Driver Reaction Time Research Articles

Automated Driving: A Literature Review of the Take over Request in Conditional Automation

In conditional automation (level 3), human drivers can hand over the Driving Dynamic Task (DDT) to the Automated Driving System (ADS) and only be ready to resume control in emergency situations, allowing them to be engaged in non-driving related tasks (NDRT) whilst the vehicle operates within its Operational Design Domain (ODD). Outside the ODD, a safe transition process from the ADS engaged mode to manual driving should be initiated by the system through the issue of an appropriate Take Over Request (TOR). In this case, the driver’s state plays a fundamental role, as a low attention level might increase driver reaction time to take over control of the vehicle. This paper summarizes and analyzes previously published works in the field of conditional automation and the TOR process. It introduces the topic in the appropriate context describing as well a variety of concerns that are associated with the TOR. It also provides theoretical foundations on implemented designs, and report on concrete examples that are targeted towards designers and the general public. Moreover, it compiles guidelines and standards related to automation in driving and highlights the research gaps that need to be addressed in future research, discussing also approaches and limitations and providing conclusions.

IMPACT OF ROAD TRAFFIC ON DRIVER REACTION TIME

The main problem of driving safety in the dark for drivers is the recognition of elements of the traffic situation. Changes in the characteristics of visual perception are due to changes in illumination, brightness of the color contrast of important and significant for the driver stimuli during movement. It is the recognition of existing obstacles in terms of contrast and brightness that is the biggest problem for drivers. When driving at night, drivers are prone to dazzle, they are less able to distinguish colors, and the field of view is significantly reduced. The availability of technical means for regulating traffic in accordance with road conditions and pedestrian traffic in the dark are the main means that allow the driver to navigate while driving. The driver's reaction time to the appearance of danger is decisive in the event of conflict situations in the dark. Driver reaction time is an important indicator of road safety. The reaction time is constantly changing and depends on many factors of working conditions, the functional state of the driver. Working conditions cause fatigue and emotional stress. The change in reaction time depends on the state of health, the intake of certain medications, the state of drug and alcohol intoxication, etc. In addition, a person's age, gender and experience also affect the reaction time. A simpler and more effective method for studying the distribution of reaction time and patterns of change is the use of an individual car with recording equipment. It has been proven that car drivers can keep their distance, brake synchronously and maintain braking force in accordance with the leading car braking and being in front. Therefore, to study the parameters of movement along the route, we used the device racelogic "VideoVbox". Experimental studies on city streets at night have been carried out, have shown the relationship between the driver's reaction time and traffic conditions. The study involved drivers between the ages of 20 and 40. As a result, regularities were obtained for the change in the reaction time under different lighting conditions and the traffic load factor of the streets. It has been found that with a low load factor, the driver is more likely to be distracted and has a worse reaction time. The optimal load for the driver is a load factor ranging from 0.35-0.55 with the best response times. The constructed model of the driver's reaction time can be used in expert practice to establish the circumstances of the occurrence of road accidents.

Predicting driver reaction time and deceleration: Comparison of perception-reaction thresholds and evidence accumulation framework

Prediction of driver reaction to the lead vehicle motion based on the perception-reaction time (PRT) is critical for prediction of rear-end crash risk. This study determines PRT at various spacings in approaching and braking conditions, and examines the association of PRT and deceleration rate with crash risk. For these tasks, a total of 50 drivers’ behavior was observed in a driving simulator experiment with 4 different scenarios – reaction to a decelerating lead vehicle, reaction to a stopped lead vehicle, perception of a lead vehicle’s speed change, and perception of a slow-moving lead vehicle. The study tested three hypotheses of PRT including perception and reaction thresholds and the evidence accumulation framework using a visual variable (tau-inverse). It was found that the drivers neither reacted after a specific PRT from the start of perception nor reacted at a specific value of tau-inverse. Rather, the drivers generally reacted when the accumulation of evidence (tau-inverse) over time reached a threshold. It was also found that the magnitude of deceleration rate depends on the tau-inverse at the start of braking and hence, higher crash risk was associated with higher level of urgency and insufficient brake force rather than longer PRT. This study demonstrates that the evidence accumulation framework is a promising method of predicting driver reaction in approaching and braking conditions for different types of lead vehicle, and the level of urgency is important for predicting the probability of crash.

