Driver Reaction Time Research Articles

Speed and reaction behavior in different highway landscapes: A driving simulator study

Objective: Speed and reaction time have an important influence on traffic safety. The highway landscape can affect psychological and physiological characteristics, which are associated with the speed and reaction time of drivers. This study aimed to understand the association between the highway landscape and driving speed and reaction time.Methods: Two simulation experiments were conducted, referred to as experiment 1 and experiment 2. Forty-four drivers were recruited to participate in the experiments. Based on the road alignment and enclosure degree, in experiment 1 and experiment 2 the highway landscape was divided into 24 and 8 types, respectively. VS-Design was used to establish the virtual scenes. A KMRTDS driving simulator was used to perform the experiments.Results: Driver reaction time decreased with an increase in the enclosure degree of the road. Moreover, in straight sections, the speed decreased with an increase in the enclosure degree of the road, whereas in curved sections, the speed was mainly affected by the road geometric alignment.Conclusions: The driver’s perceived ability was significantly affected by the highway landscape, and optimization of the highway landscape environment is necessary to promote transportation efficiency and improve the traffic safety situation.

Night-time driving visibility associated with LED streetlight dimming

New LED streetlighting designs and dimming are being introduced worldwide, however, while their cost savings are well established, their impact on driving performance has received little attention. This study investigated the effect of streetlight dimming on night-time driving performance. Participants included 14 licensed drivers (mean age 34.2 ± 4.9 years, range 27–40 years) who drove an instrumented vehicle around a closed circuit at night. Six LED streetlights were positioned along a 250 m, straight section and their light output varied between laps (dimming levels of 25%, 50%, 75% and 100% of maximum output; L25, L50, L75 and L100 respectively; at 100% average road surface luminance of 1.14 cd/m2). Driving tasks involved recognition distances and reaction times to a low contrast, moving target and a pedestrian walking at the roadside. Participants drove at an average driving speed of 55 km/hr in the streetlight zone. Streetlight dimming significantly delayed driver reaction times to the moving target (F3,13.06 = 6.404; p = 0.007); with an average 0.4 s delay in reaction times under L25 compared to L100, (estimated reduction in recognition distances of 6 m). Pedestrian recognition distances were significantly shorter under dimmed streetlight levels (F3,12.75 = 8.27; p = 0.003); average pedestrian recognition distances were 15 m shorter under L25 compared to L100, and 11 m shorter under L50 compared to L100. These data suggest that streetlight dimming impacts on driver visibility but it is unclear how these differences impact on safety; future studies are required to inform decisions on safe dimming levels for road networks.

Research of Changing the Driver's Reaction Time in the Traffic Jam

In this research the main attention is paid to establishing dynamics of changes in the driver’s reaction time in a traffic jam that affects traffic safety.With the help of the regression model, graphs of driver’s reaction time are constructed taking into account different age groups and types of the nervous system depending on the initial level of fatigue at the entrance to traffic jam and duration of traffic jam.Analysis of these graphs allowed us to establish trends in the driver’s reaction time in traffic jams, which indicate an increase in the driver’s reaction time with an increase in the time spent in the traffic jam. However, at the beginning of the traffic jam, depending on the initial fatigue level, different combinations of the reaction time change occur at the entrance to the traffic jam: at low values, the reaction time increases, and at high values it decreases. It was also found that the traffic jam has a different effect on the reaction time of drivers depending on their temperament. For the reaction time of the driver-phlegmatic traffic jam does not have a significant impact.

Study of road tunnel threshold zone lighting reduction coefficient

The luminance in the road tunnel threshold zone attracts broad attention due to its enormous energy consumption and direct influence on tunnel transportation security. Current lighting design methods in threshold zones mostly adopt the reduction coefficient method. However, the determination of reduction coefficient k simply considers tunnel design speed and flow rate, while excluding outside tunnel luminance and threshold zone color temperature and luminance, which have a major impact on driver visual adaptation. Existing problems in the determination of k value are analyzed; a visual performance experiment is utilized; and the reaction time of drivers in changeable outside tunnel luminance and threshold zone color temperature and luminance conditions is obtained; thus, the equations concerning reduction coefficient variation law are derived. In the end, a comparative analysis is made of the k values of the reduction coefficient stipulated by various norms under different color temperature conditions.

