Driver Workload Research Articles

Driving simulation platform applied to develop driving assistance systems

This study presents a driving simulation platform with low cost for the development of driving assistance systems (DAS). The platform uses a combination of two simulation loops: hardware-in-the-loop (HIL) and driver-in-the-loop (DIL). Its hardware consists of a simulation computer, a monitor computer, a vision computer, DAS actuators and a car mock-up. Its main software includes a monitor software running in the monitor computer, a vision rendering software running in the vision computer and Matlab/Simulink-based simulation model running in simulation computer. When designing its monitor software, a graphical user interface driven-by S-function method is adopted to eliminate the delay in the displaying of the simulation data. The vision rendering software uses a parametric adjustment method based on the principle of optical projection, improving the driver's perception of being immersed in the virtual traffic scene. The application of the developed platform is demonstrated by HIL experiments of vehicle actuators and DIL experiments of adaptive cruise control (ACC) algorithm. These experiments not only demonstrate the potential merit of the platform of speeding up DAS development, but also illustrate that the proposed control algorithms for actuators possess good tracking capability, as well as that the developed ACC algorithm is capable of improving driver comfort and reducing driver workload.

실시간 운전 특성 모니터링 시스템을 위한 차량 환경 개발

There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the Road Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

Route Ahead Visibility Mapping: A method to model how far ahead a motorist may view a designated route

Please click here to download the map associated with this article. We examine how visibility analysis may be used to calculate the extent of the route ahead visible to a motorist. To do this a Digital Surface Model sourced from a LiDAR dataset is used, which includes building and vegetation profiles as well as topography. Once the route has been designated the visibility along the path is modelled, in the direction of travel, from the driver's viewpoint. The visibility analysis considers all surrounding objects during the calculation, but reports only how far ahead the route may be viewed, and not the total landscape area visible. The map accompanying the article shows the results from using this method for a route in Christchurch, New Zealand, from which we identify a number of interesting results along the route. This method may be used such that navigational devices customise announcements to the most opportune times when the driver's workload is minimal and decision points are in view, rather than at predefined distances. It could also be used to notify the driver of the safest overtaking locations or those areas of limited visibility.

Psychological elements in car-following models: Mental workload in case of incidents in the other driving lane

Estimations of parameter values of car-following models show considerable differences between individuals and experiments. These differences may be caused by a different effect of external circumstances on mental workload of drivers. This effect may especially play a considerable role in case of driving under adverse conditions (e.g. evacuations, adverse weather conditions, road works and incidents on the freeway). These adverse conditions have shown to have a substantial impact on traffic flow operations. In this regard a driving simulator experiment was performed as to what extent an incident in the other driving lane influences physiological indicators as well as subjective estimates of mental workload as well as longitudinal driving behavior. Also was investigated whether current car-following models, represented by the Intelligent Driver Model and the Helly model, adequately incorporate longitudinal driving behavior under these circumstances using a calibration approach for joint estimation. From the results followed that perception of incidents in the other driving lane lead to significant changes in physiological indicators of mental workload as well as in longitudinal driving behavior. Through the estimation approach was indicated that the Intelligent Driver Model as well as the Helly model how show substantial changes in parameter values as well as that these models less adequately incorporate longitudinal driving behavior in case of incidents in the other driving lane.

Development of the Conceptual Prototype for Haptic Interface on the Telematics System

Driver safety and workload have become a crucial issue as the telematics system has evolved in a complex manner. To solve this problem, the aim of this study is to develop a conceptual prototype that supports haptic interface, an eye-free technology, with free navigation based on the user's mental model. The conceptual prototype for haptic interface is established through identifying the problems with previous haptic interface devices and defining functional requirements for the next generation telematics system. In addition, 25 criteria for a haptic device design are identified and applied to evaluate the conceptual prototype. These criteria are classified in a hierarchical order, and an Analytic Hierarchy Process (AHP) evaluation model is constructed accordingly. The AHP evaluation framework reveals critical factors as well as the degree of importance in designing the haptic device. As a result, an evaluation method has been developed for the prototype of the early phase of the haptic device design.