The impact of auditory continual feedback on take-overs in Level 3 automated vehicles

ObjectiveTo implement auditory continual feedback into the interface design of a Level 3 automated vehicle and to test whether gaze behavior and reaction times of drivers improved in take-over situations. BackgroundWhen required to assume manual control in take-over situations, drivers of Level 3 automated vehicles are less likely than conventional drivers to spot potential hazards, and their reaction time is longer. Therefore, it is crucial that the interface of Level 3 automated vehicles will be designed to improve drivers’ performance in take-over situations. MethodIn two experiments, participants drove a simulated route in a Level 3 automated vehicle for 35 min with one imminent take-over event. Participants’ gaze behavior and performance in an imminent take-over event were monitored under one of three auditory interface designs: (1) Continual feedback. A system that provides verbal driving-related feedback; (2) Persistent feedback. A system that provides verbal driving-related feedback and a persistent beep; and (3) Chatter feedback. A system that provides verbal non-driving-related feedback. Also, there was a control group without feedback. ResultsUnder all three auditory feedback designs, the number of drivers' on-road glances increased compared to no feedback, but none of the designs shortened reaction time to the imminent event. ConclusionIncreasing the number of on-road glances during automated driving does not necessarily improve drivers’ attention to the road and their reaction times during take-overs. ApplicationPossible implications for the effectiveness of auditory continual feedback should be considered when designing interfaces for Level 3 automated vehicles.

Implications of Crashes Involving Roadway Objects for Machine Vision-Based Driving Systems

Crashes involving roadway objects can cause severe injuries and property damage. Utilizing data from the Second Strategic Highway Research Program (SHRP 2) naturalistic driving study (NDS), this study investigated crashes involving roadway objects and their implications for the potential of machine vision-based driving systems in preventing such crashes. A comprehensive statistical and machine learning analysis was first conducted to identify major factors affecting the occurrence and severity of such events. Machine vision performance metrics (based on the SHRP 2 NDS cameras) and human driving decisions were then analyzed to identify opportunities where machine vision systems could particularly mitigate risk factors. The results suggest that driver behaviors/errors, speed, reaction time, and object characteristics played the most significant role in the occurrence and severity outcome of the SHRP 2 events. The average object detection distance based on the SHRP 2 cameras was approximately 20 m for all objects. The average reaction time provided by the SHRP 2 cameras was 1.5 s for all events but 1.1 s for events involving animals and roadway debris. In general, the machine vision reaction time was longer than the driver reaction time for approximately 95% of all analyzed events and 75% of the events in which drivers reacted before collisions. Drivers were able to make safe evasive maneuvers in 56% of all analyzed events and 72% events involving roadway debris and animals. Based on these results, the paper discusses in detail when and how machine vision systems could assist in preventing crashes involving roadway objects.

The Permitted Dimension of Guide Sign in Freeway Tunnel Restricted by the Geometric Space of the Tunnel Vault

Traffic guide signs should be settled in a freeway tunnel when there is a short distance between the interchange exit ramp and the tunnel exit in order to provide enough reaction time for drivers. However, there is not enough space for guide sign in a tunnel adopting the same design method as the guide sign along the general segment of the freeway. The maximum dimension of a guide sign in tunnel should be studied firstly. Based on the analysis of the characteristics of the inner outline design of the tunnel and its relationship with the guide sign dimension, the study was classified into different combination conditions: left superelevation and right superelevation under two-, three-, or four-lane freeway tunnels, respectively. The essential elements, the horizontal and vertical clearances, the radius of the tunnel vault circles, the angle of the superelevation, and the allowance vertical dimension for future sign installation were all taken into account to establish the dimension model of the guide sign in the tunnel. The maximum dimensions of the guide signs were proposed under different combination conditions. The results indicated that there is only one set of the width and the height to obtain the maximum area of the guide sign in the freeway tunnel. The height of the guide sign reduces with the increase of its widths, and the area of the guide sign increases and then reduces with the increase of its width under the same grade of superelevation. The changing trend and extent of the dimension of the guide sign under left superelevation condition were different from those under right superelevation.

