These models are also part of the Jack Occupant Packaging Toolkit and are used by a number of companies to develop and assess vehicle interiors. I've used the heavy truck driver posture prediction as part of other research and model development on driver reach and cab layout optimization.
Reach assessment is one of the most common analyses performed on vehicle operator stations, whether in planes, trains, or automobiles. The Society of Automotive Engineers Recommended Practice J presents a statistical model of driver reach capability that has been widely used for both passenger cars and heavy vehicles. However, the conditions under which the underlying data were collected, particularly the occupant restraint conditions, are quite unlike those encountered by drivers today.
Along with colleagues from the Human Motion Simulation Lab, I conducted a laboratory study of reach difficulty and capability with truck, bus, and other drivers.
I developed a statistical model that predicts the subjective difficulty of reaches to push-button targets up to maximum reach capability. The model has been applied to a variety of reach assessments in commercial and military vehicles.
We have also conducted studies of reach kinematics. Among the important conclusions is that maximum seated reach capability is not primarily limited by joint range-of-motion limitations.
Rather, balance and tolerance of risk seem to be more important factors. One conclusion of this work is that kinematically generated reach envelopes, which are very common in ergonomic assessments using human models, are unlikely to be accurate. The primary objective of the work was to develop a new H-point manikin to replace the original SAE H-point machine that was developed in the late s. The ASPECT scope included several laboratory studies of driver and passenger posture, including studies of the effects on posture of vehicle package factors e.
My colleagues and I at UMTRI have conducted a series of studies since the late s to replace the previous practices. The next section describes a process that starts in a relatively coarse, broad-brush manner, and then is refined and polished as the design matures.
The process reflects this, starting with 2D geometry and basic dimensions SAE J and internal company guidelines , laying out the basic architecture of the vehicle see Figure 3. Each of these stages is described in detail in the following sections.
In doing so, various SAE standards are referred to. The Society of Automotive Engineers International SAE is a standards development organisation for engineering professionals in the aerospace, automotive, and commercial vehicle industries. It publishes over 1, technical standards relating to the design of passenger cars; included in these are a number of ergonomics standards that are critical to vehicle occupant packaging. They provide recommended practice for laying out the initial package, however care must be taken in their use, and any occupant package must be verified and refined through human evaluations with physical architecture.
It is also important to note that SAE standards may be more applicable to a US population, whereas vehicles developed for worldwide markets will require detailed data relating to those markets to refine the occupant package appropriately. This can then be used to position the H-point of a virtual 2D H-point template see Figure 3. Thus, the H-point can be used to relate a physical seat to virtual geometry. Whereas on a fixed non-adjustable seat there is only one H-point position, on an adjustable seat e.
The extremes of these can be mapped and described as the seat movement envelope. In order to have one point of reference for occupant packaging, the manufacturer will create a unique design H-point known as the seating reference point SgRP. This is the reference point used to position the SAE 2D template.
The SgRP is a fundamental reference point for defining and describing both the occupant package and vehicle dimensions see Figure 3. Many of the occupantrelated factors and legal requirements are quoted in relation to the SgRP: the occupant packaging engineer and automotive designer will therefore need to have a good understanding of this. In addition, the SgRP enables correlation between the virtual and physical environments, providing a consistent method for the comparison of vehicles internal and competitors.
Examples of the recommendations used to establish the occupant package include the following: Head contours as defined in SAE J are used to help establish the upper cabin architecture of the vehicle, so ensuring the driver has enough space around the head. This enables their posture, location in relation to the driver and the space around them to be defined. Internal company guidelines are used in conjunction with SAE direction. Such company guidelines are based on experience of developing vehicles in the segment, of acceptable and preferable dimensions, and may also refer to the benchmarking of competitor vehicles, that is, to be competitive with the existing set of competitor vehicles, adopt the mean dimensions relating to occupant space.
At the end of this first step in the occupant package development process, we would expect to have an initial occupant package that acts as a good starting point. By that, we mean that the package has no major flaws.
However, it is very far from being a completed occupant package and requires significant further development and refinement to successfully meet the needs of the user population. These human models can be configured to represent people of various shapes and sizes in many populations, and so represent the intended user group for any vehicle. Such specialist software packages include. The purpose of these CAD tools is to predict the interaction of people with a physical environment.
As such, any software chosen should first have been validated to ascertain if for example, the predicted postures, reach and vision do indeed match those experienced by human occupants in a physical environment.
