Your firm of interaction design consultants is trying to build up a portfolio of impressive work, to enable it to pitch for business convincingly in the future.
Your task is to produce a usability evaluation of an interactive system, plus a presentation of your results. You have a completely free choice of what interactive system you evaluate, except that it must not be one that you have evaluated for a previous assignment.
You may get people to help you with tasks that are easier or better done by more than one person, but you need to be very clear about what you did and what others did.
Choice of Interactive System
Possibilities include software applications such as CASE tools or games or e-commerce websites or photo editing systems; electronic devices such as remote controls for televisions or DVD players, or digital cameras, or car radios; or control panels for appliances such as microwave ovens or home heating systems; or a self-service system such as an automatic train ticket vending machine. You may, if you wish, choose to evaluate two very similar and directly competing products, and assess ways in which one is superior to the other. This works well.
Part THREE: The evaluation methodology. An exact description of the evaluation procedure to be followed, including what the methodology is, exact descriptions of user tasks being considered, instructions to be given to users in user testing, or the set of guidelines used in heuristic evaluation.
Part FOUR: The evaluation. The results of applying the evaluation procedure: what you saw test subjects doing, measurements of their performance, answers to questions and so on; or evidence for violation of particular design guidelines; or descriptions of how and why beginning users might go wrong in particular places, etc.
Part FIVE: The findings of the evaluation. The findings of your evaluation of the usability of the interactive system. Include comments on how the findings relate to the results of the evaluation procedure, and ideally about how strong the evidence is, as well as judgements of how serious you think the usability problems are. An itemized bullet point structure is likely to be easier to read than long paragraphs of text. This should also include an appraisal of the strengths and weaknesses and successes and failures of the evaluation process.
Choice of Interactive System
The 21st century is full of technological things and the technology can be seen in every part of world. With evolution of technology everything around people have been automatically control. Everything like cars, mobile phones, computer systems, buildings have become automated these days. One of the major reason behind this is, concept of networking. The networking concept have provided some of best known technologies that can be seen in modern generation. One of the major concept that is been evolving this days is the concept of the automated cars (Sutcliffe, van Assche and Benyon 2016). The automated vehicles can be explained as a self-driving, driver less vehicle that can drive itself by sensing the surrounding and navigating through roads without using any human inputs. The cars, combine a wide variety of technologies like radar systems, laser lights, camera, advanced global positioning system or GPS, computer visions and lot others (Alejandro and Lucila 2018). All these technologies all together helps the car in process of driving and detecting objects surrounding the car. This can be called as one of the most important and advanced technology that have been evolving.
The concept of the automated cars have bought some major fields like the computer vision , machine learning, automatic data transfer in a single filed. This can be said that concept of smart cars is one of leading mile stone of world. There are many advantages of this technologies, like it increases the safety of people, enhances the driving skills and reduces chances of accident that happens on roads. Although the technology is in testing phase but there have been a numerous number of changes that have been made since the beginning of technology (Dujardin, Vanderpooten and Boillot 2015). The concept of the self-driving vehicles first came in the year of 1950s and since then there have been numerous changes in the concept of the cars. One of the major milestone that have helped in process of automating cars is the concept of machine learning. With the introduction of machine learning many of the organisations like Google, Microsoft, and Uber have started some of major experiments of automated vehicles. Although there needs to be some of the major changes in the concept and the working of vehicles.
This paper illustrates the concept of autonomous vehicles and how these concept have been evolving since the past years. Further the paper illustrates the interactive system of the autonomous cars. Further the details of the interactive design is also presented in the paper. Further the details of the evaluation methodology is also given in the paper (D'Orazio et al. 2015). The fact process of the evaluation methodology is explained in the paper with the process of the technology (Greenblatt and Saxena 2015). Further the results of the methodology is well explained in the paper. Further the paper illustrates how the evaluation is done and how it can affect the working of the cars,
An interactive system can be explained the computer system characterised to ensure that that the user can easily communicate with the servers of the system (Maglaras et al. 2016). In other words it can be explained as the amount of the interaction in-between a user and the computer system. Further for maximum number of people in the world the interactive system us Macintosh or windows operating system. These are the graphical interaction system that people use. Other than this one of the major form of interaction is Human machine Interaction system (Palanque Bastide and Sengès 2016). The automated cars are the major example of HMI or human machine interaction system. With the evolution of technology and introduction off computer system Human machine interaction system have evolved to a new world namely the Human computerised machine Interaction systems.
