A systematic review of definitions of motor vehicle headways in driver behaviour and performance studies

Headway is a safety measure commonly used to investigate driving behaviour and driver performance. Its purpose is to reflect the following distance or time between a leading and following vehicle in traffic. It is therefore associated with drivers’ response time, such as in braking or swerving, during safety critical events. In the literature, distance and time headway are defined in different ways, despite standard definitions in the traffic engineering literature, which prompted this systematic review of headway definitions across a range of study designs, in order to recommend approaches to improve the accuracy and reproducibility of headway definitions used in road safety contexts. PRISMA guidelines were followed to search four databases (EMBASE, COMPENDEX, SCOPUS and MEDLINE) for studies that reported on headways or discussed methodological approaches. The search and filtering of abstracts identified 110 articles for a qualitative synthesis. Four broad approaches to measuring headways were detected: studies using simulation, roadside external features, on-road features, and on-vehicle features. Studies were coded as to whether they included written explanation, mathematical statements, or pictorial depictions of headway. Only 49.6% of studies contextualised headway sufficiently for reproducibility. Reproducibility is crucial for accurate interpretation of research findings and comparisons across studies. It is recommended that headway definitions should a) exclude vehicle or parts of vehicle lengths, b) include reference points (e.g., bumper/axle/rear), c) have a consistent terminology, and d) include the accuracy of headway measuring devices to report the precision of a study’s findings.     

Gender‐Based Judgments of Traffic Violations: The Moderating Influence of Car Type1

This paper reports the findings of a study investigating interpretations of driver behavior during a traffic accident. Using authentic road‐accident reports including figurative depictions of the accident and a photograph of the car involved, participants were asked to make judgments of the driver's carelessness and aggression before and during the accident. Contextual factors were manipulated by altering the type of car driven (following Davies, 1999) and the sex of the driver. Results showed that car type influenced the allocation of cause of the accident, with drivers of a BMW being described as having acted more aggressively, and drivers of Smart Cars having been depicted as acting more carelessly, despite the actions of both drivers being held constant. In addition, the actions of the female driver were interpreted as more attributable to driver carelessness than driver aggression or external factors. Results are discussed with reference to car‐type stereotypes. Ways in which such biased interpretations could influence how drivers respond to other road users in real‐life situations are suggested.     

Driving on familiar roads: Automaticity and inattention blindness

This paper describes our research into the processes that govern driver attention and behavior in familiar, well-practiced situations. The experiment examined the effects of extended practice on inattention blindness and detection of changes to the driving environment in a high-fidelity driving simulator. Participants were paid to drive a simulated road regularly over 3 months of testing. A range of measures, including detection task performance and driving performance, were collected over the course of 20 sessions. Performance from a yoked Control Group who experienced the same road scenarios in a single session was also measured. The data showed changes in what drivers reported noticing indicative of inattention blindness, and declining ratings of mental demand suggesting that many participants were “driving without awareness”. Extended practice also resulted in increased sensitivity for detecting changes to road features associated with vehicle guidance and improved performance on an embedded vehicle detection task (detection of a specific vehicle type). The data provide new light on a “tandem model” of driver behavior that includes both explicit and implicit processes involved in driving performance. The findings also suggest reasons drivers are most likely to crash at locations very near their homes.     

A diary study of distracted driving behaviours

The introduction and uptake of technology within road vehicles has readily advanced the capabilities and the functions that the driver of a road vehicle has available to them. While this has benefited the drivers’ productivity and entertainment behind the wheel, it has also heightened the possibility for distraction. Research into driver distraction to date has identified how technologies inside the vehicle may be used ineffectively and can compromise the safety of the road transport system. Yet, the factors that drivers state impact on their decision to engage with distracting technologies are less well known. This paper presents the first diary study into driver distraction. The study asked drivers to record all technological distractions that they engaged with across a 4-week period, as well as interactions that they ignored or choose not to engage with. The diary entries include the technologies drivers interacted with and the conditions surrounding this, as well as external factors that drivers cited to influence their decision to interact. Primarily, factors relating to the task itself were found to be of most importance to the drivers’ decision to engage. Differences were also found in how drivers stated they compensated for any engagement with distracting tasks. This has important consequences for the design and integration of technological devices into the vehicle. The novel application of the method offers insights into the naturalistic conditions surrounding drivers’ involvement with distracting technologies. The method is also reviewed on its applicability to the study of driver distraction.     

