was due to chain reactions where one vehicle braked and forced the following vehicles to brake or change lanes in order to avoid collisions. Safety problems may result directly from distraction, or indirectly from the reactions of the drivers to the distraction.     

Effects of hazard exposure and roadway complexity on young and older driver situation awareness and performance

Few previous studies of driver situation awareness (SA) have focused on behavior in hazard negotiation. The objective of this research was to assess the effect of hazard exposure on driver SA and interactions with age and roadway complexity. Ten young (18–25 yrs) and ten older (65–81 yrs) participants drove in a simulator under two levels of environment complexity (simple – rural vs. complex – city) with two types of hazard exposure (static vs. dynamic). Situation awareness was measured using real-time probes posed by a confederate passenger. Driving performance was assessed in terms of lane maintenance and speed control. Results revealed hazards to cause degradations in high level of driver SA and speed control or to trigger adaptation, and vulnerability to hazard type was dependent on driver age. Older drivers exhibited greater speed reduction in response to dynamic hazards; whereas, young driver maintained higher speed, as compared to normal driving, when confronted with static hazards. In addition, increased roadway environment complexity compounded decrements in performance caused by hazard exposure. These findings are applicable to modeling driver behavior and SA under hazardous conditions and may support the design of new in-vehicle assistive technologies for hazard avoidance.     

Drivers’ attitudes toward imperfect distraction mitigation strategies

Studies were conducted to assess driver acceptance of and trust in distraction mitigation strategies. Previous studies have shown that in-vehicle tasks undermine driver safety, and that there is a need for strategies to reduce the effects of in-vehicle distractions. Trust and acceptance of such strategies strongly influence their effectiveness. Different strategies intended to reduce distraction were categorized in a taxonomy. Focus groups were conducted to help refine this taxonomy and explore driver acceptance issues related to these strategies. A driving simulator experiment was then conducted using two of the strategies: an advising strategy that warns drivers of potential dangers and a locking strategy that prevents the driver from continuing a distracting task. These strategies were presented to 16 middle-aged and 12 older drivers in two modes (auditory, visual) with two levels of adaptation (true, false). Older drivers accepted and trusted the strategies more than middle-aged drivers. Regardless of age, all drivers preferred strategies that provided alerts in a visual mode rather than an auditory mode. When the system falsely adapted to the road situation, trust in the strategies declined. The findings show that display modality has a strong effect on driver acceptance and trust, and that older drivers are more trusting and accepting of distraction mitigation technology even when it operates imperfectly.     

A driving simulation study to investigate the information threshold of graphical variable message signs based on visual perception characteristics of drivers

Graphical variable message signs (VMSs) are infrastructure-based advanced traveler information systems widely used to provide drivers with real-time traffic condition information about a road section or area. However, there is a lack of research on the suitable volume of information to be shown on graphical VMSs. In practice, an overload of VMS information commonly exists, especially on China’s highways. Building on our earlier findings obtained through surveys and static cognitive experiments, this study introduces the use of dynamic simulation experiments to assess the influence of the volume of information (i.e., number of roads displayed) on graphical VMSs from the perspective of drivers’ visual perception characteristics. Thirty-two drivers participated in the driving simulation experiment and questionnaires. Five indexes, including legibility speed, legibility distance, legibility time, comprehension accuracy, and driver subjective scoring, were thoroughly analyzed to evaluate their relationships to different volumes of information (i.e., four, five, and six roads shown on a VMS). The results show that the legibility distance notably decreased with increasing volumes of information. The comprehension accuracy decreased significantly when the number of roads shown increased to six. The legibility speed, legibility time, and subjective scoring also deteriorated as the number of roads displayed on the VMS increased. The index scores were evaluated, in combination with the data of the drivers’ subjective scoring, data-based statistical analyses, and comprehensive evaluations using the TOPSIS method, to recommend that five is the recommended maximum number of roads to be shown on a graphical VMS. The results of this study support the goal of providing understandable and effective messages for drivers by addressing issues relating to how much information should be displayed on a VMS. These findings provide a basis for policy development to ensure consistent and practical designs of graphical VMSs on highways.     