The Concept of Stimuli-Induced Equilibrium Point and Its Application in Ramp-Merging Control

In this paper, we propose the novel concept of stimuli-induced equilibrium point to synthesize the speed and position references for automatic on-ramp merging systems. Based on the psychological field theory, the intensity of the stimuli that act upon a driver between two vehicles in a three-vehicle platooning configuration is mathematically modeled to calculate a point at which the stimuli resultant becomes zero. This approach intends to mimic drivers’ decision process when certain distance separation with respect to the leader and follower vehicles is attained for safety. The location of this point is continuously updated according to the speed of the middle vehicle and the current traffic scenario. Such stimuli-induced equilibrium point has shown to improve the performance of existing automatic merging control schemes while increasing safety conditions by providing enough reaction time for drivers to avoid an eventual collision.

Connected cruise control among human-driven vehicles: Experiment-based parameter estimation and optimal control design

In this paper, we consider connected cruise control design in mixed traffic flow where most vehicles are human-driven. We first propose a sweeping least square method to estimate in real time feedback gains and driver reaction time of human-driven vehicles around the connected automated vehicle. Then we propose an optimal connected cruise controller based on the mean dynamics of human driving behavior. We test the performance of both the estimation algorithm and the connected cruise control algorithm using experimental data. We demonstrate that by combining the proposed estimation algorithm and the optimal controller, the connected automated vehicle has significantly improved performance compared to a human-driven vehicle.

O 076 - Electromyography for determination of muscle response: Effects of Parkinson disease

Nowadays muscle response constitutes one of the important topic in the field of medicine and rehabilitation. For rehabilitation purposes muscle response time can be analyzed by using electromyography. With the development of ADAS system, muscle response time can be determined as a part of driver reaction time for purposes of traffic analyzes and assessments. The aim of this work is to analyze muscle response within two investigated groups of drivers, i.e drivers suffering by Parkinson disease (PD drivers) and drivers without Parkinson disease (NON-PD drivers). Muscle response was found out for both drivers’ groups and it was studied how it affects the overall reaction time of driver.

The analysis of drivers' reaction time using cell phone in the case of vehicle stabilization task.

The article analyzes the driver's psychophysiological qualities such as complex reaction and individual ability to control the vehicle that has suddenly lost its stability. The comparative analysis of the duration of reaction time was performed to assess the negative influence of speaking on a phone and driving with one hand. The experimental research was carried out on special training grounds with the road surface having low adhesion coefficient, where sudden lateral vehicle destabilization was caused by the moving plate mounted on the road surface. The vehicle onboard equipment was used for identifying the difference between the destabilization moment and the responsive driver's steering wheel movement which in this research was assumed as the reaction time. Statistical methods of research applied for the analysis of results showed high probability that the driver's actions would be significantly late in controlling a vehicle. When stabilizing a vehicle movement, the complex reaction time of a vehicle driver speaking on a mobile phone is increased by 18.1% as compared with the conventional driving by a driver not speaking on a phone. The risk of using the phone depends on the driver characteristics, traits and attitudes that affect the level of their experienced dangers, and the intensity of using mobile phones and driving. Speaking on a phone while driving increases the driver's reaction time and mental workload, and changes his or her visual overview ability as well as understanding of the situation. Int J Occup Med Environ Health 2018;31(5):633-648.

A Comparison of Reaction Time and Mental Imagery of Video Game Players and Two-Wheeler Drivers

The study aimed to identify whether significant difference exist between video game players and non-players, as well as two-wheeler drivers and non-drivers in reaction time and mental imagery. The samples being male video game players (N=30), and non-players (N=30), two-wheeler drivers (N=30) and non-drivers (N=30) were collected from one of colleges of Kerala. A random selection, of total 120 samples which consisted of four groups of 30 each aged between18 to 23, was done. Personal data schedule to obtained Reaction time apparatus; to determine their reaction time, mental imagery questionnaire; to assess the sensory experiences was administered. The data analyzed using T-test showed significant difference in the choice reaction time, between video game players and non-players. Except choice reaction time, mental imagery and simple reaction time showed no significance in any group. Thus hypothesis that there is no significant difference between video game players and non players in mental imagery and reaction time and there is no significant difference between two-wheeler drivers and non-two wheeler drivers in mental imagery and reaction time are accepted. However significant difference in choice reaction domain of the reaction time was observed.

