Extended Reality is one of the emerging technologies that is currently disrupting the automotive industry. Automotive OEMs (Original Equipment Manufacturers) are already using XR for creating the cars of tomorrow. These technologies can’t only improve the performance in research and development, manufacturing, sales and aftersales, they are also enhancing the connected car ecosystem and therefore also the in-vehicle experience.
The XR In-Vehicle Experience
Extended Reality features are already available in some cars but currently limited to Augmented Reality applications. Virtual Reality technology may also be available in the future but because autonomous driving is not available yet and there are still some technological and regulatory issues to solve it’s not relevant at the moment.
Head-up Displays (HUD)
The main advantage of head-up displays in current cars is that drivers get crucial information displayed directly in their field of view. Although simple HUDs were already introduced in commercial aviation back in the 70s and in the first cars in the late 80s, they are just getting more popular now.
Augmented Reality technology is also improving the in-vehicle safety because the drivers can keep their eyes on the road. The stereoscopic images used in HUDs can even adjust to the viewing angle of the driver. Looking down on the instrument cluster or head-down display will become more and more obsolete in the future and increase safety on the roads. But modern AR-powered head-up displays are also able to warn the driver of potential hazards along the way.
Features of modern HUDs
Even though most of the manufacturers are already offering heads-up displays in some models, there is still a lot of unused potentials. Common HUDs are already able to display speed, speed limits, additional road signs, gas levels or battery percentage, but some have more features. There are even some aftermarket head-up displays available that allow you to get these features in older cars.
Directions
Most manufacturers are already able to give their drivers simple turn-by-turn navigation information directly in their field of view. Mercedes for example has already started integrating AR-powered navigation systems with the new A-Class, but the new 2021 S-Class will take it a step further. The new MBUX in the S-Class is able to project navigation information directly on the street and show the drivers exactly where they have to make a turn. The Swiss startup WayRay has also revealed a Holographic Augmented Reality Navigation System with similar functionality together with Hyundai at CES 2019.
Modern HUDs are also able to help the drivers with awareness and warn them of additional hazards like pedestrians, cyclists or other cars. This feature is especially useful for blind spots in cities, larger intersections and during the night.
Some heads-up displays are also able to help the drivers with different points of interest like restaurants, parking spots or gas stations. In the future, they will also be able to show the drivers parking spots that are big enough for the car to fit in with additional information about hourly rates or parking limitations.
In the future, HUDs will also be able to display messages or calls from our smartphones directly in the field of view. This feature will not only be much more convenient, it will also stop us from looking at our phones and therefore increase safety on the road. These notifications could also include important information about a traffic jam or accident on our route directly from the manufacturer.
Besides the head-up displays, some automakers are also providing AR-powered owner’s manual apps to provide more detailed information on the functionality of the car. This feature was already available as “Ask Mercedes” in the 2018 S-Class and will also come to future Hyundai and KIA cars.
In the future, there will also be AR-powered mirrors that allow the drivers to have an unobstructed view of what’s behind them and help with avoiding not seeing a car in the blind spot. A similar feature is already used in some bigger pickup trucks and SUVs from GMC, Chevrolet and Land Rover. These pickup trucks are regularly used for towing bigger trailers and offer their drivers additional camera views and the possibility to connect different cameras from the back of the trailer to the car’s infotainment system.
Land Rover also pioneered a similar function for the front of the new Evoque and Defender. The “ClearSight Ground View” makes the front disappear and is especially useful for steep terrain.
Jaguar even went a step further and tried to augment the pillars in the car with OLED monitors and cameras. But this feature is not yet available because foldable OLED screens are not ready for the automotive industry yet.
The Reality-Virtuality Continuum is very well-known and was already defined in 1994 by Paul Milgram. His paper “A Taxonomy of Mixed Reality Visual Displays” focused on Mixed Reality (MR) visual displays. He described MR as a
“subset of Virtual Reality (VR) related technologies that involve the merging of real and virtual worlds somewhere along the ‘virtuality continuum’ which connects completely real environments to completely virtual ones.”
His virtuality continuum explains the different steps in the transition from real environments on one end to completely virtual and computer-generated environments on the other end. Although these terms have already been officially defined, some of them are still not used correctly.
Extended Reality (XR)
The term Extended Reality (XR) is relatively new. Sometimes it is also described as Cross Reality or X-Reality. It is an umbrella term for all combinations of real and virtual environments that are currently existing. XR will also include all immersive technologies that get developed in the future. Extended Reality technologies are already in use in several industries. Because they are also continuously getting cheaper and better they will be used even more in the future. The most popular XR technologies at the moment are Augmented Reality (AR) and Virtual Reality (VR).
Mixed Reality is often used interchangeably with Augmented Reality (AR) but that’s wrong. It is an umbrella term for everything between the real world and the virtual world – including Augmented and Virtual Reality. MR blends the real world with the virtual world and creates complex environments. Because of these similarities, it is also hard to distinguish AR, VR and MR devices and applications. The most popular Mixed Reality device is the Microsoft HoloLens.
Augmented Reality describes a real-world with an overlay of computer-generated information. Because there is no immersion into a virtual world, the real environment is still the center of information. The real world is just expanded with a projection of animations, infographics, videos, images, 3D objects, or other digital content. Currently, there are four different types of Augmented Reality devices:
Head-up displays – used in modern cars
Holographic displays – for example from Samsung
Smart glasses – Google Glass
Handheld AR – modern smartphone and tablet cameras
But existing smart glasses and holographic displays are still expensive and therefore also not available to a lot of people. According to different sources, it will take at least 5 to 10 more years until AR technology is mature enough and available for everybody. Augmented Reality is currently mainly used for games like Pokémon GO or image filters on Snapchat and Instagram but this technology has a lot more potential for all industries.