Clearly, human behaviour is complex and so it is difficult to model. Many engineers assume that these digital human models represent the answer to all their ergonomics queries, and that they can successfully package a vehicle using CAD tools with great confidence in the output. Digital human modelling does bring many benefits to the design process, but should be used as a crude filter to remove the more obvious occupant packaging issues. User trials with representatives from the user population with a representative buck will highlight issues that are not evident using digital human modelling, including long-term comfort issues, effects of fatigue, and a range of subtle issues such as product acceptance based on past experience.
The main advantages of digital human modelling are that the occupant package can be developed and assessed early in the vehicle programme without the high costs associated with designing, building and assessing a physical buck. In addition, by using a digital human modelling tool to develop the initial occupant package, when a physical buck is subsequently built, it represents a design that is already refined to a certain extent; most of the major issues should have been ironed out using virtual assessments and so the basics of the occupant package should be in place.
Comparisons between the available CAD tools are made in the literature and it is beyond the scope of this chapter to provide a detailed description of each software package or an overview of their relative merits.
These are produced by a packaging engineer to show the basic geometric layout of the vehicle and so to convey the logic behind the vehicle architecture. The package drawings are shown in three views: from the side, in plan view and from the front of the vehicle. An example package drawing is shown in Figure 3. As may be evident, the packaging engineer has included 2D representations of the occupants within the vehicle, as well as the key vehicle components.
The drawings also show the three-dimensional grid reference system X, Y and Z coordinates that is used to relate the vehicle dimensionally. A variety of ground lines are also shown to represent the vehicle attitude when loaded to different conditions i. Critical vehicle dimensions are included; all dimensions are measured in millimetres using a system described in SAE J with the prefixes L, W, H, A, D and V denoting dimensions of length, width, height, angle, diameter and volume.
However, it must be remembered that the 2D H-point template represented in the drawing is an SAE derived manikin, with little representation of the true range of occupant sizes and postures. These models display varied body dimensions which can be set by the RAMSIS user, so enabling, for example, a short stature,.
In addition, data can be selected from populations around the world, to reflect the intended markets for the vehicle. As populations are not static but change with time, RAMSIS software can also predict the sizes of people in the future, so that human models can be built of a driver, say, 10 years into the future.
This, of course, is important when a vehicle model may be on the market for a sustained period of time. Having modelled human occupants, what does the user do with these manikins? The ability to get comfortable, to reach the primary and secondary controls and to see these controls and the in-car displays, as well as vision out of the vehicle can be assessed.
The positioning of these RAMSIS digital human manikins is based on knowledge acquired of where humans sit in vehicles, and so the RAMSIS digital human postures that result are a good indication of where people will really sit in the vehicle that is built to the geometry being assessed. Using a specific process with specified tasks and manikin sizes, the user can undertake repeated assessments of the initial occupant package and develop it to ensure that the basic aims of occupant packaging are met, that is, that the intended range of drivers and passengers are accommodated within the vehicle package.
At the end of this stage of the occupant package development process, we would expect to have an occupant package that theoretically begins to meet the needs of its intended user population, but still requires further development.
However, one further step may be added and is described in the next section. This immersive environment is simply a space with three walls and the ceiling acting as screens onto which high-resolution images are projected. This is a very powerful development tool as the visual experience from a virtual driving position in the cave correlates well with that experienced in a real vehicle. This gives the vehicle engineer the ability to assess vehicle geometry before a physical model has been built.
Moreover, it is possible to rapidly and easily assess alternative designs or competitor vehicles for comparison purposes. However, it should be noted that this is merely a further step in the development process albeit an important one; at the time of writing, the cave is no substitute for assessing a physical vehicle. For example, ease of entry and exit still require physical assessment.
In doing so, it brings to life a vehicle that exists only as 3D geometry in a virtual world and so helps the packaging engineer in getting support and buy-in of his proposals. At this stage of the process, the vehicle package is becoming increasingly refined and aspects of the vehicle related to interior and exterior vision are now optimised. This would, for example, include the profile of the bonnet. The next stage describes the modelling process. Let us look at each in turn. How is the vehicle modelled?
Aspects of the design that are critical to occupant packaging are included in as accurate a manner as possible, while aspects that are noncritical to occupant packaging are expressed only in a crude form materials are often not representative of those in a car, but the buck is nevertheless good enough to give a feeling of what the final vehicle would be like.
