New systems: new behaviour?

Traditional methods of speed reduction such as traffic calming and enforcement tend to have only local effects. A global speed reducing measure, Intelligent Speed Adaptation (ISA) which restricts drivers to the posted speed limit is being considered as an alternative. This paper reports a driving simulator study that evaluated the effects of such a system on driver behaviour. Measures of safety were taken when drivers drove with and without an ISA system, in addition to subjective measures of workload and acceptability. A number of changes in behaviour were noted, whereby drivers were more inclined to engage in riskier behaviour when the ISA system was operational. These changes were accompanied by reductions in maximum speeds, particularly in low speed limit areas and at speed limit transition points. It is suggested that the combinatory effects of these changes in behaviour have to be considered within the context of total network safety.     

Factors influencing drivers’ decision to install an electronic speed checker in the car

Intelligent speed adaptation (ISA) refers to various concepts aiming at limiting the vehicle speed. In Umeå, Sweden, a large scale field study was carried out to test the possibility to, on a voluntary basis, install one type of ISA device in private vehicles. In this study 10,300 car owners were contacted by telephone and offered to have an ISA device installed in their car. This paper reports on drivers’ attitudes to four different ISA-applications and on factors influencing the decision to install the one type of ISA, an electronic speed checker (ESC). The results show that approximately 40% of the respondents accepted the offer to have an ESC installed in their vehicle. The analysis indicated that age, perceived risk, moral and perceived difficulty to keep the speed limits significantly influenced their evaluation of the ESC and that the perception of the ESC influenced the decision to participate.     

The tendency of drivers to pass other vehicles

The purpose of this study was to assess the speed differential threshold—if there is one—at which drivers decide to pass a lead vehicle. Drivers in a simulator encountered vehicles in front that were programmed to travel at speeds that were similar, slightly below, or even slightly above the drivers’ own speed. The study involved a total of 152 such passing opportunities. In almost all of the encounters with slower vehicles (traveling at speeds slower than 3 km/h of the driver) they passed them, and in two thirds of the encounters when the lead vehicles were moving at their speed they passed them too. Most surprising was that in 50% of the encounters drivers passed the lead vehicle when it was traveling faster than their average speed. In these situations drivers actually increased their own speed substantially to accomplish the passing maneuver, despite the fact that not passing the lead vehicle would not have caused any delays. The tendency to pass appears to be related to the drivers’ own speed variability: the more variable the driver’s speed the more likely he or she was to pass the vehicle ahead even when its speed was greater than their average speed. The results are interpreted in terms of (a) driver aggression, and (b) association of car following with added effort, attention overload, or risk. The latter explanation implies that the tendency to pass vehicles may be reduced with the introduction of in-vehicle technologies such as adaptive cruise control.     

Manual drivers’ experience and driving behavior in repeated interactions with automated Level 3 vehicles in mixed traffic on the highway

In the near future, conditionally automated vehicles (CAVs; SAE Level 3) will travel alongside manual drivers (≤ SAE level 2) in mixed traffic on the highway. It is yet unclear how manual drivers will react to these vehicles beyond first contact when they interact repeatedly with multiple CAVs on longer highway sections or even during entire highway trips. In a driving simulator study, we investigated the subjective experience and behavioral reactions of N = 51 manual drivers aged 22 to 74 years (M = 41.5 years, SD = 18.1, 22 female) to driving in mixed traffic in repeated interactions with first-generation Level 3 vehicles on four highway sections (each 35 km long), each of which included three typical speed limits (80 km/h, 100 km/h, 130 km/h) on German highways. Moreover, the highway sections differed regarding the penetration rate of CAVs in mixed traffic (within-subjects factor; 0%, 25%, 50%, 75%). The drivers were assigned to one of three experimental groups, in which the CAVs differed regarding their external marking, (1) status eHMI, (2) no eHMI, and (3) a control group without information about the mixed traffic. After each highway section, drivers rated perceived safety, comfort, and perceived efficiency. Drivers were also asked to estimate the penetration rate of CAVs on the previous highway section. In addition, we analyzed drivers’ average speed and their minimum time headways to lead vehicles for each speed zone (80 km/h, 100 km/h, 130 km/h) as well as the percentage of safety critical interactions with lead vehicles (< 1 s time headway). Results showed that manual drivers experienced driving in mixed traffic, on average, as more uncomfortable, less safe and less efficient than driving in manual traffic, but not as dangerous. A status eHMI helps manual drivers identify CAVs in mixed traffic, but the eHMI had no effect on manual drivers’ subjective ratings or driving behavior. Starting at a level of 25% Level 3 vehicles in mixed traffic, participants' average speed decreased significantly. At the same time, the percentage of safety critical interactions with lead vehicles increased with an increasing penetration rate of CAVs. Accordingly, additional measures may be necessary in order to at least keep the existing safety level of driving on the highway.     

