UX and CX for Autonomous Cars by [Name]
Course
lecturer’s Name
Institution
state
Date
UX AND CX FOR AUTONOMOUS CARS AND PASSENGERS
Autonomous digital cars are like airplanes; they are faster than standard cars though never comfortable due to the bad feelings that human beings experience when they try boarding them. It is never easy for someone to build trust in an Artificial Intelligence machine designed by a human being. Referring to the manual and automatic cars that we are used to, human beings look at the face of their drivers to make sure everything is in control. Such instinctive behavior won’t fade because of the new technology, which will enhance self-driven cars.
In recognition of the importance and value of the available information, self-driving cars will be roaming through the streets without needing a human passenger. Such will be a technological achievement that will create an intuitive human experience in the future. The designers need to develop human solutions to curb the fear of commuters. The digital services will add value to the travel experience garnered by the travelers.
Self-driven cars will improve the inclusiveness and mobility of old human beings, especially those living with disabilities. The visually impaired would be of benefit since the technology will overcome some of the cognitive impairments. It will be fuel-efficient too. Those future cars are designed and tested in some industries. Industrial simulation is applied to predict the amount of damage that they will cause if they fail. Bayesian regression algorithms in conjunction with artificial neural network regression will be used during the design to process the dependent and independent variables and design the regression line’s shape. Although the technology s evolving rapidly, several UX problems will be encountered; safety of the cars, the designs, and the act of convincing human beings to trust the self-driving vehicles.
Design
These self-driven cars will rely on actuators, sensors, artificial neural networks, and other processors to execute the programs. In the presence of the sensors, they can maintain a geographical map of their surroundings based on the sensors placed on the vehicles. These sensors include radar detection sensors, which will track other surroundings (Topher, 2019) environment for sending a signal. Once the distancing password is sent, the high-definition cameras will detect road signs, traffic lights, pedestrians around, and other wheeled vehicles that will be around the corner. The light detection sensors (Lidar) will bounce back the light across the car’s surroundings to detect the road’s edges, distances between other vehicles, and identifying single and multiple line markings along the route.
The wheels of the vehicles will be fitted with ultrasonic sensors, which will detect road curbs and other cars in parking environments. Finally, sophisticated vehicle software will process the actuary and sensory input; it will interpret the signals and send instructions to other car actuators, which will control the vehicle’s braking, acceleration, and steering. The coded rules, material escape algorithms, futuristic modeling, and recognition of objects will help the software heed traffic rules and regulations in navigating obstacles along the road (Dagnino, 2021).
For example, Raphael is a visually challenged civil servant who travels 3 miles to his destination. With the technological advancement of self-driven cars, Raphael will be able to book his seat using a mobile application that will be availed to support the progress. The mobile application may use a USSD code to prompt the booking of the seats. His child though computer illiterate, will be able to book a seat for his father. The following day, he will be alerted by an SMS which will be read loudly by a voice recognition device in his phone to remind him about his journey. The vehicle will track where Raphael is situated and self-drive itself to the place to pick him. Raphael will then be dropped at his workplace. During A client books a seat in the evening, the same process will be repeated to drop him home.
Legal and Ethical Considerations for the Proposed Innovation of Autonomous Cars
It is ethical to produce the proposed self-driven cars since they will affect the livelihood of the human beings that will board them. The algorithms that will run the car software are intelligent since they will be built with prestigious skills in collaboration with other experienced experts to improve the car technology.
These cars will be safer compared to human-controlled vehicles, which are prone to accidents. The self-driven cars will be programmed to heed the traffic laws. They will be excellent in avoiding obstacles since they will be able to detect materials with the help of the sensors. They will also have a better visual interaction than the naked human eye on the roads.
Autonomous cars will transform the world into a better place since they will improve the lifestyle of human beings. They will improve on the traffic flow by controlling congestions in the cities. Fuel consumption will be minimized since the sensors reduce a small amount of electrical energy (Dietrich et al., 2014).
However, technology will pose threats to the current society. The data received by the GPS locator will pose a danger to society. There is a fear that hackers may hack and command the cars remotely. The fear of system failure raises a concern for the human beings who will use these cars—a situation on the pedestrian safety and bias on the logarithmic regressions. The technical barriers such as malfunction also slow the development of these vehicles’; difficulty in establishing a standard measure in the development of autonomous vehicles has slowed the production and designing rate. Various governments have found it difficult to strike deals to diversify the production rates. These transformations will abundantly make our future luminous for policy-making and facilitating the benefits while curbing various unwanted outcomes of this upcoming technology.
References
Topher, Chris, 2019. Autonomous vehicles, Enterprise Singapore.
Anon, Google search. Available at: https://www.google.com/search?kgmid=%2Fm%2F01kl97&hl=en-KE&q=Self-driving%2Bcar&kgs=9238bd6dc5767975&shndl=0&source=sh%2Fx%2Fkp%2F1&entrypoint=sh%2Fx%2Fkp [Accessed October 3, 2021].
Dietrich, B., Plachy, E.C. & Norton, M.F., 2014. Analytics across the enterprise: How IBM realizes Business Value from Big Data and Analytics, Upper Saddle River, NJ: IBM Press.
Dagnino, A., 2021. Data Analytics in the era of the industrial internet of things, Cham, Switzerland: Springer Nature Switzerland AG.
Kavoura, A., Sakas, D.P. & Tomaras, P., 2017. Strategic innovative marketing: 5th IC-SIM, Athens, Greece 2016, Cham, Switzerland: Springer International Publishing.