This is an expensive tool that takes significant resources to produce. Before a buck is evaluated, the SAE H-point machine must be used to ensure the seat envelope is representative of the intended geometry. Bucks can be static or dynamic. Static bucks are assessed in a fixed position within a laboratory, and are initially used to gain data of customer satisfaction of such attributes as ease of entry and exit, comfort of the driving position, and so forth see Figures 3.
They tend to have a greater degree of representation and so they are extremely expensive and time consuming to produce. However, they are vital in the development and assessment of. Section 3. But later in the process, when we have physical models of vehicles to.
The human assessors must be carefully chosen and an appropriate number must be used in assessments. At JLR, we have a number of internal panels of employees who act as customer representatives, as well as carrying out external customer clinics with potential customers. Members of these internal panels participate in buck and vehicle evaluations see Figure 3. They are measured and their anthropometry recorded; when members of these panels are selected to take part in buck assessments, they are chosen based on their anthropometry to ensure that the extremes of the intended user population are covered.
It is beyond the scope of this chapter to discuss population sampling in detail, and the reader is referred to the further reading section. But there is a bigger picture to consider when asking why occupant packaging is so difficult, and that considers human diversity and the vast range of people that could be catered for.
Human diversity is considerable, and this is particularly evident when we are faced with the task of designing a single product for a global population. JLR vehicles are sold in over countries around the world. Within each of the countries, the vehicles must be suitable for a wide range of people and one vehicle model must be suitable for all countries, that is, one size fits all.
Thus, all these populations must be considered when vehicles are designed and developed. In recent years, JLR and the vehicle industry in general has faced the challenge of designing for emerging markets. The countries of Brazil, Russia, India and China are known by the acronym, BRIC, and are grouped together as they are considered to be at a similar stage of recently advanced economic development. For a world vehicle design to be successful, it must be designed to meet the needs of these BRIC populations; knowledge of these populations is therefore vital.
Clearly the challenge of being user centred and designing to accommodate a large population is difficult; we must consider the physical human differences that result from age, gender, nationality, ethnicity, changes over time, lifestyle, and so forth, when designing our vehicles. How do we measure these differences? We focus on anthropometric data. It is time for another definition: simply put, anthropometry is the measurement of body dimensions. Anthropometry has been established for many years and has been critical in the understanding of human variation and has.
How is such human variability expressed? Anthropometric data is used to describe the central tendency or mean of a population as well as the distribution of the data in the population, with 5th and 95th percentile figures generally quoted. There are over standardised dimensions that have been taken from various populations around the world see an example in Figure 3.
The ergonomist must ensure that any anthropometric data used to guide a design is as recent as possible. Within a population any changes in diet, healthcare, lifestyle, age profile, and so forth, may lead to rapid change in the anthropometric data of a population. Static anthropometry refers to the measurement of body dimensions taken with the body held in a number of standardised, defined static postures.
Stature or sitting height would be such a dimension. So, by their very nature, anthropometric data are gathered from people in defined postures. However, these defined postures bear little relation to the various postures adopted by drivers, for example, in the complex dynamic tasks of getting in and out of a vehicle or of driving.
The purpose of such a user trial is to elicit information from a group of participants relating to user satisfaction, perception and expectations of a prototype design. The automotive ergonomist has many tools at his disposal: interviews, questionnaires and observation methods are used in this stage. Interviews are flexible and a useful, good tool for collecting user perception data.
Participants are interviewed in a semi-structured manner on a one-to-one basis. Similarly, questionnaires offer a good means of rapidly collecting data from participants, with a focus in this process on user satisfaction. In our process, these are administered by the experimenter on a one-to-one basis. They are a good tool to evaluate design concepts and to probe user satisfaction, being flexible, allowing easy data analysis, and being easy to administer, and so forth.
Finally, observation is undertaken of participants undergoing a complex activity such as entry or exit. Detailed task performance can be recorded and analysed, but the very act of recording may change participant behaviour and is time consuming to analyse.
It is important to undertake these assessments with participants put at ease; a permissive environment must be provided where participants feel free to criticise a design and to make negative as well as positive statements without being judged or receiving adverse comments from the experimenter.
As such, the trials are conducted on a one-to-one basis, in a relaxed informal manner. Feedback from the trials is then interpreted into design recommendations by the ergonomist. For example, questionnaire feedback from participants relating to difficulty in entering a vehicle would trigger an observational study where it might be evident that the sill profile on the buck was causing a contact point with the leg. A local change in sill profile would address the difficulty being experienced.