Following slower drivers: Lead driver status moderates driver’s anger and behavioural responses and exonerates culpability

Two experiments investigated the effects of lead-driver status on the anger-experienced and aggression-expressed in traffic scenarios in which the lead drivers’ actions were determined by an event obviously beyond, or within, their control. Experiment I contrasted reactions to lead-cars bearing Learner driver markings (Low Status) or similar unmarked cars (Control), while Experiment II contrasted reactions to Ambulances (High Status) or otherwise identical generic work vans (Control). Reported anger, heart-rate and behaviour were measured while drivers drove. When the lead vehicle slowed or changed course because of the actions of another road user, drivers were reliably more angered when slowed by a learner driver than an unmarked sedan. Drivers reported less anger when slowed by an Ambulance, than by a work van, when there was no apparent cause for the lead-vehicle slowing. Driver behaviour also differed according to lead-vehicle status. Drivers allowed greater headway between themselves and a slower ambulance, but drove closer to the work-van, and followed Learner drivers at a dangerously close distance, leaving greater headway behind a similar, unmarked car. Reliable differences in subjective anger ratings and behaviour suggest that anger experienced and expressed depends not just on the actions of the perpetrator but on the perceived status of that perpetrator. Higher status vehicles appear to be forgiven their indiscretions more readily even when there are no extenuating circumstances, whilst lower status drivers are likely to be blamed more readily for circumstances beyond their control.     

Effectiveness of the compensatory strategy adopted by older drivers: Difference between professional and non-professional drivers

It has been a controversial issue for the effect of ageing population on driving safety. Apparently, drivers’ physiological and cognitive performances deteriorate with age. However, older drivers may compensate for the elevated risk by adjusting their behaviors, known as compensatory strategy. Despite the extensive research on this topic, the compensatory strategy of older professional drivers is not well understood since many studies focused on the differences in compensatory behavior between older and young drivers. Professional drivers tend to be more skillful and able to cope with the unfavorable driving environments, thus presenting a higher capability to mitigate the risk. This study attempts to examine the compensatory behavior and its safety effect amongst older professional drivers, as compared to those of older non-professional drivers, using the driving simulator approach. In the driving simulator experiment, participants were asked to follow a leading vehicle for one hour, and two sudden brake events were presented. 41 (mid-aged and older) drivers completed the driving tests. Each participant was required to complete a car-following test, either under high or low traffic flow conditions. Performance indicators include driving capability (i.e. lateral control, longitudinal control, and brake reaction time) and compensatory behavior (i.e. average speed, and time headway). Additionally, two modified traffic conflict measures: time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) are applied to indicate the traffic conflict risk. The random parameter Tobit models were estimated to measure the association between conflict risk and driver attributes, and random intercept models were used to assess other driving performance indicators. Results show that despite the impaired lateral control performance and longer brake reaction time of older drivers, the likelihood of severe traffic conflict of older drivers is lower than that of mid-aged drivers. Furthermore, though both older professional and older non-professional drivers adopted longer time headway, the reduction in the risk of severe traffic conflict is more profound among the older professional drivers. Such findings suggest that older professional drivers are more capable of mitigating the possible collision risk by adopting the compensatory strategy, as compared to older non-professional drivers. This justifies the existence of compound effect by the compensatory strategy of older driver and better driving skills of professional driver. This research provides useful insights into driver training and management strategies for employers, as older drivers would become a major cohort in the transportation industry.     

Influence of traffic conditions on driver behavior before making a right turn at an intersection: Analysis of driver behavior based on measured data on an actual road

This paper describes an investigation of the influence of the position of a forward vehicle and following vehicle on the onset of driver preparatory behavior before making a right turn at an intersection. Four experimental vehicles with various sensors and a driving recorder system were developed to measure driver behavior before making a right turn at a specific intersection on a public road. The experimental term was eight weeks to collect data on natural driving maneuvers. The relationships between the remaining distances to the center of the intersection when releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal and the relative distances from the forward and following vehicles were analyzed based on the measured data. The time it took to reach the center of the turn and the driving speed when each behavioral event occurred were also evaluated from the viewpoint of the relative position between the driver’s vehicle and the leading or following vehicles. The results suggest that the drivers approached the target intersection in a car-following condition, and that the positions of the front and rear vehicles and the vehicle velocity influence the onset location and timing of releasing the accelerator pedal and covering the brake pedal. Drivers began to decelerate closer to the center of the intersection when they approached the intersection close to a leading or following vehicle at a reduced driving speed. However, these influences were not reflected in the turn signal operation, indicating that drivers intend to make a right turn at a constant location while approaching a target intersection and that intention appears in the turn signal activation. The findings of this observational study imply that the method of providing route guidance instruction, in which the traffic conditions surrounding the driver’s vehicle are taken into consideration, is effective in reducing driver errors in receiving instruction and following the correct route. The results also indicate that measuring and accumulating different behavioral indices based on traffic conditions contribute to determining the criteria for the presentation timing just before reaching the intersection, which can assist drivers in preparing to make a right turn at a usual location. Driver decelerating maneuvers are used while driving without leading or following vehicles and while driving with a lead and/or following vehicle at long range, and driver turn signal operations are used when approaching an intersection under close car-following conditions.     