The effect of in-vehicle warning systems on speed compliance in work zones

The purpose of this research was to evaluate the effectiveness of augmented in-vehicle speed warnings on driver behavior in work zones. The influence of three device configurations were examined as the drivers entered a work zone which was presented in a simulated driving environment. The first configuration was a control condition which used only traditional signage. The second condition had the addition of a visual in-vehicle warning while the final condition had the addition of an auditory in-vehicle warning. Results indicated that adding in-vehicle warnings did affect driver compliance to the work zone speed limit. Participants in the audio warning condition responded more quickly to the warning than those in the visual condition. Both augmented warning configurations differed significantly and were each respectively different from the drivers in the control condition. Based on these results we suggest a combination of in-vehicle warnings. Upon entry of the work zone we suggest a combined audio and visual warning message. However, after the initial entry phase, a visual warning message shows greater promise for the on-going modulation of driver speed transit.     

The impact of an in-vehicle display on glance distribution in partially automated driving in an on-road experiment

One of the major challenges of designing an HMI for partially automated vehicles is the trade-off between a sufficient level of system information and avoidance of distracting the driver. This study aimed to investigate drivers’ glance behavior as an indicator of distraction when vehicle guidance is partially automated. Therefore, an on-road experiment was conducted comparing two versions of an in-vehicle display (during partially automated driving) and no display (during manual driving) on a heavy congested highway segment. The distribution of drivers’ total glance durations on the HMI showed that visual attention was shifted away from monitoring the central road scene towards looking at the in-vehicle display to a considerable extent. However, an analysis of the distribution of single glance durations supports the view that using partial automation and a respective HMI does not lead to a critical increase in distraction. Driving with a simplified version of the HMI had the potential to reduce glance duration on and thus potential distraction of the in-vehicle display.     

The impact of smart driving aids on driving performance and driver distraction

In-vehicle information systems (IVIS) have been shown to increase driver workload and cause distraction, both of which are causal factors for accidents. This simulator study evaluates the impact that two prototype ergonomic designs for a smart driving aid have on workload, distraction and driving performance. Scenario complexity was also manipulated as an independent variable. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely affect driver distraction, while also having the positive effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs. The findings are relevant to the development and implementation of smart driving interface designs in the future.     

Effects of variable message signs for slippery road conditions on driving speed and headways

This field study investigated the effects of two variable message signs (VMS) on driver behaviour. Specifically, the signs were a warning sign for slippery road conditions and a minimum headway sign. The study was performed as a before-and-after experiment at three test sites in Finland with an after period covering two winter seasons. The results showed that the slippery road condition sign reduced the mean speed on slippery roads by 1–2 km/h in addition to the decrease caused by the adverse road conditions. The minimum headway sign decreased the proportion of headways shorter than 1.5 s for cars in car-following situations, in addition to a speed reduction of 1 km/h. The effects were somewhat smaller during the second winter than the first.     

Analysis of vehicle-based lateral performance measures during distracted driving due to phone use

Distracted driving due to mobile phone use has been identified as a major contributor to accidents; therefore, it is required to develop ways for detecting driver distraction due to phone use. Though prior literature has documented various visual behavioural and physiological techniques to identify driver distraction, comparatively little is known about vehicle based performance features which can identify driver’s distracted state during phone conversation and texting while driving. Therefore, this study examined the effects of simple conversation, complex conversation, simple texting and complex texting tasks on vehicle based performance parameters such as standard deviation of lane positioning, number of lane excursions, mean and standard deviation of lateral acceleration, mean and standard deviation of steering wheel angle and steering reversal rates (for 1°, 5° and 10° angle differences). All these performance measures were collected for 100 licensed drivers, belonging to three age groups (young, mid-age and old age), with the help of a driving simulator. Effects of all the phone use conditions and driver demographics (age, gender and phone use habits) on the measures were analysed by repeated measures ANOVA tests. Results showed that 1°, 5° SRRs are able to identify all the distracted conditions except for simple conversation; while, 10° SSR can detect all the distracted conditions (including simple conversation). The results suggest that 10° SRR can be included in intelligent in-vehicle devices in order to detect distraction and alert drivers of their distracted state. This can prevent mobile phone use during driving and therefore can help in reducing the road accidents due to mobile phone distractions.     