The ergonomist would therefore recommend a new sill profile be adopted, and would specify its geometry to the relevant engineer. If these recommendations are adopted or more typically partly adopted, the buck is updated to reflect this revised geometry.
The buck is then retested with the aim of confirming if the changes have been effective in improving the occupant package. This is an iterative process, with many revisions and testing iterations being typical. Having refined the occupant package, the finalised design will meet the needs of the intended user population. It will be easy to get in and out of the vehicle, a comfortable driving position will be found with controls within reach and falling to hand, and interior and exterior vision will be good.
Using people in the latter stages of this development process is a powerful tool. Because the package has been refined using so-called participatory design principles, we can have great confidence that our customers will find that it meets their needs well.
Power conducts multiple annual surveys of the automotive industry in the US as well as in other countries. This information will hopefully validate the findings of the in-house development process and will also inform future vehicle development. Paul Herriotts is the ergonomics specialist, while Paul Johnson is the specialist in cockpit and cabin packaging.
They have provided technical input to numerous iconic and successful British cars, ranging from Mini to Rolls-Royce Phantom, including recent Jaguar, Land Rover and Range Rover vehicles. As technical specialists at JLR, the authors are responsible for occupant packaging of vehicles that are sold in over countries around the world. Macey, S. Peebles, L. London: Department of Trade and Industry.
Pheasant, S. Anthropometrics: An Introduction for Schools and Colleges. London: British Standards Institution. Salvendy, G. Handbook of Human Factors and Ergonomics, 3rd ed. New York: John Wiley and Sons.
SAE J, Driver hand control reach. Devices for use in defining and measuring vehicle seating accommodation. In SAE Handbook. Motor vehicle driver and passenger head position. Motor vehicle dimensions. Accommodation tool reference point. Driver selected seat position. Positioning the H-point design tool—Seating reference point and seat track length. The basic drives to satisfy hunger, to sleep and to reproduce are supplemented by a variety of goals that may be directly related, indirectly related or independent of these motivations.
In this chapter, the nature of driving as a sub-task within the framework of human goals shall be discussed. This prediction was based on the assumption that the maximum number of chauffeurs who could be trained to drive was one million Peppers and Rogers, The prediction was based on a false assumption about the difficulty of the driving task.
The speed with which the car enabled movement of people, goods and information led to development pressure to improve the usability of the automobile. This resulted in vehicles that were relatively easy to drive and maintain compared to their forebears and so driving became viable to a much larger proportion of the By , there were in fact million cars worldwide, with annual production of around 60 million. However, the apparent ease with which driving can be accomplished is at odds with the true complexity of the task; McKnight and Adams estimated that driving is composed of more than fifteen hundred sub-tasks.
Given this complexity, it is perhaps surprising that Stutts et al. Nevertheless, this willingness to engage in additional tasks when driving has consequences. In a large-scale naturalistic driving study, Dingus et al.
Using data from the same naturalistic driving study, Klauer et al. Telephone communication in cars began in the s Klemens, when car phones first became available. The service at the time was limited; the equipment cost more than the price of a new car, calls had to be routed via an operator, connections were frequently lost and as the service gained customers, demand quickly exceeded the capacity of the network so callers often had to wait for a line to become available.
Although progress in mobile telephony was made in the latter half of the twentieth century, it was not until the advent of digital cellular networks in the s combined with further miniaturisation of the technology and improved affordability that uptake became widespread.
The use of a mobile phone enables a driver to remain contactable at all times but the digital cellular networks permit transmission of more than telephone calls. The exchange of data, combined with knowledge of vehicle position available from satellite systems and on-board computing power, creates a rich source of information for use within a vehicle and by a driver.
Design guidance e. This guidance covers the presentation of information and the design of the interfaces that enable access and use of this information by a driver. The aim of the guidance is to maximise safety and usability of IVIS. However, Lee and Strayer highlight the usability paradox as an issue for the safety of driving whereby the greater the ease of use of a system, the greater the likely frequency of use of the system.
Consequently, the cumulative time over which a driver is distracted may be greater. P2, Accessed: February These include the display of images or video not related to driving and manual text entry tasks. The guidelines state that devices should be designed to reduce the requirement for drivers to take long glances away from the roadway such that tasks can be completed using glances of less than two seconds and a cumulative time of twelve seconds with eyes away from the road.