The effects of aging and driving experience on reaction times of professional drivers.

Professional drivers are part of the active working population, so there is a need for continuous improvement of operating efficiency and safety in driving. Reaction time is a very important driver's trait. The aim of this study was to examine the effects of age and driving experience on reaction times of professional drivers. This study assesses part of driving efficiency of professional drivers by measuring simple reaction time and complex reaction time which are important to driving safety. Reaction times of 278 male professional drivers were tested using a hardware-software system for determining the speed of response to psychomotor simple and complex audio-visual stimuli. Our results showed a positive correlation between ageing and slowing of reaction times. This suggests that the natural ageing process clearly slows down reaction times. The response times of professional drivers are more dependent on age than on driving experience.

Normal and risky driving patterns identification in clear and rainy weather on freeway segments using vehicle kinematics trajectories and time series cluster analysis

Enhancing traffic safety on freeways is the main goal for all transportation agencies. However, to achieve this goal, many analysis protocols of network screening models need to be improved through considering human factors while analyzing traffic data. This paper introduces one on the new analysis protocol of identifying and discriminating between normal and risky driving in clear and rainy weather. The introduced analysis protocol will consider the effect of human factors on updating the networking screening process of identifying hotspots of crash risk. This paper employs the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) data to investigate the behavior of normal and risky driving under both rainy and clear weather conditions. Near-crash events on freeways, which were used as Surrogate Measure of Safety (SMoS) for crash risk, were identified based on the changes in vehicle kinematics, including speed, longitudinal and lateral acceleration and deceleration rates, and yaw rates. Through a trajectory-level data analysis, there were significant differences in driving patterns between rainy and clear weather conditions; factors that affected crash risk mainly included driver reaction and response time, their evasive maneuvers such as changes in acceleration rates and yaw rates, and lane-changing maneuvers. A cluster analysis method was employed to classify driving patterns into two clusters: normal and risky driving condition patterns, respectively. Statistical results showed that risky driving patterns started on average one second earlier in rainy weather conditions than in clear weather conditions. Furthermore, risky driving patterns extended in average three seconds in rainy weather conditions, while it was two seconds in clear weather conditions. The identification of these patterns is considered as a primary step towards an automated development that would distinguish between different driving patterns in a Connected Vehicle CV environment using Basic Safety Messages (BSM) and to enhance the network screening analysis for increased crash risk hotspots. • This study showed how driver compensates differently according to weather conditions to avoid crash event. • This study provided a discrimination threshold between normal and risky driving patterns in both rainy and clear weather conditions. • This study showed how the trajectory analysis helped in better discriminating driving patterns during a specific event. • The usage of an advanced machine learning classification method helped in detecting risky driving patterns more efficiently. • It was found that using a cluster analysis helped in detecting the risky driving pattern over the whole events. • The cluster analysis succeeded to provide results in the same context as the trajectory analysis.

Visual reaction time of drivers versus healthy adults: a comparative study

Introduction: Driving is a highly demanding profession requiring heightened alertness while remaining in an ergonomically constrained position and also associated with exposure to vehicular pollution and whole body vibration. We explored whether drivers’ reaction time is different to student group who also remain in sitting position for long hours but not exposed to other factors.
 Materials and methods: Drivers with at least one year of occupational history and under/post-graduate students were randomly selected. Their reaction time in seconds (RT) was measured by the ruler drop method (RDM) and compared with independent t test. Right vs left hand RTs were compared within groups by paired t test.
 Results: Thirty students (21.8±2.25 years) and 37 drivers (33.73±9.77 years) participated in the study. The drivers had RT of 2.03±0.2s on both the hands; students’ RT were 2.01±0.16s on right and 2.02±0.17s on left hands. For both hands, the differences were not significant between drivers and students (p>0.5). Right and left RT were also comparable for both groups (p>0.5).
 Conclusions: Bus drivers with at least one year occupational exposure have reaction times ruler drop stimulus not significantly different from controls (students).