Temporal fluctuations in driving demand: The effect of traffic complexity on subjective measures of workload and driving performance

Traffic density has been shown to be a factor of traffic complexity which influences driver workload. However, little research has systematically varied and examined how traffic density affects workload in dynamic traffic conditions. In this driving simulator study, the effects of two dynamically changing traffic complexity factors (Traffic Flow and Lane Change Presence) on workload were examined. These fluctuations in driving demand were then captured using a continuous subjective rating method and driving performance measures. The results indicate a linear upward trend in driver workload with increasing traffic flow, up to moderate traffic flow levels. The analysis also showed that driver workload increased when a lane change occurred in the drivers’ forward field of view, with further increases in workload when that lane change occurred in close proximity. Both of these main effects were captured via subjective assessment and with driving performance parameters such as speed variation, mean time headway and variation in lateral position. Understanding how these traffic behaviours dynamically influence driver workload is beneficial in estimating and managing driver workload. The present study suggests possible ways of defining the level of workload associated with surrounding traffic complexity, which could help contribute to the design of an adaptive workload estimator.     

User-related assessment of a Driver Assistance System for Continuous Support – A field trial

A Driver Assistance System for Continuous Support continuously evaluates the status of the host vehicle as well as the surrounding traffic based on information from on-board sensors. When the system detects a hazard, it issues a warning to the driver, depending on the degree of the hazard. The effects of this system on driver behaviour and acceptance were evaluated in a field trial carried out in 2013. Twenty-four drivers took part in test drives with a within-subject design along a 53 km test route containing motorway and rural-road sections. Driving data was logged and the test drivers were observed by means of an in-car observation method (Wiener Fahrprobe); in this case by two observers in the car along with the driver. Questionnaires were used to assess the drivers’ comprehension of and reaction to the system. The system was successful in affecting driver behaviour in terms of lower speed when negotiating curves. Positive effects were found in the form of better speed adaptation to the situation during driving with the system activated. Also, lane choice and lane change improved with the system on. When it came to speed limit compliance, driving speed in general and longitudinal and lateral positioning, no effects could be found. No major differences were found regarding distance to the vehicle in front, overtaking manoeuvres, stopping behaviour at intersections, driving against yellow at traffic lights and interaction behaviour with other road users while driving with or without the system. On the negative side, it was noted that only during driving with the system activated did the test drivers make turns at intersections at too high speeds. In addition, more errors associated with dangerous distance to the side were observed with the system activated. In terms of the emotional state of the driver, the only difference found was that the drivers felt an increase in irritation. Regarding subjective workload, the drivers only assessed one item, i.e. whether their performance decreased statistically significantly while driving with the system. The test drivers were of the opinion that the system was useful, and that it would enhance safety especially in overtaking manoeuvres on motorways. The blind-spot warning was found especially useful in the overtaking process. The drivers appreciated the fact that the system did not give information all the time.     

Tendency to commit traffic violations and presence of passengers in the car

The present study examined whether the tendency to commit traffic violations differed when drivers were with and without the presence of other persons in the car. One thousand and eight drivers were observed by the road side. The data registered by the observers included estimated age of the driver and the passengers, sex of the driver and number of passengers. Four dependent variables were registered for each driver, which are, wearing seatbelt, signaling, using hand-held cellular phone and keeping the distance from the vehicle in front. It has been found that for both males and females, old and young, a greater proportion of drivers who were alone committed traffic violations as compared to drivers who were not alone. These results are discussed in relation to social influences on drivers and allow insight into how the presence of passengers has an impact on driver behavior and traffic safety.     

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.     