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Models for describing the microscopic driving behavior rarely consider the “social effects” on drivers’ driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers’ driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers’ instantaneous behavior and shift the individuals’ driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver’s acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers’ social interactions can change traffic flow and implications of the study results are discussed.     

The role of preference in speed choice

Individual differences with regard to speed preference may be a source of speed heterogeneity and conflicts in traffic, such as tailgating and dangerous overtaking. The main aim of the current study was to explore drivers’ speed preferences when driving for different reasons (saving money on fuel, driving safely, driving for fun or driving as usual) and the relationship of these preferences to observed speeds and self-reported speed. 193 drivers were interviewed at five different locations, and were asked about their speeds on roads they had just travelled. Drivers’ speeds on these roads were also sampled with a speed gun. The results showed large differences between speeds chosen for different driving purposes; the lowest speeds were chosen when the goal was economy and the highest when driving for fun. In addition, there were individual differences in speed preferences such that some drivers indicated that their usual speed was above what they believed was a safe speed while others indicated that they usually drove even slower than what they thought was safe. These differences may account for much of the speed heterogeneity observed in on-road behaviour. The results also showed that drivers’ speed choices are highly influenced by their usual speeds, even more so than their beliefs regarding what constitutes a safe speed, which may help explain non-compliance with speed limits. No relationship was found between speed choice and risk perception.     

How consumer drivers construe vehicle performance: Implications for electric vehicles

Electric vehicles (EVs) have emerged as potentially important contenders as low carbon vehicles. However from the perspectives of consumer (non-commercial) drivers, all types of EVs have limitations such as short range and higher cost that are significant barriers to widespread uptake. To displace a significant fraction of conventional vehicles, they may need to offer consumer drivers specific advantages that offset these limitations. Better performance might be such an advantage, since electric powertrains can offer performance benefits such as quieter operation and higher torque at low speeds. This qualitative study explored how vehicle performance is construed by consumer drivers, using a repertory grid approach to elicit drivers’ personal constructs. Drivers were found to construe performance in terms of two main dimensions, both situationally specific: dynamic performance (involving acceleration, power, and responsiveness during pulling away, overtaking and hill climbs) and cruising performance (involving smoothness and low noise, during high speed cruising on highways). Users of gasoline fuelled cars emphasised dynamic performance more than did users of diesel fuelled cars, but the opposite was the case for cruising performance. A conceptual model based on the findings could help focus design efforts on those aspects of performance that are most directly salient to drivers.     

碰撞时间估计的影响因素研究

本研究采用遮挡范式,考察了专职公交车驾驶员对不同类型、速度和方向运动物体的碰撞时间(TTC)估计.结果发现,被试对不同类别和速度运动物体的TTC估计有显著差异.这表明,除了视觉信息和物理信息之外,运动物体的概念信息也是影响横向运动TTC估计的重要因素.     

Effects of different non-driving-related-task display modes on drivers’ eye-movement patterns during take-over in an automated vehicle

Highly automated vehicles relieve drivers from driving tasks, allowing them to engage in non-driving-related-tasks (NDRTs). However, drivers are required to take over control in certain circumstances due to the limitations of highly automated vehicles. This study focused on drivers’ eye-movement patterns during take-overs when an NDRT (watching videos) was presented via a head-up-display (HUD) and a mobile device display (MDD), compared to no NDRT as the baseline. The experiment was conducted in a high-fidelity driving simulator with real-world driving videos scenarios. Forty-six participants took part in the experiment by completing three drives in three counterbalanced conditions (HUD, MDD and baseline). A take-over-request was issued towards the end of automated driving requesting drivers to stop the NDRT and take over control. Eye-movement data including pupil diameter, blinks, glance duration and number of AOI (Area of Interest) were collected and analysed. The results show that during automated driving, drivers were more engaged in the MDD NDRT with smaller pupil diameter and shorter glance duration on the front scenario compared to the HUD and baseline modes. The number of AOI was reduced during automated driving in both MDD and HUD modes. The take-over-request redirected drivers’ visual attention back to the driving task from NDRT by increasing drivers’ pupil diameter, glance duration and number of AOI. However, the effect of MDD NDRT on pupil diameter and glance duration continued even after the take-over-request when the NDRT was terminated. The study demonstrated HUD is a better display to help maintain drivers’ attention on the road.     