연령 증가에 따른 주행 중 인지 부하의 특성 변화

Driving is a complex psychomotor task often interrupted by secondary activities that increase cognitive workload and divert attention away from the roadway. The risk of inattentive driving is known to vary with age. To assess the characteristics of advancing age on driver's cognitive workload under dual task condition, we evaluate the performance of 96 drivers divided into three age groups: 20's, 40's, and 60's. This study considers driver's cognitive workload in the context of urban and highway driving. Error rate & Dual task cost are used to measure driver's cognitive workload. Results indicate that age impacts cognitive workload during dual task driving conditions.

An analysis of the effect of roadway design on driver's workload

Driving behavior is a direct consequence of the stimuli received from the road infrastructure, from the surrounding environment, and from the atmosphere inside the vehicle. Almost all of these perceptions, which affect steering, are received through the drivers' eyes. For this reason, in this paper visual behavior was examined in order to deduce new indexes connected to mental workload. To this aim, a consistent sample of drivers covered a rural road inside a vehicle, while their eye movements and driving activities were being recorded with suitable instruments. The quantification of some variables involved in the trials permitted the evaluation of visual behavior and determination of a measure of mental workload, identifying also any situations where performance was compromised. Some reports between mental workload and road geometry, summarized in a few tables, could represent a further aid for road designers and managers.

Investigations on control algorithm of steady-state cornering and control strategy for dynamical correction in a steer-by-wire system

To improve the handling performance of a steer-by-wire (SBW) vehicle, a series of control logics are proposed. Firstly, an algorithm for enhancing the maneuvering in steady-state cornering is presented. On this basis, two categories of control strategies are used to dynamically correct and compensate the transient state steering responses and vehicle behaviors. Simulator tests including subjective evaluations and virtual field tests are both conducted to make comprehensive investigations on the series of control logics. The subjective evaluations demonstrate that the SBW vehicle with a specifically selected value of steering sensitivity tends to be more desirable for driving than a conventional one in which a fixed steering ratio exists. The virtual field tests indicate that the control strategies for dynamical correction and compensation could effectively improve the handling performances of an SBW vehicle by reducing the work load of drivers, enhancing the track-holding performance, and improving steering response properties.

Mental workload when driving in a simulator: Effects of age and driving complexity

Driving errors for older drivers may result from a higher momentary mental workload resulting from complex driving situations, such as intersections. The present study examined if the mental workload of young and older active drivers vary with the difficulty of the driving context. We adopted the probe reaction time (RT) technique to measure the workload while driving in a simulator. The technique provided clear instructions about the primary (driving) and secondary (RT) tasks. To avoid structural interference, the secondary task consisted of responding as rapidly as possible with a vocal response (“top”) to an auditory stimulus. Participants drove through a continuous 26.4-km scenario including rural and urban sections and probes (stimuli) were given in a baseline static condition and in three different driving contexts embedded into the overall driving scenario. Specifically, stimuli were given randomly when (a) driving on straight roads at a constant speed, (b) approaching intersections for which the driver had to stop the car, and (c) when overtaking a slower vehicle. Unless a driving error was made, drivers did not need any emergency responses. Reaction time was defined as the temporal interval between the auditory stimulus and the onset of the corresponding verbal response detected from the analog signal of a piezo-electric microphone fixed on a headset (ms accuracy). Baseline RTs were similar for both groups. Both groups showed longer RTs when driving and RTs increased as the complexity of the driving contexts increased (driving straights, intersections, overtaking maneuvers). Compared to younger drivers, however, older drivers showed longer RTs for all driving contexts and the most complex driving context (overtaking maneuvers) yielded a disproportionate increase. In conclusion, driving leads to a greater mental workload for the older drivers than for the younger drivers and this effect was exacerbated by the more complex driving context (overtaking maneuvers).

Time perception as a workload measure in simulated car driving

In experimental studies using flight simulations subjects’ duration estimates have shown to be an effective indicator of cognitive task demands. In this study we wanted to find out whether subjective time perception could serve as a measure of cognitive workload during simulated car driving. Participants drove on a round course of a driving simulator consisting of three different environments with different levels of task demands. Drivers were required to perform a time-production task while driving the vehicle. Electrodermal activity and subjective ratings of mental workload (SWAT) were recorded simultaneously. The length of produced intervals increased significantly in more complex driving situations, as did electrodermal activity and subjective ratings of mental workload. Thus, time production is a valid indicator of cognitive involvement in simulated driving and could become a valid method to measure the current mental workload of car drivers in various traffic situations.