Evolution and Advantages of Autonomous Vehicles
(Figure 1: Use case Diagram for the Self Drive Mode)
(Source: Author)
(Figure 2: Use case Diagram for the Driver Mode)
(Source: Author)
The man machine interactive system can be explained as one of the toughest system that is created. A car is full of the mechanical parts which works together for the process of the driving. The human beings helps the car in the process of the direction, locating and other such features. In a normal car or a vehicle the human beings intelligence is used for the purpose of sensing, directing and making critical decisions (Mersky and Samaras 2016). The human brain is designed in such a way that it carries out such processes and is trained from the birth for the process of the thinking. But in the concept of the automated vehicles, it comes to the work of the machine learning and hence is one of the toughest part of the system (Card 2017). Further an automated vehicle uses a numerous number of sensors, radars computer systems wires and other computerised electrical part working with the mechanical part of the car in order to make it move (Ghiasi et al. 2017). In a normal vehicle when in motions it is the work of the driver to locate the front of the car and make decisions if there is any potential danger coming, but in the automated vehicles there is no human to make the decisions. Hence the vehicle have to independently think and take a decisions if there is any such danger coming in front of the car (Baecker 2014). Hence car have to TechEd a lot in order to enhance the computer thinking and increase the communication in between the devices that are present in the system. These cars are made in order to enhance the security in the process of the driving. One of the major process for the making of the car is to enhance the driving quality of the driver and assist the driver in taking critical decisions. One of the major example of this is the if the driver of the car is taking a hash decision of overtaking then the machine can help in the process of judging the system and hence decrease the chances of any potential risk.
Further one of the other major use of this is that if driver is unconscious or in absent mind in the road then machine can help the car from getting into any accident and hence the chances of any risk (Azizi, Iqbal and Hadi 2018). I this paper the major point that will be considered is that how the autonomous vehicles helps in the process of the incrsing the security of the driver and hew this reduces the risks of driving and making critical decisions (Preece, Rogers and Sharp 2015). The history of the self-driving cars are very old, the first assistant autonomous vehicle came in the year of the 1939 which was an electric vehicle which was controlled by the electromagnetic waves in order to assist the driver. Hence from then all the other big companies started implementing the idea for this process and hence this became a revolutionary idea. In the year of the 1958 the organisation general motors came into market and made a car that was able to steer left and right using the current flows of the cars (Wali, et al. 2018). This was one of the major revolutionary idea that hit the market and hence the chances of the automated cars increase. With the rise of the technology the concept further in resent and hence the concept of the self-driving cars also increased, By the year of the 2011 all the big technical companies like the Google , Uber and some of the car manufacturing companies like the Tesla and Mercedes took idea serious made debut in autonomous vehicle (Rautaray and Agrawal 2015). This time the technology of the machine learning and concepts of the sensors and radars helped in the process of this hence the idea became one of the most successful idea. Some of the major changes were made in the year of the 2016 and when the organisation Volvo made some of the serious advancement in the concept of the automated cars and made steering wheels that can assist the drivers in the process of the controlling and assisting the driver in taking serious driving decisions and reduce the chances of the starring wheel controlling risk.
Interactive System and Human-Machine Interaction
The major functionality of the system is that the machines takes information form the sensors like the radars, infrared and other systems and processes these information in order to enhance the decisions of the driver (Gerla et al. 2014). OR if the no driver is present in the vehicle then move its own. In order to take the decisions there needs to be number of the inputs that has to be processed by the computers of the cars, like the information from the global positioning system about the portion of the car and sensing the directions thorough which the car can move (Nishimura and Itoh 2018). The second most important decisions that must be taken in to sense if there is any obstacle present in the souring area of the car (Kim 2015). This information have to be taken from the sources like the camera in order to enhance the visions, other than this information can be taken from the sources like the radar about the distance of the obstacle, sensors to sense that in which the car must move in order to reduce the chances of collision from the obstacle or the car have to hit the brakes in order to reduce stop and avoid.
