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

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

A validation study of driving errors using a driving simulator

BackgroundDriving simulators have become an important research tool in road safety. They provide a safer environment to test driving performance and have the capacity to manipulate and control situations that are not possible on-road.AimTo validate a laboratory-based driving simulator in measuring on-road driving performance by type and mean driving errors.MethodsParticipants were instructed to drive a selected route on-road. The same route was programmed in the driving simulator using the UC/Win-road software. All participants completed a background questionnaire. On-road driving behaviours of participants and driving behaviours in the simulator were assessed by an occupational therapist and two trained researchers using an assessment form. Interclass correlations were calculated to assess the inter-rater agreement between the researchers on driving behaviours. Paired t-tests were used to assess differences in driving performance between the simulator and on-road assessments.ResultsA convenience sample of 47 drivers aged 18–69 years who held a current Western Australian class C licence (passenger vehicle) were recruited into the study. The mean age was 34.80 years (SD: 13.21) with twenty-six males (55.32%) and 21 females (44.68%) completing the study. There was no statistical difference between the on-road assessment and the driving simulator for mirror checking, left, right and forward observations, speed at intersections, maintaining speed, obeying traffic lights and stop signs.ConclusionThe preliminary results provide early support for the relative validity of the driving simulator which may be used for a variety of road safety outcomes with reduced risk of harm to participants.     

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.     

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

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

Diverging diamond interchanges: A driving simulator study

This study assessed driver performance while navigating a Diverging Diamond Interchange (DDI) compared to a standard intersection in a driving simulator. A total of 201 Western Australian (WA) drivers aged 18–80 years completed the simulator drive and questionnaire. Measures of driving simulator performance assessed included time spent out of lane, number of lane excursions, compliance to the speed limit, crashes and near misses. Other driving measures, which were recorded by the researcher, included driver errors/violations such as red-light violations, wrong way violations and navigation errors. Qualitative information was also obtained in a post exit interview with each participant regarding the difficulties they experienced when driving through the DDI. A repeated-measure analysis of variance (r-ANOVA) was undertaken to examine differences in intersection type (DDI versus standard intersection) and driving performance measures from the driving simulator. The only significant result was compliance to the speed limit (F (1, 656) = 160.11, p < 0.001) on the driving simulator. A higher proportion of red-light violations were observed by the researcher as participants navigated through the DDI, compared to the standard intersection. Qualitative comments from participants also highlighted the need for better signage and road markings. Recommendations when DDIs are implemented include community education on speed limit compliance, avoidance of red-light violations and design improvements regarding signage and road markings.     

Effect of chevron design on driver behaviour when encountering and passing through a dangerous curve

Horizontal curves are locations on the road network with a high road accident risk. In order to provide drivers with timely and proper information about the upcoming curve, road authorities often use chevron signs. Although the main design of chevrons is similar in most countries (one colour for the background and another for the arrow), the combination of colours differs. The aim of this simulator study is to investigate how different colour combinations affect drivers when they encounter and drive through horizontal curves on rural roads at daytime. Overall, each of the tested chevrons reduced the driving speed (between 25 and 29 km/h), although not to the speed limit level (60 km/h). However, for curves marked with chevrons with fluorescent or white background the driving speed was the lowest at all measuring points, regardless of the curve direction. The observation of lateral movement shows that there are no significant differences in the way the vehicle is positioned when approaching and driving through curves marked with different chevrons. Based on the obtained results, practical recommendations and potential future research activities are presented.     

Car following with an inertia-oriented driving technique: A driving simulator experiment

BackgroundFor many decades, car-following (CF) and congestion models have assumed a basic invariance: drivers’ default driving strategy is to keep the safety distance. The present study questions that Driving to keep Distance (DD) is a traffic invariance and, therefore, that the difference between the time required to accelerate versus decelerate must necessarily determine the observed patterns of traffic oscillations. Previous studies have shown that drivers can adopt alternative CF strategies like Driving to keep Inertia (DI) by following basic instructions. The present work aims to test the effectiveness of a DI course that integrates 4 tutorials and 4 practice sessions in a standard PC computer designed to learn more adaptive driving behaviors in dense traffic. Methods. Sixty-eight drivers were invited to follow a leading car that varied its speed on a driving simulator, then they took a DI course on a PC computer, and finally they followed a fluctuating leader again on the driving simulator. The study adopted a pretest-intervention-posttest design with a control group. The experimental group took the full DI course (tutorials and then simulator practice). The control group had access to the DI simulator but not to the tutorials. Results. All participating drivers adopted DD as the default CF mode on the pre-test, yielding very similar results. But after taking the full DI course, the experimental group showed significantly less accelerations, decelerations, and speed variability than the control group, and required greater CF distance, that was dynamically adjusted, spending less fuel in the post-test. A group of 8 virtual cars adopting DD required less space on the road to follow the drivers that took the DI course.     