Driver glance behavior towards displayed images on in-vehicle information systems under real driving conditions

Intelligent vehicle technologies like driver assistance systems and in-vehicle information systems, enhance convenience of the driving experience for drivers and passengers. At the same time, these systems may increase driver distraction and workload. Guidelines developed for this purpose include principles, methods, and assessments which are widely agreed upon, with some being singled out for a particular recommendation or requirement. Especially the display of graphical or photographic images are generally assumed to distract the driver from safely operating the vehicle and should be blocked during driving under all circumstances (so called per se lock outs). This study investigates the effect of displaying graphical and photographical images during driving on driveŕs glance behavior during real-world driving. Findings presented in this paper provide empirical evidence for the unobtrusiveness of these stimuli: Participants didn’t exhibit longer glance durations towards in-vehicle information systems, nor a deterioration of driver distraction parameters such as total eyes off road time and long glance proportion when being compared to driving without displaying any photographic images.     

How drivers adapt their behaviour to changes in task complexity: The role of secondary task demands and road environment factors

The present study investigates the impact of different sources of task complexity such as driving demands and secondary task demands on driver behaviour. Although much research has been dedicated to understanding the impact of secondary task demands or specific road traffic environments on driving performance, there is little information on how drivers adapt their behaviour to their combined presence. This paper aims to describe driver behaviour while negotiating different sources of task complexity, including mobile phone use while driving (i.e., calling and texting) and different road environments (i.e., straight segments, curves, hills, tunnels, and curves on hills). A driving simulator experiment was conducted to explore the effects of different road scenarios and different types of distraction while driving. The collected data was used to estimate driving behaviour through a Generalized Linear Mixed Model (GLMM) with repeated measures. The analysis was divided into two phases. Phase one aimed to evaluate driver performance under the presence and absence of pedestrians and oncoming traffic, different lanes width and different types of distraction. The second phase analysed driver behaviour when driving through different road geometries and lane widths and under different types of distraction. The results of the experiment indicated that drivers are likely to overcorrect position in the vehicle lane in the presence of pedestrians and oncoming traffic. The effect of road geometry on driver behaviour was found to be greater than the effect of mobile phone distraction. Curved roads and hills were found to influence preferred speeds and lateral position the most. The results of this investigation also show that drivers under visual-manual distraction had a higher standard deviation of speed and lateral position compared to the cognitive distraction and the non-distraction condition.     

Factors influencing drivers’ reading and comprehension of on-board traffic messages

IntroductionWhen variable message signs (VMS) or on-board traffic information systems are used, it is essential that while driving, motorists read and understand the information as soon as possible in order to make appropriate decisions to increase road safety and/or facilitate traffic flow. Thus, it is important to investigate the factors that may increase fast reading and comprehension of on-board traffic information.ObjectivesWe examined the influence of the type of message (warnings vs. recommendations), location of the pictogram (top or bottom of the text), type of display device (IPhone, Blackberry, or Tablet) and its position (horizontal or vertical) on drivers’ fast reading and comprehension of on-board messages provided via in-vehicle system. Moreover, we were interested in drivers’ acceptability of in-vehicle system.MethodForty-nine drivers (M_Men = 32, 19–65 years) participated to a reading and comprehension task while travelling on a desktop driving simulator. Participants were exposed to two series of 11 traffic messages displayed on one of the three devices. Reading and comprehension times were measured (= milliseconds) for each message. At the end, they had to fill in a questionnaire on their beliefs about on-board traffic messages and in-vehicle system.ResultsDrivers expressed a positive attitude toward on-board traffic messages and in-vehicle system. Reading and comprehension times were of approximately 4 seconds and were longer for warnings as compared to recommendations. The pictogram placed at the top of the text, the tablet and the vertical display device facilitated fast reading and comprehension.     

Field testing anti-speeding messages

PurposeDetermine whether anti-speeding messages displayed on roadside variable message signage (VMS) influence drivers’ speed choice selections.MethodSpeed detection tubes were installed across a single carriageway 60 km/h limit road section at positions prior to, immediately after, and at a longer distance from VMS display of anti-speeding messages during study Week2. Bi-directional vehicle speed data were collected continuously during the week prior to VMS installation (Week1), throughout the week that the anti-speeding messages were displayed (Week2), and a post-display week (Week3).ResultsOf six separately measured locations, Week2 southbound mean speeds (facing signage) and percent of drivers/riders exceeding the signed speed limit were consistently below those recorded during Week1 for all time periods. Aggregated Week3 (post-VMS) southbound data for all time periods, showed consistent patterns for mean speed and percent of drivers exceeding the signed speed limit, being higher than in Week2 (VMS displayed) but lower than during Week1 (pre-VMS).DiscussionCompared with Week1, messages influenced aggregate driver speed selection during Week2, with a residual positive effect (slower speeds) in Week3. While all three messages had positive effects, differences occurred in relative effectiveness between daytime (school and non-school hours) and night-time periods. Separately disaggregated data revealed differential effects for the three messages.ConclusionsFindings demonstrated the value of implementing theoretically informed message content and provided evidence for the impact that roadside road safety messaging can have on driver speed selection.     