Conversely, Strayer, Watson and Drews report the results of numerous studies that show clear impairments to various aspects of driving performance by cognitive distraction.
An example of a zombie behaviour is thermoregulation—we are not consciously aware of the processes that maintain body temperature. There is still work to be done to resolve the true extent, severity and incidence of cognitive distractions. However, the development of ADAS is reactive to dangers observed in driving—the support for the driver increases, as technology is developed to tackle threats to safety.
The NHTSA draft guidelines on driver distraction state that the regulations it contains were deliberately not made mandatory to avoid unforeseen conflict with the introduction of new safety technologies that may permit the driver to engage in tasks previously considered excessively distracting.
This acknowledges that tertiary tasks currently described as excessively distracting may become more acceptable if ADAS alleviates the task demand on the driver. Whilst the driver may be distracted, ADAS may provide additional hazard detection and appropriate responses such that the complete driver—vehicle system can still safely negotiate challenging driving situations.
An extreme implementation of ADAS is for the human driver to cede all control of the vehicle to technology, the concept of a fully autonomous vehicle. This is not a distant future concept but a present reality e.
However, whilst the technological challenges to fully autonomous cars are rapidly being surmounted, the legal issues surrounding accident liability in the event of a collision involving an autonomous vehicle are yet to be resolved Beiker and Calo, The introduction of such a radical change in vehicle control must be achieved with minimal risk of danger or injury but this must be weighed against the potential beneficial effects that vehicle autonomy may bring.
These include not only a reduction in injuries as a result of fewer driver error accidents but also sustainability benefits that may arise from more efficient use of vehicles. Whilst technological advances indicate that autonomous cars are close to market, the truth is that it will be several years before that scenario is realised. Furthermore, it is unlikely that the technology will be affordable to the majority of drivers for some time beyond its initial introduction such that widespread adoption in the vehicle fleet is many years away.
The evidence indicates that: For the majority of the time, drivers believe they have the spare mental capacity to engage in tertiary, driving-unrelated tasks. Technology is creating the opportunity for drivers to engage in a larger number of increasingly complex tertiary tasks. The usability paradox indicates that well-designed, highly usable systems, although less distracting per interaction, may result in higher cumulative distraction if they are used more frequently.
When drivers are given the opportunity to engage in tertiary tasks, a proportion of drivers will take it. The demands of the driving task are being modulated by the introduction of a variety of ADAS. ADAS that reduce risk of driver error accidents to zero are unlikely to be widespread within this decade. The way in which drivers manage competing demands from the driving task, from in-vehicle systems and by other life goals has parallels with the work of an influential military strategist from the s.
Following the Korean War, the development of fighter aircraft had pursued goals of outright speed, range and armament at the expense of agility. However, these were outclassed in Vietnam by the dedicated combat aircraft supplied by the Soviet Union. Through the s, US military strategist Col. John Boyd analysed aerial warfare tactics from the Korean War. Boyd suggested the principal advantages were that the cockpit configuration of the F permitted better vision of the combat arena; F pilots were better trained in the application of air-toair tactics and so could respond more appropriately to the developing engagement; and that the F had better control interfaces such that pilots could implement desired manoeuvres more readily.
Opponents in a dogfight must cycle through this loop, whether in an offensive or defensive position. Adapted Richards, C. Center for Defense Information, May.
However, the OODA loop has applications beyond air warfare. Figure 4. The key statements that underpin OODA loop theory adapted from Boyd, are as follows: Without our genetic heritage, cultural traditions, and previous experiences, we do not possess an implicit repertoire of psychophysical skills shaped by environments and changes that have been previously experienced.
Without a many-sided, implicit cross-referencing process of projection, empathy, correlation and rejection across these many different domains or channels of information , we cannot even do analysis and synthesis. Without OODA loops embracing all of the above and without the ability to get inside other OODA loops or other environments , we will find it impossible to comprehend, shape, adapt to and in turn be shaped by an unfolding evolving reality that is uncertain, ever-changing, and unpredictable.
Although derived with military operations in mind, these concepts can be applied usefully in the domain of driving. In its simplest format, controlling a moving vehicle requires the driver to use innate e. Perceptual information from primarily visual e. The movement of the driven vehicle within the environment and relative to other actors must be analysed and synthesised in the context of the goals of the. The driver must then decide how to respond based on the available information and on experience.