Safety implications of co-locating road signs: A driving simulator investigation

BackgroundAs road complexity increases the requirement for number of road signs also increases, although the amount of road side space does not. One practical strategy to address this is to present multiple road signs on the same gantry (sign co-location). However, there is very little research on the safety implications of this practice.Method36 participants (mean age = 42.25 years, SD = 13.99, 18 females) completed three driving simulator scenarios, each scenario had a different sign co-location condition: no co-location, dual co-location and triple co-location. Each scenario presented similar information using direction signs, variable message signs and variable speed limit signs, under. Each drive included standard motorway driving (100 km/h speed zone) in free flow traffic and one emergency event where a lead vehicle suddenly braked. The scenario order was counterbalanced and the emergency event vehicle varied.ResultsOverall, there was no impact of co-locating signs on general driving performance. No significant difference was observed between conditions for reaction time and minimum headway in response to the emergency event. Participants were able to correctly choose their destination whether the signs were co-located or not.DiscussionFor the particular configuration of signs tested there is no evidence that co-location negatively impacts driving performance. However, there may be some implications for travel speed and the manner in which the emergency event is responded to. Future work should confirm the findings on real roads. These findings provided support for sign co-location as a practical and safe option for displaying multiple road signs in a confined area.     

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

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

Measuring being lost in thought: An exploratory driving simulator study

In driver behaviour research there is considerable focus on distraction caused by specific external systems, such as navigation systems or mobile telephones. However, it is not clear whether self-paced actions such as daydreaming have the same negative effects on driving behaviour. In a driving simulator study, the effects of an internal cognitive process (internal distraction) on driving behaviour and physiological data were compared to the effects of a sound and speech task (external distraction). Three groups of participants made two drives on a motorway, with one control group, one internal distraction group and one external distraction group. Dependent measures included driving behavioural measures, physiological measures and a subjective indication of participants’ experienced involvement in the driving task.The effects of both the internal and external distraction task were reflected in speed, number of lane changes, deceleration, glances and subjective ratings. When an effect was found for both the internal and the external distraction task, the results indicated similar (negative) effects. Participants also indicated that they had the feeling they were less involved in the driving task with both secondary tasks.     

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

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

Effects of hands-free cellular phone conversational cognitive tasks on driving stability based on driving simulation experiment

Driver distraction due to cellular phone usage is a major contributing factor to road crashes. This study compares the effects of conversational cognitive tasks using hands-free cellular phone on driving performance under three distraction conditions: (1) no distraction (no cellular conversation), (2) normal conversation (non-emotional cellular conversation), and (3) seven-level mathematical calculations. A car-following scenario was implemented using a driving simulator. Thirty young drivers with an average age of 24.1 years maintained a constant speed and distance between the subject vehicle and a leading vehicle on the driving simulator, and then respond to the leading vehicle’s emergency stop. The driving performances were assessed by collecting and statistically analyzing several variables of maneuver stability: the drivers’ brake reaction times, driving speed fluctuation, car-following distance undulation, and car-following time-headway undulation. The results revealed that normal conversation on a hands-free cellular phone impaired driving performance. The degree of impairment caused by normal calculation was equivalent to the distraction caused by Level 3 mathematical calculations according to the seven-level calculation baseline. The calculation difficulty of Level 3 is one double-digit figure plus a single-digit figure, and non-carry addition mental arithmetic is required, e.g., 44 + 4. The results indicated that an increase in the level of complexity of the calculation task was associated with an increase in brake reaction time. The seven-level calculation-task baseline could be applied to measure additional distraction effects on driving performance for further comparison.     