Improvement of Evaluation Indices for Rear-End Collision Risk

There are various kinds of indices to evaluate collision risk against forward obstacles, which are used to determine the timing of collision warning provision in forward obstacle collision warning systems (FCWSs) and advanced emergency braking systems. A previous study proposed a deceleration for collision avoidance (DCA) method, which can evaluate a collision risk more precisely than other conventional indices. However, the calculation process of DCA assumed that a following vehicle (FV) performs a uniform motion within a driver's constant reaction time. The assumption causes underestimation of collision risk when the FV accelerates and overestimation when it decelerates. Consequently, this paper shows a detailed calculation process of an improved DCA based on an expanded assumption that the FV maintains a uniformly accelerated motion within the reaction time. Moreover, stimulus-response experiments were conducted to measure the driver's reaction time when he/she adjusts the brake pedal depression. Numerical simulations, where DCA is used for the FCWS, were performed to show that the improved DCA (with a new setting for the driver reaction time) describes the collision risk more properly compared to the conventional DCA.

A novel framework to evaluate pedestrian safety at non-signalized locations

This paper proposes a new framework to evaluate pedestrian safety at non-signalized crosswalk locations. In the proposed framework, the yielding maneuver of a driver in response to a pedestrian is split into the reaction and braking time. Hence, the relationship of the distance required for a yielding maneuver and the approaching vehicle speed depends on the reaction time of the driver and deceleration rate that the vehicle can achieve. The proposed framework is represented in the distance-velocity (DV) diagram and referred as the DV model. The interactions between approaching vehicles and pedestrians showing the intention to cross are divided in three categories: i) situations where the vehicle cannot make a complete stop, ii) situations where the vehicle’s ability to stop depends on the driver reaction time, and iii) situations where the vehicle can make a complete stop. Based on these classifications, non-yielding maneuvers are classified as “non-infraction non-yielding” maneuvers, “uncertain non-yielding” maneuvers and “non-yielding” violations, respectively. From the pedestrian perspective, crossing decisions are classified as dangerous crossings, risky crossings and safe crossings accordingly. The yielding compliance and yielding rate, as measures of the yielding behavior, are redefined based on these categories. Time to crossing and deceleration rate required for the vehicle to stop are used to measure the probability of collision. Finally, the framework is demonstrated through a case study in evaluating pedestrian safety at three different types of non-signalized crossings: a painted crosswalk, an unprotected crosswalk, and a crosswalk controlled by stop signs. Results from the case study suggest that the proposed framework works well in describing pedestrian-vehicle interactions which helps in evaluating pedestrian safety at non-signalized crosswalk locations.

Enhanced emotion enabled cognitive agent-based rear-end collision avoidance controller for autonomous vehicles

Amongst collisions, rear-end collisions are the deadliest. Several rear-end collision avoidance solutions have been proposed recently in the literature. A key problem with existing solutions is their dependence on precise mathematical models. However, real world driving is influenced by a number of nonlinear factors. These include road surface conditions, driver reaction time, pedestrian flow, and vehicle dynamics. These factors involve so many different variations that precise mathematical solutions are hard to obtain, if not impossible. This problem with precise control-based rear-end collision avoidance schemes has also previously been addressed using fuzzy logic, but the excessive number of fuzzy rules straightforwardly prejudices their efficiency. Furthermore, such fuzzy logic-based controllers have been proposed without the use of an appropriate modeling technique. One such modeling technique is agent-based modeling. This technique is suitable because it allows for mimicking the functions of an artificial human driver executing fuzzy rules. Keeping in view these limitations, we propose an enhanced emotion enabled cognitive agent (EEEC_Agent)-based controller. The proposed EEEC_Agent helps autonomous vehicles (AVs) avoid rear-end collisions with fewer rules. One key innovation in its design is to use the human emotion of fear. The resultant agent is very efficient and also uses the Ortony–Clore–Collins (OCC) model. The fear generation mechanism of EEEC_Agent is verified through NetLogo simulation. Furthermore, practical validation of EEEC_Agent functions is performed by using a specially built prototype AV platform. Finally, a qualitative comparison with existing state-of-the-art research works reflects that the proposed model outperforms recent research proposals.