As explained in the paper that the automated car is one of the most new and faced technology that have come up with the advancement of the time (Longo 2015). The organisation that are working in this kind of the technology is working on something for the future. The users of the system can vary form case to case. In the terms of cars users are drivers who can use the system for the betterment of the driving process. While if the automated vehicle something different like the cars as of a truck, or Plane, or ship then the user of the system changes (Oinas-Kukkonen and Harjumaa 2018). One of the common in all the users is that all the users are driving some format of the transport and hence the drivers of the system are the user of the system. In the terms of the car and truck the concept off the automated vehicle is one of the most used concept. The automated cars help user to enhance the security of the driving process like taking some of the critical situations while driving and some time helping the driver in doing task with an ease. Like one of the major example of this is that if the driver is driving a car and needs to use the cell phone while driving it can be a serious situation in the terms of the driving process (Schoettle and Sivak, 2014). Hence the user can switch on the auto driving mode in the car hence computer systems takes over the driving process. This reduces the chances of the error of the driver reduces chances of risk. Thus the user uses the interactive system of the car to increase the security of the car. One of the other major use of this is that the driver is in a distance to the car and needs the car at a place then can call for the car and the car auto drives to the position of the driver.
Evaluation Methodology
The Evaluation methodology can be explained as the process or tool with help of which the steeps that are needed for doing a critical and quality evaluation can be done. Following this method one can specify the level of quality of the process like the performance, problems and others (Yáñez Gómez, Cascado Caballero and Sevillano 2014). In this paper the process used for evaluation is the heuristic evaluation of the automated cars system. The heuristic evaluation can be explained as the method that is used for the purpose of the computer software that helps to identify the usability problems that can come up while the using of process (Lima Salgad and Freire 2014). The primary goal of heuristic evolution is to list the problems that can come up while using the system. In this case the heuristic evolution will help in the process of finding out the flaws that can cause serious problems in automated cars (Nojavanasghari, Hughes and Morency 2017). The process of making a heuristic evaluation is one of the most important thing to be done. In general the process of heuristic evaluation must be done while the designing process is still on so that the creators can understand what kind of problems can come up with the design of the system. The heuristic evaluation is defined by one Jacob Nelsen and is one of major process of evaluation. According to Jacob the major steps in the process of the evaluation is are
- Visibility of system status: The designer must not assume any calculation and everything must be theoretical and hence riding the chances of any error
- Match between system and the real world: The system must be capable of reposing in the user language and not machine language (Davids, Chikte and Halperin 2013).
- User control and freedom: The system must be user freely use the system and the system must be user freely
- Consistency and standards: The system must be consistent and must follow the international standers in order to ensure user enhancement
- Error prevention: There system must be prevented to any errors so that user can use if in a free manner.
- Recognition rather than recall: There must be open options for the user so that the user must not have to take critical decisions.
- Flexibility and efficiency of use: Novice user must use the system in a serious manner without any difficulty
- Aesthetic and minimalist design: There should not be present anything that is objectionable by the user
- Help users recognize, diagnose, and recover from errors: If there is any error located by the use then the machine and the organization must accept and reduce such risks
- Help and documentation: There should be made enough documentations made in order to make the user understand the system properly.
The heuristic evaluation is one of the most important thing that must be done in order to enhance the working of the software and other things. In the automated cars system the software is the core process of the working of the systems. This helps in the process of the making of some of the serious decision in order to enhance the work of the computers. In this system there is a huge work of the computer systems in the process of accessing the information and there is a huge need of human computer interactions in order to enhance the system (Lilholt, Jensen and Hejlesen 2015). The human that is the users need to keep up with the system and put on constant updates in the system so that there are very much low chances of any errors. This is to make sure that the computer system is always updated and hence there is no error from the user’s part in order to enhance the security of the services. The process of the heuristic evolution is one of the most important thing that must be done. In this process the heuristic method is chosen because of the factor that is explains all the things that are needed to evaluate the automated car systems (Preece et al. 2013). Heuristic helps in the explain that what kind of the errors can come up while the user issuing the system and how it can help the users to access and use the information’s in order to reduce the chances of any errors. Hence further this information can be used for the process of reducing the chances of this kind of the errors and hence reduce the risks that are related to the automatic car management systems.