Assessing the effect of long-automated driving operation,repeated take-over requests,and driver’s characteristics on commercial motor vehicle drivers’ driving behavior and reaction time in highly automated vehicles

Automated Commercial Motor Vehicles (CMVs) have the potential to reduce the occurrence of crashes, enhance traffic flow, and reduce the stress of driving to a larger extent. Since fully automated driving (SAE Level 5) is not yet available, automated driving systems cannot perform all driving tasks under all road conditions. Drivers need to regain the vehicle’s control when the system reaches its maximum operational capabilities. This transition from automated to manual is referred to as Take-Over Request (TOR). Evaluating driver’s performance after TORs and assessing effective parameters have gained much attention in recent years. However, few studies have addressed CMV drivers’ driving behavior after TOR and the effect of long-automated driving and repeated TORs. This paper aims to address this gap and gain behavioral insights into CMV drivers’ driving behavior after TOR and assess the effect of the duration of automated operation before TOR, repeated TORs, and driver characteristics (e.g., age, gender, education, and driving history). To accomplish this, we designed a 40-minutes experiment on a driving simulator and assessed the responses of certified CMV drivers to TORs. Drivers’ reaction time and driving behavior indices (e.g., acceleration, velocity, and headway) are compared to continuous manual driving to measure driving behavior differences. Results showed that CMV drivers’ driving behavior changes significantly after the transition to manual regardless of the number of TORs and the duration of automated driving. Findings suggest that 30 min of automated operation intensifies the effect of TOR on driving behaviors. In addition, repeated TOR improves reaction times to TOR and reduces drivers' maximum and minimum speed after TORs. Driver’s age and driving history showed significant effects on reaction time and some driving behavior indices. The findings of this paper provide valuable information to automotive companies and transportation planners on the nature of driver behavior changes due to the carryover effects of manual driving right after automated driving episodes in highly automated vehicles.     

Car-following behavioural adaptation when driving next to automated vehicles on a dedicated lane on motorways: A driving simulator study in the Netherlands

Automated vehicles (AVs) are expected to improve traffic flow efficiency and safety. The deployment of AVs on motorways is expected to be the first step in their implementation. One of the main concerns is how human drivers will interact with AVs. Dedicating specific lanes to AVs have been suggested as a possible solution. However, there is still a lack of evidence-based research on the consequence of dedicated lanes for AVs on human drivers’ behavior. To bridge this research gap, a driving simulator experiment was conducted to investigate the behavior of human drivers exposed to different road design configurations of dedicated lanes on motorways. The experiment sample consisted of 34 (13 female) licensed drivers in the age range of 20–30. A repeated measures ANOVA was applied, which revealed that the type of separation between the dedicated lane and the other lanes has a significant influence on the behavior of human drivers driving in the proximity of AV platoons. Human drivers maintained a significantly lower time headway (THW) when driving in the proximity of a continuous access dedicated lane as compared to a limited-access dedicated lane with a guardrail separation for AV platoons. A similar result was found for the limited-access dedicated lane in comparison to the limited-access dedicated lane with guardrail separation. Moreover, the results regarding the empirical relationships between THW and sociodemographic variables indicate a significant THW difference between males and females as well as a significant inverse relationship between THW and the years of driving experience.     

Disengagement from driving when using automation during a 4-week field trial

IntroductionA small body of research on the real-world use of commercially available partial driving automation suggests that drivers may struggle with or otherwise lapse in adequately monitoring the system and highway environment, and little is known about key issues such as how behavior associated with system use changes over time. The current study assessed how driver disengagement, defined as visual-manual interaction with electronics or removal of hands from the wheel, differed as drivers became more accustomed to partial automation over a 4-week trial.MethodsTen volunteers drove a Volvo S90 with adaptive cruise control (ACC), which automates speed and headway, and Pilot Assist, which combines ACC and continuous lane centering. Instrumentation captured automation use, secondary task activity, hands-on-wheel status, vehicle speed, and GPS location during all trips.ResultsThe longer drivers used the Pilot Assist partial automation system, the more likely they were to become disengaged, with a significant increase in the odds of observing participants with both hands off the steering wheel or manipulating a cell phone relative to manual control. Results associated with use of ACC found comparable or lower levels of disengagement compared to manual driving as the study progressed.DiscussionThis study highlights concerns about vehicle control and the degree to which drivers remain actively in the loop when using automation. Calls for implementing more robust driver monitoring with partial automation appear warranted—particularly those that track head or eye position.     

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.     

Headway on urban streets: observational data and an intervention to decrease tailgating

A method to collect headway (tailgating) data in an urban setting was implemented and produced reliable headway data on over 25 000 drivers. Data are reported on the effectiveness of two hand-held roadside signs admonishing drivers not to tailgate. One of these signs (that included a reference to “crashes”) had a significantly positive impact on drivers' headway. Drivers’ followed with an average headway of 2.11 s when the sign was absent compared to an average headway of 2.29 s when the sign was present. When the sign was absent, 49.4% of the drivers were in compliance with the 2-second rule compared to 57.5% when the sign was present. The percentage of drivers who followed with a headway of less than 1 s decreased from 7.3 when the sign was absent to 3.0 when the sign was present. Additionally, there was an increase of 10.6 ft in vehicle separation from baseline to intervention.     