Using naturalistic driving study data to investigate the impact of driver distraction on driver's brake reaction time in freeway rear-end events in car-following situation

IntroductionThe rear-end crash is one of the most common freeway crash types, and driver distraction is often cited as a leading cause of rear-end crashes. Previous research indicates that driver distraction could have negative effects on driving performance, but the specific association between driver distraction and crash risk is still not fully revealed. This study sought to understand the mechanism by which driver distraction, defined as secondary task distraction, could influence crash risk, as indicated by a driver's reaction time, in freeway car-following situations. MethodA statistical analysis, exploring the causal model structure regarding drivers’ distraction impacts on reaction times, was conducted. Distraction duration, distraction scenario, and secondary task type were chosen as distraction-related factors. Besides, exogenous factors including weather, visual obstruction, lighting condition, traffic density, and intersection presence and endogenous factors including driver age and gender were considered. ResultsThere was an association between driver distraction and reaction time in the sample freeway rear-end events from SHRP 2 NDS database. Distraction duration, the distracted status when a leader braked, and secondary task type were related to reaction time, while all other factors showed no significant effect on reaction time. ConclusionsThe analysis showed that driver distraction duration is the primary direct cause of the increase in reaction time, with other factors having indirect effects mediated by distraction duration. Longer distraction duration, the distracted status when a leader braked, and engaging in auditory-visual-manual secondary task tended to result in longer reaction times. Practical applicationsGiven drivers will be distracted occasionally, countermeasures which shorten distraction duration or avoid distraction presence while a leader vehicle brakes are worth considering. This study helps better understand the mechanism of freeway rear-end events in car-following situations, and provides a methodology that can be adopted to study the association between driver behavior and driving features.

How we can measure the non-driving-task engagement in automated driving: Comparing flow experience and workload

In automated driving, a driver can completely concentrate on non-driving-related tasks (NDRTs). This study investigated the flow experience of a driver who concentrated on NDRTs and tasks that induce mental workload under conditional automation. Participants performed NDRTs under different demand levels: a balanced demand–skill level (fit condition) to induce flow, low-demand level to induce boredom, and high-demand level to induce anxiety. In addition, they performed the additional N-Back task, which artificially induces mental workload. The results showed participants had the longest reaction time when they indicated the highest flow score, and had the longest gaze-on time, road-fixation time, hands-on time, and take-over time under the fit condition. Significant differences were not observed in the driver reaction times in the fit condition and the additional N-Back task, indicating that performing NDRTs that induce a high flow experience could influence driver reaction time similar to performing tasks with a high mental workload.

Looking forward to safer HGVs: The impact of mirrors on driver reaction times

Heavy Goods Vehicle (HGV) collisions are responsible for a disproportionate number of urban vulnerable road user casualties (VRU – cyclists and pedestrians). Blind-spots to the front and side of HGVs can make it difficult (sometimes impossible) to detect close proximity VRUs and may be the cause of some collisions. The current solution to this problem is to provide additional mirrors that can allow the driver to see into the blind-spots. However, keeping track of many mirrors requires frequent off-road glances which can be difficult to execute during demanding driving situations. One suggestion is that driving safety could be improved by redesigning cabs in order to reduce/remove blind-spot regions, with the aim of reducing the need for mirrors, and increasing detection rates (and thereby reducing collisions). To examine whether mirrors delay driver responses we created a series of simulated driving tasks and tested regular car drivers and expert HGV drivers. First we measured baseline reaction times to objects appearing when not driving (‘Parked’). Participants then repeated the task whilst driving through a simulated town (primary driving tasks were steering, braking, and following directional signs): driving slowed reaction times to objects visible in mirrors but not to objects visible through the front windscreen. In a second experiment cognitive load was increased, this slowed RTs overall but did not alter the pattern of responses across windows and mirrors. Crucially, we demonstrate that the distribution of mirror RTs can be captured simply by the mirror’s spatial position (eccentricity). These findings provide robust evidence that drivers are slower reacting to objects only visible in eccentric mirrors compared to direct viewing through the front windscreen.