Challenges of Autonomous Vehicles
The automated car as explained above is a technology that is generated in order to enhance the security of the driver and the passengers of the vehicle. Hence there is a serious need of the right judgement of the sensors and software is one of the most important thing that have to be made (Sivak and Schoettle 2015). The software in the automated cars are designed in such a way that it takes proper decisions in correct time in order to increase security and reduce errors in driving patters. Some of the major interactive with the user is that the vehicle giving correct decisions. The plans of the researcher and the manufactures are to present a vehicle that can help in the process of driving and provide best security options for the driver (Schoettle and Sivak 2015). The designing of the vehicle requires numerous number of calculations to be made in order to enhance the security of the vehicle. The basic purpose of the design is to ensure are to follow the rules:
1: The first thing is to ensure it can assist the driver while driving and giver proper suggestion in making description while driving (Sivak and Schoettle 2015). These include suggestions of better decisions, computerised outputs for the driver to understand the situation.
- The second thing that is to ensure is that when the driver is not present in the scenario the car can take proper decisions and driver securely though the roads without any errors.
In order to successfully run the system there is to be ensured that these aspects are maintained. The test subject that was first created for this purpose did gave a positive review of all the systems working fine (Sivak and Schoettle 2015). In order to ensure the tings the subject was passed through critical and dangerous situations in order to ensure that the work is done in a proper manner. While the auto pilot mode was on and there were no driver present in the scenario or the driving seat then the vehicle was passed though real life test like driving in a busy roadway. The results were monitored using digital system and human interactions. Some of the test that were run were, when in auto pilot mode the car needed to measure the distance of the obstacle and so that collisions would be avoided (Paden et al. 2016). Further, the vehicles test coming from the opposite directions coming were also made. Further overtaking another car process was also imitated. There tests were made in order to ensure that when the vehicle is on road then it must ensure that public and human beings around the vehicle are safe. Also in case of the huge traffics the car can easily drive though without harming the other vehicle around.
Some of the other tests were done in order to ensure that when driver is present at seat then the car must provide correct driving guides and does not override the settings or decisions of the driver and hence increase the security of the driver (Schoettle and Sivak 2014). This test were done in a very serious manner in order to ensure that the passengers and driver are safe in car along with the people around the car. These tests also ensured that all the components of the car are present in the car. Some of the major tests were made when the driver is present on the seat and like when the driver was slow in taking decisions how the car over ridded the driver settings in order to ensure security. Further checks were made for the driver errors like the opening and closing of doors, lighting systems of the car, seatbelt check and other components of the car.
Interactive Design of Autonomous Vehicles
These tests were made in order to ensure when the vehicle is in the public it is ever ready for taking all the correct decisions. The test were made numerous times in order to enhance the results that were seen of the program (Bansal and Kockelman 2018). The test subject also had to ensure that if there is any crash with the car how the system reached to it how it affected people sitting inside or people and objects near the car. Further test were made to check under which circumstances the car software failed and were unable to provide any further suggestions to the driver. All these were made in order to ensure that the passengers in the systems are secured and to ensure that the car is completely secured.
The test that have been done in with the use of the test subject provide some of the most interesting findings in the paper which helps in the process enhancing the security of the paper. The test showed what the major weak points were in the system and these can be solved with the proper follow up of the system (Charisi et al. 2017). The first thing that is to be ensured that the automated vehicles are a combination of the mechanical, computerised and human systems that have been bought together in order to make something useful for the people. The mechanical parts of the cars are connected with the computer systems in such a way that the computer systems can make use of the mechanicals parts of the car to provide better results to the people. The car is made to use some of the most advanced technologies like the machine learning, computing visions, radar systems and other such methods for the purpose of the incrsing the security options for public. The two tests that were made
- When the driver is in the automatic driving systems
- When the driver is present the decisions that are made using the machine learning.
Both the test were made in tough situations hence providing some of the most efficient results for the same. The first test showed some of the best results those were:
- The first test where done were to check how the car reacted to the obstacles that were present around and how the car took decisions in order to avoid the same (Hanna and Kimmel 2017). The results were the when the vehicle detected a motion less obstacle it searched for the other routes in order to move. But when the sensors spotted a moving obstacle it observed its movement and judge that what can be done in order to reduce the obstacle.
- When moving in free road the car took data form the sensors of the systems and matched them with the data from the GPS system in order to follow the route and if there were any obstacle came or the road ahead was no longer available which was the best possible route to reach the destination.