Comparison of contributing factors in hit-and-run crashes with distracted and non-distracted drivers

Among different types of crashes, hit-and-run is driver’s failure to stop after a vehicle crash. There are many accidents where drivers could actually be at fault or totally innocent, and leaving the scene would turn an innocent driver into a criminal. The current paper aims to contribute to the literature by exploring the association of different variables pertaining to the condition of infrastructure, environment, driver, population of the area, and crash severity and type with hit-and-run crashes. The analysis is performed for two data sets: (i) crashes where the driver was distracted; and (ii) crashes where driver was not distracted. Hit-and-run crash data with corresponding factors are police-reported data for crashes within Cook County, Illinois, occurring between 2004 and 2012. A logistic regression model assessed 43 variables within 16 categories for statistically significant association with hit-and-run crashes, for drivers with and without distraction. For both driver distraction statuses, 17 variables were associated with a significant increased probability of a hit-and-run crash and 10 variables were associated with a significant decreased probability. Additionally, it was found that crashes on curve level and curve hillcrest road alignment types were associated with increased likelihood of a hit-and-run crash when the driver was distracted and decreased likelihood when the driver was not distracted. Variables related to hit-and-run crashes vary depending on driver’s distraction status. When comparing likelihood to flee the scene after a crash, non-distracted drivers are 27% less likely to do so compared to distracted drivers.     

Challenges for automated vehicle driver training: A thematic analysis from manual and automated driving

Considerable research and resources are going into the development and testing of Automated Vehicles. They are expected to bring society a huge number of benefits (such as: improved safety, increased capacity, reduced fuel use and emissions). Notwithstanding these potential benefits, there have also been a number of high-profile collisions involving Automated Vehicles on the road. In the majority of these cases, the driver’s inattention to the vehicle and road environment was blamed as a significant causal factor. This suggests that solutions need to be developed in order to enhance the benefits and address the challenges associated with Automated Vehicles. One such solution is driver training. As drivers still require manual driving skills when operating Automated Vehicles on the road, this paper applied the grounded theory approach to identify eight “key” themes and interconnections that exist in current manual vehicle driver training. These themes were then applied to the limited literature available on Automated Vehicle driver training, and a ninth theme of trust emerged. This helped to identify a set of training requirements for drivers of Automated Vehicles, which suggests that a multifaceted approach (covering all nine themes and manual and Automated Vehicle driving skills) to driver training is required. This framework can be used to develop and test a training programme for drivers of Automated Vehicles.     

Passing behavior on two-lane highways

Two-lane highways make up a substantial proportion of the road network in most of the world. Passing is among the most significant driving behaviors on two-lane highways. It substantially impacts the highway performance. Despite the importance of the problem, few studies attempted to model passing behavior. In this research, a model that attempts to capture both drivers’ desire to pass and their gap acceptance decisions to complete a desired passing maneuver is developed and estimated using data on passing maneuvers collected with a driving simulator. Sixteen different scenarios were used in the experiment in order to capture the impact of factors related to the various vehicles involved, the road geometry and the driver characteristics in the model.A passing behavior model is developed that includes choices in two levels: the desire to pass and the decision whether or not to accept an available passing gap. The probability to complete a passing maneuver is modeled as the product of the probabilities of a positive decision on both these choices. The estimation results show that modeling the drivers’ desire to pass the vehicle in front has a statistically significant contribution in explaining their passing behavior. The two sub-models incorporate variables that capture the impact of the attributes of the specific passing gap that the driver evaluates and the relevant vehicles, the geometric characteristics of the road section and the driver characteristics and account for unobserved heterogeneity in the driver population.     

Effects of variable message signs for slippery road conditions on reported driver behaviour

A field study by Rämä and Kulmala (Rämä, P., Kulmala, R. (2000). Effects of variable message signs for slippery road conditions on driving speed and headways. Transportation Research, Part F, 3, 85–94.) showed that a variable message sign warning about slippery road conditions reduced the mean speed by 1–2 km/h. The study also showed that a variable message sign recommending a minimum headway between vehicles decreased the proportion of short headways. However, the signs may have other effects on driver behaviour besides those measurable in terms of speed and headway, and this study was designed to investigate such potential effects. In total, 114 drivers who had encountered the slippery road condition sign and 111 drivers who had encountered the sign showing recommended minimum headway in adverse road surface conditions were interviewed. The results suggested that these variable message signs do indeed have other effects, such as the refocusing of attention to seek cues on potential hazards, testing the slipperiness of the road, and more careful passing behaviour. On the other hand, the results suggested that driving speed and headway are essential variables with which many other variables correlate.