Distraction while driving: The case of older drivers

As the impairment of older drivers is especially found in perception and attention, one could assume that they are especially prone to distraction effects of secondary tasks performed while driving. The aim of the study was to examine the effect of age on driving performance as well as the compensation strategies of older drivers under distraction. 10 middle-aged and 10 older drivers drove in a simulator with and without a secondary task. To assess driving performance the Lane Change Task (Mattes, 2003) was used. This method aims at estimating driver demand while a secondary task is being performed, by measuring performance degradation on a primary driving-like task in a standardized manner. The secondary task – a self-developed computer-based version of “d2 Test of Attention” was presented both with and without time pressure. The results show that older participants’ overall driving performance (mean deviation from an ideal path) was worse in all conditions as compared to the younger ones. With regard to lane change reaction time both age groups were influenced by distraction in a comparable manner. However, when the lane keeping performance (standard deviation of the lateral position) was examined, the older participants were more affected than the younger ones. This pattern could be explained by compensation strategies of the older drivers. They focused on the most relevant part of the driving task, the lane change manoeuvres and were able to maintain their performance level in a similar way as did younger drivers. The driving performance of the older participants was not additionally impaired when the secondary task imposed time pressure. Overall, subjective rating of driving performance, perceived workload and perceived distraction was found to be similar for both age groups. The observed trends and patterns associated with distraction while driving should contribute to the further research or practical work regarding in-vehicle technologies and older drivers.     

Detecting eye movements in dynamic environments

To take advantage of the increasing number of in-vehicle devices, automobile drivers must divide their attention between primary (driving) and secondary (operating in-vehicle device) tasks. In dynamic environments such as driving, however, it is not easy to identify and quantify how a driver focuses on the various tasks he/she is simultaneously engaged in, including the distracting tasks. Measures derived from the driver’s scan path have been used as correlates of driver attention. This article presents a methodology for analyzing eye positions, which are discrete samples of a subject’s scan path, in order to categorize driver eye movements. Previous methods of analyzing eye positions recorded in a dynamic environment have relied completely on the manual identification of the focus of visual attention from a point of regard superimposed on a video of a recorded scene, failing to utilize information regarding movement structure in the raw recorded eye positions. Although effective, these methods are too time consuming to be easily used when the large data sets that would be required to identify subtle differences between drivers, under different road conditions, and with different levels of distraction are processed. The aim of the methods presented in this article are to extend the degree of automation in the processing of eye movement data by proposing a methodology for eye movement analysis that extends automated fixation identification to include smooth and saccadic movements. By identifying eye movements in the recorded eye positions, a method of reducing the analysis of scene video to a finite search space is presented. The implementation of a software tool for the eye movement analysis is described, including an example from an on-road test-driving sample.     

Reading the situation: The relationship between dyslexia and situational awareness for road sign information

Road signs are tools that provide crucial information to drivers about various roadway situations. Therefore, the present study aimed to assess the levels of ‘situation awareness’ held by drivers in relation to these signs. This study also assessed the relationship between dyslexia, road sign comprehension, and road sign situation awareness, thus building on the limited research in this area. Drivers completed measures of road sign comprehension and dyslexia. Drivers then completed three drives on a driving simulator; each followed by a probe containing queries about the perception, comprehension and projection of road signs seen in the preceding drive. Situation awareness was lowest at the level of projection. Further, dyslexia was negatively associated with road sign comprehension, and road sign situation awareness, suggesting that the disorder may be detrimental for multiple forms of road sign processing. Implications are provided in the form of a ‘SAFE’ driver training program that targets a holistic form of road sign processing which takes into account sign meanings in relation to both in-vehicle and outer-vehicle factors; thus encouraging proactive driver behaviour.     