System-Level Reliability Analysis of Cooperative Driving with V2X Communication for Intersection Collision Avoidance

Cooperative driving with vehicle-to-everything (V2X) communication is a promising technique to improve traffic safety and efficiency. Intersection collision avoidance (ICA) is a typical safety application of it. This paper analyzes reliability of ICA with cooperative manual driving at the system level. First, the reliability of an ICA system is defined as the probability of the ICA system avoiding collisions or near-misses at intersections without failure under conditions that collisions or near-misses are about to happen. Post-encroachment time is used in the expression of this definition. Then, components of the ICA system are classified into four types: hardware, software, maneuver, and V2X communication, and a reliability block diagram (RBD) is applied to reveal how these components contribute to system reliability. Five ICA system patterns with different V2X communication modes and strategy types are compared based on RBD analysis. This shows that centralized strategies are more reliable than decentralized ones for V2I communication if software reliability of these two strategies is the same. Furthermore, reliabilities of ICA components are analyzed in detail, and they are classified into two categories based on their different impact modes on the system. Finally, a numerical example shows how to test reliability of an ICA system using reliabilities of its components by Monte Carlo simulation. Results show that closer distances from vehicles to their conflict point when alerted, longer driver reaction time, and smaller vehicle deceleration rates are more likely to lead to system failure, whereas communication latency has little effect on it.

Gender differences in driving control of young alcohol-impaired drivers

BackgroundMale and female drivers exhibit different degrees of vehicle control while driving under the influence of alcohol. However, this interaction between alcohol and gender is understudied. The present study examined the effects of different alcohol levels on the driving control of male and female drivers with the help of driving simulator experiments in heterogeneous traffic conditions. MethodForty young drivers (20 males and 20 females) completed simulated driving at four Blood Alcohol Concentration (BAC) levels: 0% (control), 0.03%, 0.05% and 0.08%. Driving impairment in vehicle control was measured in terms of average speed, acceleration variability and reaction time of drivers. Repeated-measures ANOVA tests were conducted and regression models were developed for male and female drivers to quantify the effects of BAC levels and driver characteristics on the driving control measures. ResultsSignificant effects of gender were observed for average speed (p < 0.001) and acceleration variability (p = 0.015) but not for reaction time of drivers (p = 0.891). Further, the effect of BAC was significant in all the three measures of vehicle control (p < 0.001). Driving control improved with increasing age of male drivers while caffeine consumption was observed as an alcohol-antagonizing factor in female drivers. ConclusionThe findings suggest that vehicle control of female drivers is more likely to get affected even at low BAC levels, providing evidence that they belong to critical section of driving community in terms of alcohol-related impairment. The findings may help in discouraging drinking and driving among male and female drivers.

Modelling the influence of time pressure on reaction time of drivers

Speeding is a major traffic violation and time pressure is one of the leading contributors to speeding. High-speed driving requires an immediate response to perilous events from the driver to avoid a crash. Reaction time is one of the important driving performance measures to assess the driver’s response to the event. Therefore, the current study examined the influence of time pressure on reaction times of the drivers measured for two different perilous events (pedestrians crossing and obstacle overtaking). Eighty-five Indian licensed drivers participated in a driving simulation study designed for three different time pressure conditions: No Time Pressure (NTP), Low Time Pressure (LTP), and High Time Pressure (HTP). The survival analysis technique was used to model the effect of time pressure and driver characteristics with reaction times of the drivers. It was observed that drivers’ reaction times decreased by 18% and 9% in LTP and 28% and 16% in HTP during the pedestrians crossing and obstacle overtaking events, respectively. Further, 1 m/second increase in approach speed resulted in 2% and 4% reduction in reaction times of the drivers in pedestrians crossing and obstacle overtaking events, respectively. Young drivers responded 21% faster than mature drivers during the pedestrians crossing event. Interestingly, sleeping hours and physical fitness played an important role in driver’s reaction to the events. The drivers performing regular physical exercise and having minimum eight-hours of overnight sleep reacted 16% and 17% earlier in pedestrians crossing and obstacle overtaking events, respectively. The overall findings from this study showed enhanced stimulus-response behaviour of the drivers under time pressure driving conditions. The results obtained from the study can give new insight into various safety-related ITS applications.