The driver can engage a repertoire of appropriate learned actions to cause the vehicle to respond in the desired manner see e. It can be seen in Figure 4. The action of driving requires the driver to continually circulate around this loop to maintain safe control of the vehicle, responding to changes in the environment and in the status of the driven vehicle.
Szlyk et al. The authors cited evidence of compensation by the AMD-affected drivers to reduce their exposure to risk by restricting driving to familiar areas, to slower speeds, to times of daylight and to simpler road configurations. This observation fits with the task difficulty homeostasis theory Fuller, but can also be explained by less effective circulation of the OODA loop. Impaired observation reduces the quality of the output in all subsequent steps.
Compared to a driver with normal vision, this would result in a driver experiencing greater difficulty achieving the same level of performance in a set driving task or the driver could experience the same level of difficulty by reducing the demands of the driving task—leading to the observed changes in driving exposure.
A driver under the influence of alcohol may suffer impairments to all stages of the loop. Alcohol has been shown to affect the ability to perceive visual stimuli Moskowitz, ; to analyse and synthesise observed information Peterson et al.
The OODA loop forms a neat framework for placing the impairments to driving caused by alcohol in context. Distractions fitting this description may impact on the driving task in different ways. Tactical behaviour operates over a time base of 5 to 60 seconds, an example of which might be moving into the appropriate lane on a highway in order to take the next exit.
Strategic behaviour takes place over minutes to days and an example might be a decision by the driver to drive the vehicle in a fuel efficient manner—which will then have repercussions at the tactical and operational levels. Each level of driving behaviour can be associated with an OODA loop.
Activity at the higher levels cascades down to influence behaviour at the lower levels. Communication technologies enable a driver to remain engaged with OODA loops relating to life beyond the driving task. The ubiquity of mobile telephony means that instant and unbroken communication is for many people the expected norm.
The relatively low frequency of road accidents means that negative feedback on distracted driving an Strategic behaviour minutes-days Technology availability Tactical behaviour 5—60 seconds. Adapted Lee, J. Preface to the special section on driver distraction. Human Factors. Winter 46 4 , — This wide-ranging document synthesised documented evidence and expert judgment on guidelines for the design of such interfaces.
It provides recommendations for the implementation of specific types of driving safety systems such as forward collision warning systems and lane change warning systems. However, the report begins by discussing general guidelines for the design of driver warnings.
The warnings delivered by the safety systems are the culmination of: The observation of a change in a particular metric. The orientation of that observation by evaluating it against relevant thresholds. The decision about what action to take based on that evaluation.
The action applied—to deliver a warning or not. A human driver is subject to competing demands such that observation is not necessarily continuous and the mental resources for orientation and decision may be loaded by other tasks.
An electronic safety system can continuously monitor the driving environment waiting to detect the specific conditions that the manufacturer has deemed constitute a safety risk and act as programmed should those conditions occur. Assuming there are no negative behavioural adaptations to the presence of the system, this will result in improved safety of the car—driver system.
Aviation has benefitted from autonomous pilot support systems, such as autopilot for many years. Such systems became commonplace after World War II and into the jet age. However, Parasuraman and Riley discussed the factors that limit the benefits that may be achieved by automation. A high incidence of false alarms may lead to disuse or under-utilisation of automation. The authors also describe automation abuse, in which the automation and implementation of functions occurs without due regard for the consequences for human performance.
Beringer and Harris describe a number of reasons why autopilot systems may fail that are relevant to the driving situation. Insufficient training of the operator—pilots who have not been adequately trained in the use of autopilot systems can over-, under- or misuse the available technology. The lack of a conceptual model of the operation of the components of automation—pilots that do not understand the. Human performance limitations—the detection of malfunctions is influenced by limitations in visual and aural perception.
Human factors and design issues—installed systems and their associated warning signals may not conform to standard human factors practices and principles.
This evidence from the aviation world, where regimes for pilot fitness to fly, and training exceed those for driving, emphasises the need for thorough research and testing in the design of ADAS. Ill-conceived systems may fulfil one or more of these criteria, resulting in sub-optimal support to the driver. Understanding all the factors that underpin the OODA loop of the ADAS and how those might support or affect the OODA loops of the driver will help the automotive industry to develop safety systems that maximise driver benefit.