Analysing the influence of visible roadwork activity on drivers’ speed choice at work zones using a video-based experiment

The present study used a video-based experimental design to investigate the influence of visible roadwork activity on speed preferences at work zones. Four videos from real work zones in Norway were used. Two roadwork areas were filmed at two moments – with and without visible roadwork activity. A total of 815 drivers watched two videos and answered a questionnaire online. Participants stated speed preferences for both videos and then evaluated the influence of 17 common work zone elements on their speed choice. The results showed lower preferred speeds for the videos with visible roadwork activity. The elements considered by drivers to influence their speed included speed regulation (e.g. speed limit signs), transient motives (e.g. time pressure), flow pressure (e.g. speed of the rear driver) and situational conditions (e.g. road situation). Results from the regression analysis showed that visible roadwork activity was the strongest predictor of lower preferred speeds. Speed regulation and transient motives were also significant predictors of preferred speeds. Those who considered speed regulation more important to influence their speed choice at work zones were likely to state lower preferred speeds, while those who considered transient motives as more important were likely to state higher preferred speeds. These findings support the hypothesis that visible roadwork activity is an important factor for lower speed preferences at work zones. The main practical implication is that road authorities should consider various countermeasures to achieve safe driving speeds at work zones, not only roadworks warning signs.     

Drivers’ and cyclists’ safety perceptions in overtaking maneuvers

Drivers overtaking cyclists on rural roads are a safety concern, as drivers need to handle the interaction with the cyclist and possibly an oncoming vehicle. Improving the maneuver’s outcome requires an understanding of not only the objective, measurable safety metrics, but also the subjective, perceived safety of each road user. Previous research has shown that the perceived safety of the cyclist is most at risk at the passing moment, when driver and cyclist are closest to each other. However, to develop safety measures, it is necessary to know how both road users perceive safety, by understanding the factors that influence their perceptions during the overtaking maneuver. This study measured the perceived safety of drivers in a test-track experiment in Sweden and the perceived safety of cyclists in a field test in Spain. For both drivers and cyclists, we developed Bayesian ordinal logistic regression models of perceived safety scores that take as input objective safety metrics representing the different crash risks at the passing moment. Our results show that while drivers’ perceived safety decreases when there is an oncoming vehicle with a low time-to-collision, cyclists’ perceived safety is reduced by a small lateral clearance and a high overtaking speed. Although our datasets are heterogeneous and limited, our results are in line with previous research. In addition, the Bayesian models presented in this paper are novel and may be improved in future studies once more naturalistic data become available. We discuss how our models may support infrastructure development and regulation, policymaking, driver coaching, the development of active safety systems, and automated driving by providing a possible method for predicting perceived safety.     

Stability in drivers' speed choice

Repeated speed measurements were obtained to examine drivers' consistency in speed choice. Drivers were observed at two locations along a route or for two days at the same location. Single carriageway roads were used with posted speed limits of 70 and 90 km/h. Correlation coefficients between repeated speed measures ranged from .49 to .81 for free-flowing vehicles. Higher consistency between measures was found where segments of the road were homogenous. Consistency in relation to speed limit varied as a function of roads and direction of travel. From 4% to 41% of the drivers observed legal speeds at both sites and between 43% and 100% travelled over the speed limits at both sites. The results are discussed in terms of using self-reported speed in driver surveys and modelling of driver behaviour.     

Investigating the impact of a novel active gap metering signalization strategy on driver behavior at highway merging sections

A safe headway to the lead vehicle is important to reduce conflicts with merging vehicles from highway on-ramps. Previous research has outlined the advantage of gap metering strategies to yield sufficient space to merging vehicles and improve highway capacity during peak hours. However, prevailing gap metering systems fail to indicate the minimum required gap and leave it to the drivers’ judgment to adjust their headway. This paper proposes a new Active Gap Metering (AGM) signalization that helps outer lane drivers to adjust their headway to the lead vehicle when approaching highway ramps with incoming vehicles. This AGM signalization represents a combination of pavement markings and an innovative Variable Message Sign (VMS). The AGM system was tested alone and in combination with additional variable speed limits (VSL) in distinct environments of the Doha Expressway in the State of Qatar using a driving simulator. The driving behavior of 64 drivers was analyzed using repeated-measures ANOVA. The results showed that the AGM effectively influenced the drivers’ behavior on the right stream lane. Drivers did gradually increase the distance to the lead vehicle, which resulted in optimal headways to merging on-ramp vehicles. Most importantly, the minimum time-to-collision (TTC_min) to the merging vehicle was increased by an additional 1–1.5 s as compared to no treatment. The proposed AGM signalization can, therefore, be considered by policymakers to influence drivers’ headways at critical merging sections.     