UX and CX for Autonomous Cars by [Name]
Course
lecturer’s Name
Institution
state
Date
UX AND CX FOR AUTONOMOUS CARS AND PASSENGERS
Autonomous digital cars are like airplanes; they are faster than standard cars though never comfortable due to the bad feelings that human beings experience when they try boarding them. It is never easy for someone to build trust in an Artificial Intelligence machine designed by a human being. Referring to the manual and automatic cars that we are used to, human beings look at the face of their drivers to make sure everything is in control. Such instinctive behavior won’t fade because of the new technology, which will enhance self-driven cars.
In recognition of the importance and value of the available information, self-driving cars will be roaming through the streets without needing a human passenger. Such will be a technological achievement that will create an intuitive human experience in the future. The designers need to develop human solutions to curb the fear of commuters. The digital services will add value to the travel experience garnered by the travelers.
Self-driven cars will improve the inclusiveness and mobility of old human beings, especially those living with disabilities. The visually impaired would be of benefit since the technology will overcome some of the cognitive impairments. It will be fuel-efficient too. Those future cars are designed and tested in some industries. Industrial simulation is applied to predict the amount of damage that they will cause if they fail. Bayesian regression algorithms in conjunction with artificial neural network regression will be used during the design to process the dependent and independent variables and design the regression line’s shape. Although the technology s evolving rapidly, several UX problems will be encountered; safety of the cars, the designs, and the act of convincing human beings to trust the self-driving vehicles.
Design
These self-driven cars will rely on actuators, sensors, artificial neural networks, and other processors to execute the programs. In the presence of the sensors, they can maintain a geographical map of their surroundings based on the sensors placed on the vehicles. These sensors include radar detection sensors, which will track other surroundings (Topher, 2019) environment for sending a signal. Once the distancing password is sent, the high-definition cameras will detect road signs, traffic lights, pedestrians around, and other wheeled vehicles that will be around the corner. The light detection sensors (Lidar) will bounce back the light across the car’s surroundings to detect the road’s edges, distances between other vehicles, and identifying single and multiple line markings along the route.
The wheels of the vehicles will be fitted with ultrasonic sensors, which will detect road curbs and other cars in parking environments. Finally, sophisticated vehicle software will process the actuary and sensory input; it will interpret the signals and send instructions to other car actuators, which will control the vehicle’s braking, acceleration, and steering. The coded rules, material escape algorithms, futuristic modeling, and recognition of objects will help the software heed traffic rules and regulations in navigating obstacles along the road (Dagnino, 2021).
For example, Raphael is a visually challenged civil servant who travels 3 miles to his destination. With the technological advancement of self-driven cars, Raphael will be able to book his seat using a mobile application that will be availed to support the progress. The mobile application may use a USSD code to prompt the booking of the seats. His child though computer illiterate, will be able to book a seat for his father. The following day, he will be alerted by an SMS which will be read loudly by a voice recognition device in his phone to remind him about his journey. The vehicle will track where Raphael is situated and self-drive itself to the place to pick him. Raphael will then be dropped at his workplace. During A client books a seat in the evening, the same process will be repeated to drop him home.
Legal and Ethical Considerations for the Proposed Innovation of Autonomous Cars
It is ethical to produce the proposed self-driven cars since they will affect the livelihood of the human beings that will board them. The algorithms that will run the car software are intelligent since they will be built with prestigious skills in collaboration with other experienced experts to improve the car technology.
These cars will be safer compared to human-controlled vehicles, which are prone to accidents. The self-driven cars will be programmed to heed the traffic laws. They will be excellent in avoiding obstacles since they will be able to detect materials with the help of the sensors. They will also have a better visual interaction than the naked human eye on the roads.
Autonomous cars will transform the world into a better place since they will improve the lifestyle of human beings. They will improve on the traffic flow by controlling congestions in the cities. Fuel consumption will be minimized since the sensors reduce a small amount of electrical energy (Dietrich et al., 2014).
However, technology will pose threats to the current society. The data received by the GPS locator will pose a danger to society. There is a fear that hackers may hack and command the cars remotely. The fear of system failure raises a concern for the human beings who will use these cars—a situation on the pedestrian safety and bias on the logarithmic regressions. The technical barriers such as malfunction also slow the development of these vehicles’; difficulty in establishing a standard measure in the development of autonomous vehicles has slowed the production and designing rate. Various governments have found it difficult to strike deals to diversify the production rates. These transformations will abundantly make our future luminous for policy-making and facilitating the benefits while curbing various unwanted outcomes of this upcoming technology.
References
Topher, Chris, 2019. Autonomous vehicles, Enterprise Singapore.
Anon, Google search. Available at: https://www.google.com/search?kgmid=%2Fm%2F01kl97&hl=en-KE&q=Self-driving%2Bcar&kgs=9238bd6dc5767975&shndl=0&source=sh%2Fx%2Fkp%2F1&entrypoint=sh%2Fx%2Fkp [Accessed October 3, 2021].
Dietrich, B., Plachy, E.C. & Norton, M.F., 2014. Analytics across the enterprise: How IBM realizes Business Value from Big Data and Analytics, Upper Saddle River, NJ: IBM Press.
Dagnino, A., 2021. Data Analytics in the era of the industrial internet of things, Cham, Switzerland: Springer Nature Switzerland AG.
Kavoura, A., Sakas, D.P. & Tomaras, P., 2017. Strategic innovative marketing: 5th IC-SIM, Athens, Greece 2016, Cham, Switzerland: Springer International Publishing.