- One of the major weakness that was observed in this process was the car was unable to understand if there were multiple obstacles coming from different directions and stopped the motion in order to reduce the chances of any risk.
- At a point where the energy generation sources like the electric charge and the fuel finished up the machine no longer was able to drew energy is switched on the to the emergency battery mode in order to reach the refuelling stations in the shortest distance possible.
- When a high speed vehicle was coming from the opposite direction the automated vehicle detected the same in a safe distance in order to avoid collations at the point.
Hence the car although passed the maximum number of the tests but failed in some and hence reduce was needed to make learn more for the same.
The second test that was done was to ensure that when the driver is present in the car how are assisted the driver to ensure that proper decisions are taken in order to ensure that all the things are done in a proper manner (Alheeti et al. 2018). The results showed some of best reports that is very much useful for the makers and the engineers to ensure proper security of the passengers of the system. These proved that these systems was something that was needed to ensure that driver security and also passenger.
- When the car was switched on it checked all the systems of car and provided the driver with all the details in order to ensure that smooth journey was on.
- The car assisted the driver to ensure that after the driver was on seat all the doors were properly locked and the driver’s seat belt was put on in order to ensure security.
- While in the driving mode the car constantly update the drivers with updates from the sensors from the front and the rear helping the driver to take better decisions.
- When the driver was present in the seat and turned on the self-driving mode the system took over all the functionality and worked on the same manner thinking that the driver is not present in the seat (Lee et al2016). Hence ensuring proper security of the driver.
- Further if the driver if the driver was unmindful then the car gave a slight sock through the steering wheel and hence bringing the back the attention of the driver.
- Other than this while there was some of the critical situations were to be made the vehicle computerised software provide constant updates to the driver and hence production some of the best judgements for the user to ensure proper security.
The test results showed that the autonomous system was capable of taking some of the most serious situations at the time of the need. IT can be said that the software was able to handle difficult situations without any error and hence reduce the chances of any risk that is associated with the vehicle (Litman 2017). This can be said the use of this system can help in the future development of the systems which can introduce some of the major facts in order to enhance the security services of the same. Thus must be said that the automatous vehicle also needed some of the major updates in order to ensure future aspects of the working. The concept of the machine learning is one of the other major thing that can help in the process of ensuring proper and future updates of the system (Lin 2015). One of the other major thing that the vehicle was able to ensure that when the driver was present in the seat then none of the decision was taken forcefully and the driver was only notified about the actions that were needed to be taken. It was the decision of the driver whether to check the updates from the systems and accept them or not accept them.
Conclusion
Conclusion:
Thus concluding the topic it can be said that autonomous vehicles are something that can take the future on. One of the other major thing that must be said is that the driver when in the seat must not leave all the decisions for the car to take and keep a look at the updates and respect on the same. Autonomous vehicles are something that is one of the most serious thing that has a potential of making something bigger. There are many of the organisations are working on the concept of the self-driving cars in order to ensure that this technology can be brought to- the public and hence reduce the chances of the accidents. Other than this technology is also getting implemented in the planes and other forms of the transport. One of the other major sector where the concept of autonomous vehicles helped is the sector of delivery where automated delivery trucks and delivering the products. Hence it can be said these are something very interesting concepts. With the concept of Artificial Intelligence and rise of the machine learning concept these technologies have some of the great potentials and hence increases the chances of the property of the development of the same. The people must learn about this type of the technologies in order to ensure that these things are used in a proper manner. It can be said that in the recent future all the cars and other vehicles will be having the technology of the self-driving vehicles. The interactive system between the user and machine is one of the other major thing that is being developed and hence has to be ensured. The major finding in the paper was that the automated car system needed some of the major updates in the terms of the systems of the updates. This can be said the use of this system can help in the future development of the systems which can introduce some of the major facts in order to enhance the security services of the same. Thus must be said that the automatous vehicle also needed some of the major updates in order to ensure future aspects of the working. The automated cars help the user to enhance the security of the driving process like taking some of the critical situations while driving and some time helping the driver in doing task with an ease. Hence it can be said that this technology have some of the major potentials in order to increase the security and the entire working processes of the cars and other systems.