Modelling fundamental diagrams according to different water film depths from the perspective of the dynamic hydraulic pressure

In this paper, we propose enhanced fundamental diagrams based on different water film depths by considering the effects of hydroplaning using a physical method. Various factors are calculated to describe the total safe distance headway of main vehicle components. These factors include the driver reaction times, reaction distances, vehicle braking times, and vehicle braking distances corresponding to different water film depths. An excellent match is found between the computed braking distance, the braking time calculated using the proposed numerical model, and the results published in other papers. These calculations are performed to estimate the distance headway and quantitatively analyse the relationships between the speed, density, and water film depth. By using three road-specific parameters estimated by our proposed model, namely, the free-flow speed, jam density, and capacity flow, a link transmission model is developed to analyse the dynamic impact of the water film depth.

Cardiorespiratory fitness and sex assigned at birth contribute to brake reaction time in older adults

IntroductionAge-related increases in reaction time (RT) are pervasive. Driver RT is a crucial component of roadway safety. Superior cardiorespiratory fitness (CRF) is associated with faster RTs on a variety of behavioral tasks. Driver RT, as with any RT measure, is comprised of constituent components that contribute to a total response time (TT). Simple RT (sRT) is comprised of the requisite sensory and central processing of TT. Movement time (MT) is comprised of the requisite movement of a particular behavioral response (e.g., moving your foot from the accelerator to the brake pedal). This study aimed to determine the strongest predictor of constituent components of driver RT on a brake onset test. MethodsCross-sectional analysis. Predictor variables included CRF, age and sex. Participants were 50 community-dwelling older adults between the ages of 60 and 77 (mean age = 66.5 years, SD = 4.1). Maximal graded exercise tests were used to assess CRF. A driving simulator was used to assess constituent components of driving-related RT. Results: Findings indicated that CRF was the largest contributor to sRT variance (beta = −0.35, p = 0.03). Sex was the largest contributor to MT (beta = −0.44, p = 0.003) and TT (beta = −0.28, 0.05) variance.CRF also demonstrated a marginal contribution to TT variance (beta = −0.25, p = 0.08). Age did not significantly contribute to sRT, MT or TT. ConclusionsAge-related increases in RT can jeopardize roadway safety. Findings from this study demonstrate that a modifiable lifestyle variable may have the ability to reduce roadway risk by improving constituent components of driver RT.

Change of driver's reaction time depending on the amount of alcohol consumed by the driver - the case study

Each driver should drive according to the actual road traffic rules of the country in which is he currently located. The law systems of various states of Europe allow an increased maximal blood alcohol level of driver. As the fact that no small number of road accidents is caused because of the influence of alcohol on the driver, it is necessary to focus the attention of the society on this issue. The paper deals with the influence of alcohol to change of the reaction time of the driver. During the project of the alcohol effect on the driver and its behaviour, the reaction time of several drivers of a selected group of people was measured. At first (before alcohol drinking) it was assessed the physical and mental condition of the drivers, using a series of question. Subsequently were carried out the measurements by car with sober driver. After this initial measurement the driver began to drink an alcohol and after 20 minutes the level of alcohol in driver´s breath was determined by certificated equipment. After finding of this value was the driver re-tested by the car, where he had to stop the vehicle before simulated barrier. During the tests the stopping distance, the mean fully developed deceleration was explored as the supporting variables. As the most important variable was the driver´s reaction time. It was researched by using of the video-analysing from two synchronized cameras. The aim of this paper is to focus on the fact that there is a dependence between the amount of consumed alcohol and the driver´s reaction time, which significantly affects the road safety. The reaction time of the driver directly influences to the stopping distance thus it is resolute for stopping the vehicle before a barrier

Drivers ’reaction time research in the conditions in the real traffic

Abstract The article presents the results of research on the total reaction time of drivers in real traffic conditions. The tested driver had to react to a complex signal by performing a braking manoeuvre. The measurements were based on the author’s method combining the measurements of reaction time during the actual driving with their computer analysis. The research group consisted of 15 drivers with different seniority of driving licences. The study measured the time of perception and the time of leg transfer from the accelerator pedal to the brake pedal. The results were subjected to analysis and on its basis conclusions were formulated.