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

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

Estimating effectiveness of speed reduction measures for pedestrian crossing treatments using an empirically supported speed choice modeling framework

Pedestrian crossing treatments, such as Pedestrian Hybrid Beacons (PHBs) and Rectangular Rapid-Flashing Beacons (RRFBs), are traffic control devices implemented to help pedestrians safely cross busy or higher-speed roadways at midblock crossings and uncontrolled intersections. This study aims to assess the effectiveness of the PHB and RRFB by analyzing drivers’ speeding behavior under different roadway types with real-life traffic conditions. In order to understand the effect of pedestrian crossing treatments (i.e., PHB and RRFB) have on drivers’ speeding behavior, this paper analyzes four zones (i.e., one upstream zone and three consecutive downstream zones). For the four analysis zones, different indexes were computed which corresponds to the differences in drivers’ speed when encountered with the pedestrian crossing treatments. A grouped random effect hurdle beta regression model is estimated for the indexes, with a fixed effect hurdle beta model used for comparison and validating the importance of considering the grouped random heterogeneity across participants. The proposed analysis framework was validated by the means of an empirical driving simulator study, based on two urban roads in the Central Florida region, North Alafaya Trail (SR-434) and South Orange Blossom Trail (US-441). The results revealed that the proposed modeling framework reflects drivers’ difference in speed for the different pedestrian crossing treatments. The results suggest that with proper understanding of the PHB, the PHB can reduce drivers speed even beyond the location of the PHB. Meanwhile, the RRFB does have some effect in speed reduction beyond the location of the RRFB, however many drivers failed to acknowledge the RRFB. It is suggested that when drivers’ have proper education on the use of the PHB to reduce speed safely and for the installation of RRFB be on roads with two or less lanes and a speed limit less than 40 mph. While the main purpose of the pedestrian crossing treatments is to help pedestrians cross safely, speed reduction can be considered a byproduct as revealed in this study.     

Identification of driving simulator sessions of depressed drivers: A comparison between aggregated and time-series classification

Depression has been found to significantly increase the probability of risky driving and involvement in traffic collisions. The majority of studies correlating depressive symptoms with driving, pursue to predict the differences in driving behavior if the driver has already been diagnosed. Little evidence can be found, however, on how mental and psychological disorders can be identified from driving data, and usually analyses utilize simple models and aggregated data. This study aims at utilizing microscopic data from a driving simulator to detect sessions belonging to “depressed” drivers by utilizing powerful machine learning classifiers. Driving simulator sessions from 11 older drivers with symptoms of depression and 65 healthy drivers were utilized towards that aim. Random Forests, an ensemble classifier, with proven efficiency among transportation applications, are then trained on highly disaggregated data describing the mean and standard deviation of speed and lateral or longitudinal acceleration of drivers in the simulator. The kinematic data were aggregated in 30-seconds, 1-minute and 5-minute intervals, but the corresponding time-series of the measurements were also taken into account. Furthermore, classifiers were treated with imbalanced learning techniques to address the scarcity of depressed drivers among the healthy. Time-series of mean speed and the standard deviation of longitudinal acceleration even with a duration of 30-seconds have proven to be the best predictors of driving sessions belonging to depressed drivers with a very low rate of false alarms. The results outperform previous approaches, and indicate that naturalistic driving data or deep learning could prove even more efficient in detecting depression.     

Priority rule signalization under two visibility conditions: Driving simulator study on speed and lateral position

In literature, priority-controlled and right-hand priority intersections have rarely been compared on other elements than the number of right-of-way violations and collisions. This study investigates the effect on speed and lateral position of five priority rules under two visibility conditions at an intersection (without hierarchy between branches), which is, at this moment, a knowledge gap.Fifty participants drove five different routes in a simulator and were exposed to the following manipulations: priority to the right rule applying and indicated (road sign and road sign with road marking), priority to the right rule applying but not indicated (no sign), priority to the right rule not applying and indicated (priority road and priority at next intersection), under good and bad visibility.Results show a significant speed decrease for both situations where the priority to the right rule was indicated compared to situations with no priority to the right rule, especially when visibility was bad. Priority to the right signs with additional road marking resulted in lowest speed under both visibility conditions. For all priority rules, lateral position shifted more towards the middle of the road when visibility was bad.Since speed was higher in case of priority roads or roads with priority at next intersection, it can be concluded that a higher level of control (priority-controlled intersections) does not necessarily result in a traffic safety improvement. Therefore, policy makers should take into account the results of this study and not generally change all the priority to the right intersections by priority-controlled intersections.     