Later in the twentieth century, computer technology became sufficiently small, cheap and robust to be integrated into vehicles. This opened new horizons for information exchange and communication with both the driver and vehicle. Whilst the opportunities for the driver to remain contactable via mobile telephone and data links have expanded, the demands of the driving task have not grown simpler and the legal questions around the introduction of driver support systems that may alleviate the risk of distracted driving suggest that a complete technological solution to permit drivers to engage freely in driving unrelated tasks is some years away.
Consequently, there is a dangerous transition period when the opportunities for drivers to engage in distracting tertiary activities are accelerating at a rate that is exceeding that of the development of ADAS systems that might help mitigate the effects of driver distraction.
Drivers may have many objectives that conflict with their discrete ability to control a vehicle. Considering the OODA loops that govern behaviour of the driver and of the driver—vehicle complex may enable an improved understanding of how distraction impacts performance, how driver support systems may mitigate distraction and improve the safety and efficiency of driving and to assist in the smooth implementation of autonomous vehicles.
Legal Aspects of Autonomous Driving. Workshop summary essay. Accessed: February Beringer, D. Technical Report No. Boyd, J. Available at: www. Accessed: January Boyd Breen, J. Car telephone use and road safety: Final report. An overview prepared for the European Commission. Burian, S. Effects of alcohol on risk-taking during simulated driving. Human Psychopharmacology, 17, — Campbell, J. HS Dingus, T. DOT HS Hence there was an area for enhancement in the seat, cabin space, seat height, backrest tilt, seat tilt.
Figure 3. In order to provide support for the driver while backrest angle has been proposed to decrease 80 degrees. This will lead to increase the comfort level of the driver. Thus to reduce the score a second model is proposed. The dimensions of the second model are shown in figure 3.
The assembly of the e-rickshaw with second proposed seat shown in the figure 3. The analysis was done for both positions of the driver i. As shown in the figure the new seat is comfortable for one person to sit at a time.
An angle between seat and backrest is maintained at 80 degrees to provide the support for the back of the driver. As shown in the figure the new proposed seat is comfortable and allows the driver to do his movements easily. This can lead to various musculoskeletal disorders and other injuries. This can lead to various musculoskeletal disorders like back pain, neck pain, Leg pain and trunk pain etc.
In order to decrease the chances of musculoskeletal disorders, there is need of proper modification in the design of cabin space. The modification has been suggested to increase the space of the cabin. After implementing the changes driver can easily do his movements and there is enough space for doing his legs movements.
After implementing the changes RULA analysis is done on the e-rickshaw model with the new seat. Different scores have been given to the various body parts. These scores have been given on the basis of the position of the body parts. The analysis score has been reduced from 5 to 2. The analysis score comes out to be 2 which show that there is a negligible risk and no changes were needed in the design. The analysis score with the new seat is shown in figure 3.
It is clear from figure 3. The new design of the e-rickshaw is comfortable than the current e-rickshaw used in today. The comparison between old model and the newly designed model is given in table 3. The changes done in the seat and cabin length reduced the level of musculoskeletal disorders and provide the driver a better and comfortable ride. The RULA score reducing considerably in the new proposed model of the seat at different body parts like upper arm, forearm, wrist, neck, and trunk.
These suggested changes reduced the score of RULA analysis relatively as there is the significant decrease in the ergonomic risk involved in this proposed job. Comparisons of the standard model with newly proposed models were shown in figure 3.
As shown in the figure the RULA score was reduced considerably at upper arm, forearm wrist, neck and trunk for a new proposed model. The RULA score for the new proposed model has been reduced from 5 to 1 which shows that there is a negligible risk and changes may be needed.
The RULA analysis score has been clearly shown that the score at different parts of body reduced considerably. The final score of this method indicates that the e-rickshaw drivers have a high risk of developing musculoskeletal disorders and hence the working position should be modified instantly. In the current study, an attempt has been made to lower the ergonomic risks by proposing modifications in the design of the driver seat and cabin length.
Two different seat models were proposed and the RULA analysis was done on them. These changes will allow the driver to attain a comfortable and convenient position while driving. Secondly, some modifications have been made in the dimensions of the cabin which allow the driver to adjust his posture easily and also allow the driver to move his legs easily while driving.
This is clear from the analysis results that the second seat model is best suited for an e-rickshaw driver. The advantages of the said modifications were clearly reflected in the scores that have been remarkably reduced. Hence there is a great scope for carrying out future research work in this field. Agarwal P.
K et al. Ganesh S. Jadhav et al. A Ansari and Dr M.
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