Olfactory Facilitation of Takeover Performance in Highly Automated Driving

This study aims to quantify the impact of olfactory stimulation and takeover modality on the performance of takeovers in conditionally automated driving. Takeover requests are important for the safety of automated vehicles. The reaction time and subsequent performance of drivers in the takeover process are crucial for safety. In this study, peppermint was adopted as an auxiliary modality to the tactile and auditory design of takeover requests. Sixty participants took part in the experiment, which required participants to avoid a stalled vehicle after they were awoken from a state of light sleep by a takeover request. Takeover modality (tactile, auditory, and combined) was the within-subjects factor. In the between-subjects design, half of the participants received a peppermint odor stimulation when the takeover request occurred, and the other half received a placebo (air). The presence of peppermint odor did not influence the reaction time, but participants did show signs of being more alert afterwards. For the moment of takeover, use of the auditory modality had a significant positive effect on reaction time compared to the tactile conditions. Peppermint odor had a positive impact on drivers' takeover quality when engaged in nondriving-related activities such as light sleep, and the takeover request modalities were shown to be crucial for a safe and successful takeover. The results will be useful as a reference for developers of automated driving systems to design human-machine interfaces, shorten the driver's reaction time, and improve takeover quality.

Determination of driver’s reaction time in expert studies of road traffic accidents using software and hardware complex

The article addresses the psychophysiological state of vehicle drivers, analyzed in expert studies of road traffic accidents (RTAs). The purpose of this article is to publish the results of research on reaction time and visual perception of drivers under the influence of alcohol. The authors experimentally obtained the values of simple reaction time of drivers able to work as usual and drivers in a state of alcoholic intoxication (0.3‰, 0.5‰), as well as the values of the volume of their visual perception. The influence of different degrees of alcohol intoxication on the driver reaction time, which affects the ability to timely prevent accidents, is derived and scientifically justified.

EEG-based assessment in novice and experienced drivers' braking behaviour during simulated driving

The driver is an essential factor in the traffic system, and inexperienced drivers are special high-risk groups. We used electroencephalography (EEG) and reaction time to quantify the differences between experienced and novice drivers' risk perception and braking behaviour in a driving simulator. Twenty-seven participants were asked to drive through a 12-km dynamic scenario with EEG signals recorded simultaneously. There are mainly four frequency bands for human EEG activity: alpha, beta, theta, and delta. The power spectral density (PSD) of beta activity was analysed because it dominated when drivers braked in an emergency. The results indicate that the indicators of β activity and reaction time discriminated between the novice and experienced drivers. The reaction time of drivers was related to the increment of the β activity, indicating that the driver's risk perception stage will affect their risk reaction. The study provides us with the operating performance and internal physiological activities of drivers in the braking process.

Empirical evaluation of drivers’ start-up behavior at signalized intersection using driving simulator

Abstract Start-up behavior at signalized intersection mainly depends on perception reaction time of drivers to the green phase. This study investigated the start-up behavior at signalized intersections by considering reaction time, acceleration and jerk (the rate of change of acceleration) of drivers in the state of Qatar. Distributions for reaction time, acceleration and jerk were plotted and the mean and 50th percentile values were presented. Three demographic factors (i.e., gender, ethnicity and age) were analyzed using two-tailed/unpaired t-tests. The relationships between acceleration and reaction time, and jerk and reaction time were investigated by linear regression analyses. Descriptive analysis showed that drivers had a mean reaction time of 2.91 s. Furthermore, Arab drivers had significantly lower reaction time than non-Arab drivers. Regarding the jerk maneuvers, young drivers (below 30 years) displayed significantly higher jerk than drivers of 30 years or above. Results from linear regressions showed significant negative correlations in both models (i.e., reaction time on acceleration, reaction time on jerk). As this study targeted multi-cultural drivers’ population, the results of reaction time and jerk distributions could be used as inputs in simulation models which are developed for evaluating driver behavior and safety at signalized intersections in regions with multi-cultural driving population.