A simulator study of factors influencing drivers’ behavior at traffic lights

Drivers’ reactions to changing traffic lights have an impact on safety at intersections. We examined the influence of transient factors – more specifically time pressure and social context, both conducive to traffic-light violation – on behavior behind the wheel when a traffic light changes. We carried out an experiment on a driving simulator. The participants were 94 car drivers (53 males) with a mean age of 21.7 years. They drove under time pressure vs. no time pressure. At several intersections the participants were alone (no other drivers present), whereas at several other intersections they were behind a line-up of vehicles, the last of which ran the yellow light (other drivers present). As expected, time pressure and social context (presence of other drivers) increased participants’ risky behaviors while approaching, and going through traffic lights, as well as undesirable rapid accelerations when the signal changes to green. The effect of time pressure on yellow-light running was not mediated by approach speed, which showed that participants in a hurry were likely to run lights intentionally. The results are interpreted in view of proposing effective measures for reducing yellow-light running and rapid accelerations at traffic lights.     

Crash avoidance and driver assistance technologies – Are they used?

Crash avoidance technologies have potential to mitigate collisions, and actual crash reductions have been identified for some systems. This study measured observed on-off rates of these technologies as an indicator of use, with a focus on lane maintenance systems (i.e., designed to keep vehicles within lanes by warning, braking, and/or steering) and studied factors that might increase their acceptance and use. Vehicles from nine manufacturers fitted with lane maintenance systems were observed at service departments during 2016. Systems were turned on in 51% of 983 vehicles. The activation rate was higher for systems with braking/steering interventions and vibrating warnings and decreased with total mileage. Large proportions of front crash prevention (93%), blind spot monitoring (99%), rear cross-traffic alert (97%), and driver monitoring alert (90%) systems were enabled, and most optional settings were set to factory defaults. Owner surveys linked to observations showed that drivers who had lane maintenance systems turned off believed warnings were distracting and unnecessary compared with drivers whose systems were on.     

Adaptations in driver deceleration behaviour with automatic incident detection: A naturalistic driving study

Traffic congestion and crash rates can be reduced by introducing variable speed limits (VSLs) and automatic incident detection (AID) systems. Previous findings based on loop detector measurements have revealed that drivers reduce their speeds while approaching traffic congestion when the AID system is active. Notwithstanding these behavioural effects, most microscopic traffic flow models assessing the impact of VSLs do not describe driver response accurately.This study analyses the main factors that influence driver deceleration behaviour while approaching traffic congestion with and without VSLs. The Dutch VSL database was linked to the driver behaviour data collected in the UDRIVE naturalistic driving study. Driver engagement in secondary tasks and glance behaviour were extracted from the video data. Linear mixed-effects models predicting the characteristics of deceleration events were estimated.The results show that the maximum deceleration is high when approaching a slower leader, when driving at high speeds and short distance headways, and close to the beginning of traffic congestion. The minimum time headway is short when driving at high speeds and changing lanes. Certain drivers showed higher decelerations and shorter time headways than others. Controlled for these main factors, smaller maximum decelerations were found when the VSLs were present and visible, and when the gantries were within close proximity. These factors could be incorporated into microscopic traffic simulations to evaluate the impact of AID systems on traffic congestion more realistically. Further research is needed to clarify the link between engagement in secondary tasks, glance behaviour and deceleration behaviour.     

Anger-congruent behaviour transfers across driving situations

Anger and aggression on the road may sometimes appear unprovoked and unrelated to current driving circumstances. It is unclear whether such anger and aggression arises because of events prior to those circumstances in which anger is experienced and aggression is exhibited. In this study, time pressure and enforced following of a slowly moving vehicle were used to increase drivers' anger in order to assess whether affect and behaviour during a subsequent, non-provocative, drive would change accordingly. Ninety-six drivers drove twice in a simulated urban environment. During the first drive, oncoming traffic and a slowly moving lead vehicle required that half of the drivers travelled far slower than they would choose. During the second drive, drivers again followed slower vehicles and were required to respond to traffic events not encountered in the manipulation drive. Mood (Profile of Mood States) was assessed before and after each drive, and anger evaluations, arousal (heart rate) and behaviour (speed, lane position and collisions) were measured during drives. Anger increased and both mood and driving behaviour deteriorated in drivers exposed to slower lead vehicles, compared with control group drivers. These behavioural differences of speed and lane positioning carried over into the subsequent drive even to driving situations unlike those where provocation had previously occurred. Drivers who had previously been impeded later approached hazards with less caution, and attempted more dangerous overtaking manoeuvres. It is concluded that sometimes dangerous driving may result from anger provoked by circumstances other than those in which the behaviour is exhibited.     