The power and sensitivity of four core driver workload measures for benchmarking the distraction potential of new driver vehicle interfaces

This study evaluated the power and sensitivity of several core driver workload measures in order to better understand their use as a component of future driver distraction potential evaluation procedures of the in-vehicle human machine interface (HMI). Driving is a task that requires visual, manual and cognitive resources to perform. Secondary tasks, such as mobile phone use and interaction with in-built navigation, which load onto any of these three processing resources increase driver workload and can lead to impaired driving. Because workload and distraction potential are interrelated, a comprehensive method to assess driver workload that produces valid and predictive results is needed to advance the science of distraction potential evaluation. It is also needed to incorporate into New Car Assessment Program (NCAP) testing regimes. Workload measures of cognitive (DRT [Detection Response Task] Reaction Time), visual (DRT Miss Rate), subjective (NASA-TLX [driver workload questionnaire]), and temporal demand (Task Interaction Time) were collected as participants drove one of 40 vehicles while completing a variety of secondary tasks with varying interaction requirements. Of the evaluated measures, variance and power analyses demonstrated that Task Interaction Time is the most sensitive in detecting differences in driver workload between different in-vehicle HMIs, followed by DRT Miss Rate, NASA-TLX and finally DRT Reaction Time. There were relatively weak correlations between each of the four measures. These results suggest that Task Interaction Time, coupled with a reliable visual demand metric such as DRT Miss Rate, eye glance coding, or visual occlusion, more efficiently detect differences in driver workload between different HMIs compared to DRT Reaction Time and the NASA-TLX questionnaire. These results can be used to improve the understanding of the utility of each of these core driver workload measures in assessing driver distraction potential.     

Comprehension of new instructions for car drivers in merging areas

This article describes some key results of a study with the aim of measuring the time and accuracy of comprehension of the new instructions ‘keep lane’ and ‘merge alternately’. These instructions shall allow for a more efficient merging behaviour when approaching a working zone with a lane closure on a motorway, and thus increase the capacity of such bottlenecks. One hundred and ninety seven randomly selected car drivers were surveyed by means of face-to-face interviews. A computer-aided survey design ensured a precise measurement of the comprehension time and the testing of animated signs. The instruction ‘merge alternately’ performed well in every respect, though the tested signs were new to drivers. The instruction ‘keep lane’ refers to a completely new meaning. It lags behind both in time and accuracy of comprehension. In this case, the results suggest using a variable message sign (VMS) with a simple text rather than a picture. Moreover, a considerable learning effect was identified. Comprehension improved significantly with the third repetition of the instruction.     

Driver performance effects of simultaneous visual and cognitive distraction and adaptation behavior

Driver distraction has become a major concern for transportation safety due to increasing use of infotainment systems in vehicles. To reduce safety risks, it is crucial to understand how fundamental aspects of distracting activities affect driver behavior at different levels of vehicle control. This study used a simulator-based experiment to assess the effects of visual, cognitive and simultaneous distraction on operational (braking, accelerating) and tactical (maneuvering) control of vehicles. Twenty drivers participated in the study and drove in lead-car following or passing scenarios under four distraction conditions: without distraction, with visual distraction, with cognitive distraction, and with simultaneous distraction. Results revealed higher perceived workload for passing than following. Simultaneous distraction was most demanding and also resulted in the greatest steering errors among distraction conditions during both driving tasks. During passing, drivers also appeared to slow down their responses to secondary distraction tasks as workload increased. Visual distraction was associated with more off-road glances (to an in-vehicle device) and resulted in high workload. Longer headway times were also observed under visual distraction, suggesting driver adaptation to the workload. Similarly, cognitive distraction also increased driver workload but this demand did not translate into steering errors as high as for visual distraction. In general, findings indicate that tactical control of a vehicle demands more workload than operational control. Visual and cognitive distractions both increase driver workload, but they influence vehicle control and gaze behavior in different ways.     

Modeling drivers' visual attention allocation while interacting with in-vehicle technologies

In 2 experiments, the authors examined how characteristics of a simulated traffic environment and in-vehicle tasks impact driver performance and visual scanning and the extent to which a computational model of visual attention (SEEV model) could predict scanning behavior. In Experiment 1, the authors manipulated task-relevant information bandwidth and task priority. In Experiment 2, the authors examined task bandwidth and complexity, while introducing infrequent traffic hazards. Overall, task priority had a significant impact on scanning; however, the impact of increasing bandwidth was varied, depending on whether the relevant task was supported by focal (e.g., in-vehicle tasks; increased scanning) or ambient vision (e.g., lane keeping; no increase in scanning). The computational model accounted for approximately 95% of the variance in scanning across both experiments.