2205 ドライバ特性を考慮した緊急時の操舵支援制御の効果に関する研究(OS6-2:操舵・操縦特性,OS6:ヒューマンファクタ,オーガナイズド・セッション(OS),第18回交通・物流部門大会(TRANSLOG2009))

ABSTRACT: In recent years, a lot of research regarding steering assist controls has been studied with aims of reducing driver's steering workload and improving vehicle performance. Meanwhile, the performance as man-machine system may not always improve by intervention of the steering assist control because driver’s steering is essential. Therefore, the design of the system considering driver's characteristics is necessary. In this research, we designed the steering assist control by applying the optimal regulator for the closed-loop system including the driver, and control inputs of this system are both the steering angle and the steering torque in order to take driver's characteristics into account. In addition, we verified the control effects by using the driving simulator.

定常円旋回時の車両運動のドライバーに与える精神的負荷 : 心拍のウェーブレット解析(機械力学,計測,自動制御)

定常円旋回時の車両運動のドライバーに与える精神的負荷 : 心拍のウェーブレット解析(機械力学,計測,自動制御)

Impact of Incremental Increases in Cognitive Workload on Physiological Arousal and Performance in Young Adult Drivers

This study examined the sensitivity of heart rate, skin conductance, and respiration rate as measures of mental workload in a simulated driving environment. Workload was systematically manipulated by using increasingly difficult levels of a secondary cognitive task. In a sample of 121 young adults, heart rate increased incrementally with increasing task demand. Significant elevations in skin conductance and respiration rate were also observed. At the lower levels of added workload, secondary task performance was nearly perfect and changes in indices of driving performance were negligible. At the highest level of workload, all three physiological measures appeared to plateau, and a subtle drop in simulated driving performance became detectable. Taken together, the pattern of results indicates that physiological measures can be sensitive to changes in workload before the appearance of clear decrements in driving performance. These findings further highlight a role for physiological monitoring as a means to measure mental workload in product design and functionality research. They also support work exploring the potential for incorporating physiological measures of driver workload and attentional state in future safety systems.

Conventional versus Moving-Map Navigation Methods

Thirty-eight male and female participants, aged 21 to 50 years, drove to three unfamiliar destinations using three different methods of navigation: Nav, an in-vehicle moving-map and route guidance navigation system; Free, the free use of paper maps or computer printouts, but without access to the navigation system; and Way, which was the same as Free, but with waypoints also provided. Each participant had a minimum of 6 weeks of prior experience using in-vehicle navigation technology. The routes were each designed to sample urban, rural, and highway road categories. Methods were counterbalanced across route and presentation order. An onboard experimenter administered the study. Data were gathered to assess navigational efficiency, workload, and safety-related driving errors. A peripheral detection task was included as a loading task to measure workload and spare attentional capacity objectively; the rating scale of mental effort was included as a subjective measure of mental effort. Use of the navigation system produced better results than either of the two conventional methods in terms of several key metrics related to driver workload, driving errors, and navigational efficiency. These results support the notion that an onboard, moving-map navigation system incorporating route guidance can play a meaningful role in enhancing navigational efficiency and safety for experienced navigation system users. Future research is recommended to examine eye glance and other driver behaviors further, such as lane excursions and headway maintenance, to gain additional insight into the effect of method of navigation on the primary driving task.

Determinants of following headway in congested traffic

This paper reports on results of a study undertaken in the UK aimed at investigating factors affecting the car following process. An understanding of the factors affecting this complex decision making process is essential to a wide range of theoretical issues including driver workload, capacity and the modeling of freeway flow, as well as practical applications such as the design of in-vehicle driver aids and assistance systems, many of which have direct relevance to increasing driver safety. The study used an instrumented vehicle to collect time dependent following data for a group of test drivers. Data was collected on two differing types of high speed road, using six primary subjects who drove a test vehicle, supplemented by data on 123 drivers that were observed following the test vehicle. Examination was made of how the time headway chosen by a driver is influenced by a range of situational variables commonly believed to effect behavior, with four main findings. Firstly, headway was found to change according to the type of vehicle being followed (i.e. subjects followed closer to trucks than to cars), secondly, little variation was found with changes in overall traffic flow, thirdly, little correlation was found with road type, and lastly a distinct day-to-day variation in individual behavior was observed.