The ability of young,middle-aged and older drivers to inhibit visual and auditory distraction in a driving simulator task

Driver distraction is one major cause of road traffic accidents. In order to avoid distraction-related accidents it is important to inhibit irrelevant stimuli and unnecessary responses to distractors and to focus on the driving task, especially when unpredictable critical events occur. Since inhibition is a cognitive function that develops until young adulthood and decreases with increasing age, young and older drivers should be more susceptible to distraction than middle-aged drivers. Using a driving simulation, the present study investigated effects of acoustic and visual distracting stimuli on responses to critical events (flashing up brake lights of a car ahead) in young, middle-aged, and older drivers. The task difficulty was varied in three conditions, in which distractors could either be ignored (perception-only), or required a simple response (detection) or a complex Go-/NoGo-response (discrimination). Response times and error rates to the critical event increased when a simultaneous reaction to the distractor was required. This distraction effect was most pronounced in the discrimination condition, in which the participants had to respond to some of the distracting stimuli and to inhibit responses to some other stimuli. Visual distractors had a stronger impact than acoustic ones. While middle-aged drivers managed distractor inhibition even in difficult tasks quite well (i.e., when responses to distracting stimuli had to be suppressed), response times of young and old drivers increased significantly, especially when distractor stimuli had to be ignored. The results demonstrate the high impact of distraction on driving performance in critical traffic situations and indicate a driving-related inhibition deficit in young and old drivers.     

A simulation sickness study on a driving simulator equipped with a vibration platform

Simulator sickness is a well-known side effect of driving simulation which may reduce the passenger well-being and performance due to its various symptoms, from pallor to vomiting. Numerous reducing countermeasures have been previously tested; however, they often have undesirable side effects. The present study investigated the possible effect of seat vibrations on simulator sickness. Three configurations were tested: no vibrations, realistic ones and some that might affect the proprioception. Twenty-nine participants were exposed to the three configurations on a four-minute long automated driving in a simulator equipped with a vibration platform. Simulator sickness was estimated thanks to the Simulator Sickness Questionnaire (SSQ) and to a postural instability measure. Results showed that vibrations help to reduce the sickness. Our findings demonstrate that some specific vibration configurations may have a positive impact on the sickness, thus confirming the usefulness of devices reproducing the road vibrations in addition to creating more immersion for the driver.     

Valid representation of a highly dynamic collision avoidance scenario in a driving simulator

In Germany the second-most frequent accidents in road traffic are rear-end collisions. For this reason rear-end collisions are quite important for accident research and the development of driving safety systems. To examine the functionality and to design the human–machine-interface of new driving safety systems, especially in the early development phase, subject tests are necessary. Because of the great hazard potential of such safety critical scenarios for the test persons, they are often conducted in a driving simulator (DS). Accordingly, validity is an important qualification to ensure that the findings collected in a simulated test environment can be directly transferred to the real world.This paper regards the question of driving behavior validity of DS in critical situations. There are hardly any validation studies which analyze the driving behavior in a specific collision avoidance situation.The validation study described in this paper aims to evaluate the behavioral validity of a fixed-base simulator in a collision avoidance situation. For this reason a field study from 2007 was replicated in a fixed-base simulator environment.The main questions of this validation study were if the driver can notice an active hazard braking system and if the driving behavior in a static simulator can be valid in such a critical situation.The key finding of the study states that there is no driving behavior validity in a static driving simulator for the tested dynamic scenario. The missing vestibular feedback causes a different behavior of the participants in field and simulator. The resulting absence of comparability leads to non-valid performance indicators. But these indicators are key parameters for analyzing the function and acceptance of active braking systems. So the question arises, which motion performance does a motion base have to provide in order to achieve valid acceleration simulation of such a highly dynamic collision avoidance scenario. The DS’s performance is measured in workspace, velocity and acceleration.