Optimal Control of Connected Vehicle Systems With Communication Delay and Driver Reaction Time

In this paper, linear quadratic regulation is used to obtain an optimal design of connected cruise control (CCC). We consider vehicle strings where a CCC vehicle receives position and velocity signals through wireless vehicle-to-vehicle communication from multiple vehicles ahead. Communication delay, driver reaction time, and heterogeneity of vehicles are considered. The optimal feedback law is obtained by minimizing a cost function defined by headway and velocity errors and the acceleration of the CCC vehicle on an infinite horizon. We show that, by decomposing the optimization problem, the feedback gains can be obtained recursively as signals from vehicles farther ahead become available, and that the gains decay exponentially with the number of cars between the source of the signal and the CCC vehicle. Such properties allow graceful degradation of CCC performance under imperfect communication. The effects of the cost function on the head-to-tail string stability are also investigated and the robustness against variations in human parameters is tested. The analytical results are verified by numerical simulations at the nonlinear level. The results allow us to significantly reduce the complexity of CCC design.

Research on drivers’ reaction time in different conditions

The study has determined the peculiarities of forming the reaction time of drivers in laboratory and real conditions. The fastest response time in the real conditions was found to be 1.37 seconds in the second age group of the tested drivers. The drivers’ reaction time was by 25 % longer in the first group and by 60 % longer in the third group. The smallest impact of the functional state on the drivers’ reaction time in the laboratory conditions was produced on the drivers of the second age group; the biggest impact was recorded for the drivers of the third group. The duration of the latent period relative to the total duration of the drivers’ reaction time of the drivers varied on average from 30 % to 45 %. It was found that in all age groups the reaction time of male drivers on average was 15 % shorter than of female drivers. The functional state of the drivers was evaluated by the following factors: the stress index, the activity rate of the regulatory systems, as well as the frequency and the average amplitude rhythms on the electroencephalogram. These indices were obtained using the experimental software packages NeuroCom and Cardio Sens. Testing in the real conditions revealed that the drivers’ reaction time was on average twice the value obtained in the laboratory conditions. The reaction time was proven to depend on the drivers’ psychophysiological characteristics, which should be taken into account while determining the safe vehicle speed in projects of automated systems of traffic management. The safe speed modes and speed limits were determined with regard to the patterns of the drivers’ reaction time formation.

Investigating driver reaction time and speed during mobile phone conversations with a lead vehicle in front: A driving simulator comprehensive study

ABSTRACTThis study analyzed driving performance while using different mobile devices in different road configurations and geometries during a critical driving situation. Three different road environments were implemented in a driving simulator: an urban road, a two-lane rural road, and a highway. Thirty drivers with an average age of 26.8 years were asked to answer a phone call while driving, using different mobile devices: hand-held, hands-free, and hands-free voice-activated cellular phone. The effects of using the mobile phones were also compared to the BC (no phone conversation). Driving performance, under car-following conditions, were collected and statistically analyzed when a sudden braking of the leading vehicle occurred. The main results demonstrated that the driver's speed generally reduced during the phone call whereas the reaction time generally increased, especially under certain driving conditions (urban road, along tangent, using hand-held mobile device). This study analyzed the effects of using a mobile phone while driving, highlighted the worst combinations of the variables investigated, and demonstrated that some reductions in driving performance were revealed, especially in the urban environment, even when using mobile equipment permitted by the regulations of several countries.

Feedback control for the lattice hydrodynamics model with drivers’ reaction time

In this paper, a new lattice hydrodynamic model (LH model) of traffic flow under consideration of reaction time of drivers and a corresponding feedback control scheme are proposed. Based on the model, stability analysis is conducted through linear stability analysis of transfer function. The obtained phase diagram indicates that the reaction time of driver can affect the instability region of traffic flow. Under the action of a feedback control, the unstable region is shrunken to reach suppressing jams. The numerical simulations are performed to validate the effect of reaction time of driver in the new LH model. The study results confirm that the reaction time of driver significantly affects the unstability of traffic system, and the feedback control can suppress traffic jams. Furthermore, it is found that the traffic system from the chaotic traffic state to periodic steady one is successfully realizing the control of traffic system.

To Analyze Reaction Time of Drivers Based on Drivers Characteristics- A Review

To Analyze Reaction Time of Drivers Based on Drivers Characteristics- A Review