Driving with a congestion assistant; mental workload and acceptance

New driver support systems are developed and introduced to the market at increasing speed. In conditions of traffic congestion drivers may be supported by a “Congestion Assistant”, a system that combines the features of a Congestion Warning System (acoustic warning and gas pedal counterforce) and a Stop & Go system (automatic gas and brake pedal during congestion). To gain understanding of the effects of driving with a Congestion Assistant on drivers, mental workload of drivers was registered under different conditions as well as acceptance of the system. Mental workload was measured by means of physiological registrations, i.e. heart rate, a secondary task and with the aid of subjective scaling techniques. Acceptance was measured with an acceptance scale. The study was carried out in an advanced driving simulator. Driving with the Congestion Assistant while in congestion potentially leads to decreased driver mental workload, whereas just before congestion starts, i.e. developing just noticeable, the system may add to the workload of the driver. Acceptance is generally high after experiencing the system, though not in all respects.

Development of an Adaptive Workload Management System Using the Queueing Network-Model Human Processor (QN-MHP)

The risk of vehicle collisions significantly increases when drivers are overloaded with information from in-vehicle systems. One of the solutions to this problem is developing adaptive workload management systems (AWMSs) to dynamically control the rate of messages from these in-vehicle systems. However, existing AWMSs do not use a model of the driver cognitive system to estimate workload and only suppress or redirect in-vehicle system messages, without changing their rate based on driver workload. In this paper, we propose a prototype of a new queueing network-model human processor AWMS (QN-MHP AWMS), which includes a queueing network model of driver workload that estimates the driver workload in several driving situations and a message controller that determines the optimal delay times between messages and dynamically controls the rate of messages presented to drivers. Given the task information of a secondary task, the QN-MHP AWMS adapted the rate of messages to the driving conditions (i.e., speeds and curvatures) and driver characteristics (i.e., age). A corresponding experimental study was conducted to validate the potential effectiveness of this system in reducing driver workload and improving driver performance. Further development of the QN-MHP AWMS, including its use in in-vehicle system design and possible implementation in vehicles, is discussed.

Workload Transitions in Driving

Driver mental workload is an often studied concept, however less attention is given to the question of transitions in driver workload. Fourteen adult drivers completed a simulated driving task following a navigation system which would fail at certain intervals. Subjective measures of driver workload were taken and demonstrate that the recovery from a driving stressor is asymmetrical and time-delayed. Drivers' subjective ratings of workload remained high after the stressors were removed. Findings and implications are discussed.

New Insights into Driving Using Recurrence Quantification Analysis

Traditional measures of central tendency and dispersion, such as the mean and standard deviation, ignore ordering effects in time-series data. Hidden within the ordered regularity of time series' may lie unique human performance characteristics. Recurrence quantification analysis (RQA), a contemporary tool designed for the investigation of nonlinear-time-series data, is used to explore lateral driving movement in a simulated car-following task. This investigation assesses a previously published data set that contrasts baseline driving performance, with performance while legally intoxicated, and hands-free/hand-held cell phone conversation. A number of distinguishing lateral movement characteristics were found using RQA. Free from the constraints imposed by discrete driving measures, RQA has the potential to provide real-time measures of driver workload under a variety of conditions.

Tactile and Multisensory Spatial Warning Signals for Drivers.

The last few years have seen many exciting developments in the area of tactile and multisensory interface design. One of the most rapidly-moving practical application areas for these findings is in the development of warning signals and information displays for drivers. For instance, tactile displays can be used to awaken sleepy drivers, to capture the attention of distracted drivers, and even to present more complex information to drivers who may be visually-overloaded. This review highlights the most important potential costs and benefits associated with the use of tactile and multisensory information displays in a vehicular setting. Multisensory displays that are based on the latest cognitive neuroscience research findings can capture driver attention significantly more effective than their unimodal (i.e., tactile) counterparts. Multisensory displays can also be used to transmit information more efficiently, as well as to reduce driver workload. Finally, we highlight the key research questions currently awaiting further research, including questions such as: Are tactile warning signals really intuitive? Are there certain regions of the body (or in the space surrounding the body) where tactile/multisensory warning signals are particularly effective? To what extent is the spatial coincidence and temporal synchrony of the individual sensory signals critical to determining the effectiveness of multisensory displays? And, finally, how does the issue of compliance vs. reliance (or the 'cry wolf' phenomenon associated with the presentation of signals that are perceived as false alarms) influence the effectiveness of tactile and/or multisensory warning signals?