References
Alejandro, R.C. and Lucila, M.C., 2018, August. Development of an Interactive System that Senses Air Quality in Parking Lots Indicating Situations of Health Risks. In Congress of the International Ergonomics Association (pp. 870-878). Springer, Cham.
Alheeti, K.M.A., Al-Ani, M.S. and McDonald-Maier, K., 2018. A hierarchical detection method in external communication for self-driving vehicles based on TDMA. PloS one, 13(1), p.e0188760.
Azizi, L., Iqbal, M.S. and Hadi, M., 2018. Estimation of Freeway Platooning Measures Using Surrogate Measures Based on Connected Vehicle Data. In 97st Annual Meeting of Transportation Research Board, Washington DC.
Baecker, R.M. ed., 2014. Readings in Human-Computer Interaction: toward the year 2000. Elsevier.
Bansal, P. and Kockelman, K.M., 2018. Are we ready to embrace connected and self-driving vehicles? A case study of Texans. Transportation, 45(2), pp.641-675.
Card, S.K., 2017. The psychology of human-computer interaction. CRC Press.
Charisi, V., Habibovic, A., Andersson, J., Li, J. and Evers, V., 2017, June. Children's Views on Identification and Intention Communication of Self-driving Vehicles. In Proceedings of the 2017 Conference on Interaction Design and Children (pp. 399-404). ACM.
Davids, M.R., Chikte, U.M. and Halperin, M.L., 2013. An efficient approach to improve the usability of e-learning resources: the role of heuristic evaluation. Advances in physiology education, 37(3), pp.242-248.
de Lima Salgado, A. and Freire, A.P., 2014, June. Heuristic evaluation of mobile usability: A mapping study. In International Conference on Human-Computer Interaction (pp. 178-188). Springer, Cham.
D'Orazio, M., Longhi, S., Olivetti, P. and Bernardini, G., 2015. Design and experimental evaluation of an interactive system for pre-movement time reduction in case of fire. Automation in Construction, 52, pp.16-28.
Dujardin, Y., Vanderpooten, D. and Boillot, F., 2015. A multi-objective interactive system for adaptive traffic control. European Journal of Operational Research, 244(2), pp.601-610.
Gerla, M., Lee, E.K., Pau, G. and Lee, U., 2014, March. Internet of vehicles: From intelligent grid to autonomous cars and vehicular clouds. In Internet of Things (WF-IoT), 2014 IEEE World Forum on (pp. 241-246). IEEE.
Ghiasi, A., Hussain, O., Qian, Z.S. and Li, X., 2017. A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method. Transportation Research Part B: Methodological, 106, pp.266-292.
Greenblatt, J.B. and Saxena, S., 2015. Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles. Nature Climate Change, 5(9), p.860.
Hanna, M.J. and Kimmel, S.C., 2017. Current US federal policy framework for self-driving vehicles: opportunities and challenges. Computer, 50(12), pp.32-40.
Kim, G.J., 2015. Human–Computer Interaction: Fundamentals and Practice. Auerbach Publications.
Lee, E.K., Gerla, M., Pau, G., Lee, U. and Lim, J.H., 2016. Internet of Vehicles: From intelligent grid to autonomous cars and vehicular fogs. International Journal of Distributed Sensor Networks, 12(9), p.1550147716665500.
Lilholt, P.H., Jensen, M.H. and Hejlesen, O.K., 2015. Heuristic evaluation of a telehealth system from the Danish TeleCare North Trial. International journal of medical informatics, 84(5), pp.319-326.
Lin, P., 2015. Why ethics matters for autonomous cars. In Autonomes fahren (pp. 69-85). Springer Vieweg, Berlin, Heidelberg.
Litman, T., 2017. Autonomous vehicle implementation predictions. Victoria, Canada: Victoria Transport Policy Institute.
Longo, L., 2015, June. Designing medical interactive systems via assessment of human mental workload. In Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on (pp. 364-365). IEEE.
Maglaras, L.A., Al-Bayatti, A.H., He, Y., Wagner, I. and Janicke, H., 2016. Social internet of vehicles for smart cities. Journal of Sensor and Actuator Networks, 5(1), p.3.
Mersky, A.C. and Samaras, C., 2016. Fuel economy testing of autonomous vehicles. Transportation Research Part C: Emerging Technologies, 65, pp.31-48.