Anger-congruent behaviour transfers across driving situations

Anger and aggression on the road may sometimes appear unprovoked and unrelated to current driving circumstances. It is unclear whether such anger and aggression arises because of events prior to those circumstances in which anger is experienced and aggression is exhibited. In this study, time pressure and enforced following of a slowly moving vehicle were used to increase drivers’ anger in order to assess whether affect and behaviour during a subsequent, non-provocative, drive would change accordingly. Ninety-six drivers drove twice in a simulated urban environment. During the first drive, oncoming traffic and a slowly moving lead vehicle required that half of the drivers travelled far slower than they would choose. During the second drive, drivers again followed slower vehicles and were required to respond to traffic events not encountered in the manipulation drive. Mood (Profile of Mood States) was assessed before and after each drive, and anger evaluations, arousal (heart rate) and behaviour (speed, lane position and collisions) were measured during drives. Anger increased and both mood and driving behaviour deteriorated in drivers exposed to slower lead vehicles, compared with control group drivers. These behavioural differences of speed and lane positioning carried over into the subsequent drive even to driving situations unlike those where provocation had previously occurred. Drivers who had previously been impeded later approached hazards with less caution, and attempted more dangerous overtaking manoeuvres. It is concluded that sometimes dangerous driving may result from anger provoked by circumstances other than those in which the behaviour is exhibited.     

Drivers Display Anger‐Congruent Attention to Potential Traffic Hazards

Previous research has suggested that angry drivers may respond differently to potential hazards. This study replicates and extends these findings. Under simulated driving conditions, two groups of drivers experienced conditions that would either increase angry mood (N = 12; men = 6) or not (control group, N = 12; men = 6). All drivers then performed a neutral drive, during which they encountered a number of traffic events not experienced in the initial drive. These included vehicles emerging from driveways into their path and jaywalking pedestrians. Subjective anger, eye‐movement behaviour and driving behaviours (speed and reaction times) were measured as drivers drove. Subjective moods (Profile of Mood States) were assessed before and after each drive. Anger‐provoked drivers reported reliably higher increases in angry mood when compared with the control group after the initial drive, and these increases remained stable across the subsequent neutral drive. During the neutral drive, anger‐provoked drivers demonstrated evidence of more heuristic style processing of potential hazards, with shorter initial gazes at less apparent hazards and longer latencies to look back at jaywalking pedestrians obscured by parked vehicles. Anger‐provoked drivers also took longer to make corrective actions to avoid potential collisions. It is concluded that anger‐provoked drivers may initially make more superficial assessments of certain driving situations and consequently underestimate the inherent risk. Copyright © 2012 John Wiley & Sons, Ltd.     

How do other people influence your driving speed? Exploring the ‘who’ and the ‘how’ of social influences on speeding from a qualitative perspective

Using only legal sanctions to manage the speed at which people drive ignores the potential benefits of harnessing social factors such as the influence of others. Social influences on driving speeds were explored in this qualitative examination of 67 Australian drivers. Focus group interviews with 8 driver types (young, mid-age and older males and females, and self-identified Excessive and Rare speeders) were guided by Akers’ social learning theory (Akers, 1998). Findings revealed two types of influential others: people known to the driver (passengers and parents), and unknown other drivers. Passengers were generally described as having a slowing influence on drivers: responsibility for the safety of people in the car and consideration for passenger comfort were key themes. In contrast, all but the Rare speeders reported increasing their speed when driving alone. Parental role modelling was also described. In relation to other drivers, key themes included speeding to keep up with traffic flow and perceived pressure to drive faster. This ‘pressure’ from others to ‘speed up’ was expressed in all groups and reported strategies for managing this varied. Encouragingly, examples of actual or anticipated social rewards for speeding were less common than examples of social punishments. Three main themes relating to social punishments were embarrassment, breaching the trust of others, and presenting an image of a responsible driver. Impression management and self-presentation are discussed in light of these findings. Overall, our findings indicate scope to exploit the use of social sanctions for speeding and social praise for speed limit compliance to enhance speed management strategies.