Nishimura, A. and Itoh, T., 2018, March. Implementation of an Interactive System for the Translation of Lyrics. In Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion (p. 9). ACM.
Nojavanasghari, B., Hughes, C.E. and Morency, L.P., 2017, May. Exceptionally social: Design of an avatar-mediated interactive system for promoting social skills in children with autism. In Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems (pp. 1932-1939). ACM.
Oinas-Kukkonen, H. and Harjumaa, M., 2018. Persuasive systems design: key issues, process model and system features. In Routledge Handbook of Policy Design (pp. 105-123). Routledge.
Paden, B., ?áp, M., Yong, S.Z., Yershov, D. and Frazzoli, E., 2016. A survey of motion planning and control techniques for self-driving urban vehicles. IEEE Transactions on intelligent vehicles, 1(1), pp.33-55.
Palanque, P., Bastide, R. and Sengès, V., 2016. Validating interactive system design through the verification of formal task. Engineering for HCI, p.189.
Preece, J., Rogers, Y. and Sharp, H., 2015. Interaction design: beyond human-computer interaction. John Wiley & Sons.
Preece, M.H., Hill, A., Horswill, M.S., Karamatic, R., Hewett, D.G. and Watson, M.O., 2013. Applying heuristic evaluation to observation chart design to improve the detection of patient deterioration. Applied ergonomics, 44(4), pp.544-556.
Rautaray, S.S. and Agrawal, A., 2015. Vision based hand gesture recognition for human computer interaction: a survey. Artificial Intelligence Review, 43(1), pp.1-54.
Schoettle, B. and Sivak, M., 2014. A survey of public opinion about autonomous and self-driving vehicles in the US, the UK, and Australia.
Schoettle, B. and Sivak, M., 2014. Public opinion about self-driving vehicles in China, India, Japan, the US, the UK, and Australia.
Schoettle, B. and Sivak, M., 2015. Potential impact of self-driving vehicles on household vehicle demand and usage.
Sivak, M. and Schoettle, B., 2015. Motion sickness in self-driving vehicles.
Sivak, M. and Schoettle, B., 2015. Road safety with self-driving vehicles: General limitations and road sharing with conventional vehicles.
Sutcliffe, A.G., van Assche, F. and Benyon, D. eds., 2016. Domain knowledge for interactive system design. Springer.
Wali, B., Khattak, A.J., Bozdogan, H. and Kamrani, M., 2018. How is driving volatility related to intersection safety? A Bayesian heterogeneity-based analysis of instrumented vehicles data. Transportation Research Part C: Emerging Technologies, 92, pp.504-524.
Yáñez Gómez, R., Cascado Caballero, D. and Sevillano, J.L., 2014. Heuristic evaluation on mobile interfaces: A new checklist. The Scientific World Journal, 2014.
To export a reference to this article please select a referencing stye below:
My Assignment Help. (2021). Usability Evaluation Of Interactive System And Interactive Design Of Autonomous Vehicles In Essay.. Retrieved from https://myassignmenthelp.com/free-samples/imat5209-human-factors-in-system-design/self-driving-vehicles-on-household.html.
"Usability Evaluation Of Interactive System And Interactive Design Of Autonomous Vehicles In Essay.." My Assignment Help, 2021, https://myassignmenthelp.com/free-samples/imat5209-human-factors-in-system-design/self-driving-vehicles-on-household.html.
My Assignment Help (2021) Usability Evaluation Of Interactive System And Interactive Design Of Autonomous Vehicles In Essay. [Online]. Available from: https://myassignmenthelp.com/free-samples/imat5209-human-factors-in-system-design/self-driving-vehicles-on-household.html
[Accessed 07 September 2024].
My Assignment Help. 'Usability Evaluation Of Interactive System And Interactive Design Of Autonomous Vehicles In Essay.' (My Assignment Help, 2021) <https://myassignmenthelp.com/free-samples/imat5209-human-factors-in-system-design/self-driving-vehicles-on-household.html> accessed 07 September 2024.
My Assignment Help. Usability Evaluation Of Interactive System And Interactive Design Of Autonomous Vehicles In Essay. [Internet]. My Assignment Help. 2021 [cited 07 September 2024]. Available from: https://myassignmenthelp.com/free-samples/imat5209-human-factors-in-system-design/self-driving-vehicles-on-household.html.