Augmented Virtuality (AV) is one of the lesser-known immersive technologies. It is also a Mixed Reality technology and is situated between AR and VR on the Reality – Virtuality Continuum. Most of the time, AV applications and devices are just described as Mixed Reality. The term Augmented Virtuality is almost exclusively used in scientific papers. Examples for AV include computer games with real players, virtual concerts with real artists and real people on virtual backgrounds in video conference calls.
Virtual Reality (VR)
Virtual Reality is generally achieved with a head-mounted display and describes a fully immersive experience in a completely virtual world with no real objects. VR systems are using hardware, software, sensors and displays to create a computer-generated environment and allow the user to move in this world. With the help of controllers, it is also possible to move objects, arms or guns. Virtual Reality is currently mainly used for playing games but it also has a lot of potential for the health sector, the military, engineers and other industries.
„Virtual Reality refers to immersive, interactive, multi-sensory, viewer-centered, three-dimensional computer-generated environments and the combination oftechnologies required to build these environments.“
This video shows a perfect example of a VR Game (Beat Saber) in an AV Video. The player is just able to see the boxes, scores and lightsabers during the playing experience but we can see an AV Video with the player in front of the virtual world.
Resources
Books
Virtual und Augmented Reality (VR/AR), Grundlagen und Methoden der Virtuellen und Augmentierten Realität from Ralf Dörner, Wolfgang Broll, Paul Grimm, Bernhard Jung, 2019
Medieninnovationen AR und VR, Erfolgsfaktoren für die Entwicklung von Experiences from Elle Langer, 2020
Artificial Intelligence is getting more and more important in the automotive industry. The value of AI in automotive is expected to approach 10 billion Euros in 2024. When talking about Artificial Intelligence and cars, most people are just thinking about self-driving cars. Despite the fact that AI is a key technology to enable cars to drive autonomously, there are a lot more AI-powered services available in modern connected cars.
All Advanced Driver Assistance Systems (ADAS) like emergency braking, blind spot monitoring and lane keeping systems also depend on Artificial Intelligence. These systems are not only providing more safety and more convenience on the road, they are also helping customers, automakers and regulators to build trust in AI. This trust will play an important role when AI takes over the control of the vehicle in self-driving cars.
But Artificial Intelligence is not limited to driving features. It has the potential to optimize every process along the automotive customer journey. Some processes are already relying on AI and would not be possible without it.
Driver Monitoring
Artificial Intelligence is not just able to monitor the road and surroundings. It is also improving the safety by keeping an eye on the driver. AI is able to analyze if the eyes are on the road, how distracted the driver is and if the driver is getting tired. Depending on the status it could inform the driver to keep the eyes on the road, propose a small break at the next gas station or even safely stop the car when the driver is not reacting because of a serious medical problem.
Another example for improved safety could be the use of AI during accidents. Artificial Intelligence is able to change the seat position to a better position and how the airbags are going off depending on the position, height and weight of the driver milliseconds before the impact.
Driver Recognition
AI is also able to detect if there is a driver in the vehicle, which driver is in the car and if the driver is actually allowed to drive the car. This feature is especially helpful when different members of a family are sharing one car. The car recognizes the driver and automatically adjusts the seating position, mirrors, ambient lighting, default temperature, favorite playlist and many more. Artificial Intelligence will be one of the key factors of vehicle personalization in the future.
Connected vehicles need a lot of data for delivering all the services. AI powered platforms ensure that this data is available to the services all the time.
Traffic Forecasting
Artificial Intelligence is especially useful for analyzing a lot of data in a short time. AI powered traffic forecasting is taking traffic data from the past and predicts the future traffic situation based on data from similar days, time and conditions. It also helps with faster options for avoiding unexpected traffic jams.
Predictive Maintenance
Traditional cars are alerting their drivers with check-engine lights, oil lights and other combinations of lights in the dashboard when the damage has already happened. Sometimes this is just too late and accidents occur because of faulty parts. Connected vehicles are already monitoring all sensors with the help of AI and detect problems before they affect the driving. Artificial Intelligence is also able to monitor the wear and tear of critical parts based on the driving style, road conditions and mileage. This monitoring could also inform the driver that a specific part is going to break soon and should be replaced before something happens. In addition to hardware maintenance, automakers can also provide over the air (OTA) software updates for fixing bugs in the software, improving the functionality of the ADAS or changing the design of the infotainment without the need to visit a dealership first.
But the applications of AI in automotive are not limited to the vehicle itself. Artificial Intelligence also has the potential to optimize different processes during the manufacturing of the car.
Assembly Line Robots
While assembly line robots were already used in the 1960s, they are now also helping the humans and working with them instead of alongside them on different steps of the process. Assembly line robots are not only shortening the time a car spends in the assembly line, they are also improving safety and helping to avoid injuries like back problems due to heavy lifting. Robots are already automatically moving materials, different car parts and the car itself between the assembly lines in a lot of factories. With the further development of AI, these robots will be optimized even further.
Quality Control
Another important part during the manufacturing process is the quality control. AI is not only able to detect irregularities in materials, it is also able to identify faulty parts before they are used in a car and predict if it is cheaper to repair or replace the part completely. Image recognition also helps with identifying flaws during the manufacturing process like scratches in the paint job or small damages in the bodywork.
Supply Chain Automation
Artificial Intelligence also allows automakers to improve their supply chain management. It is able to predict the materials needed for the upcoming production based on the orders, optimize storage in the warehouses and even check the quality of the delivered parts and determine if they are good enough for using them in a car.
Automotive Insurance / Insurtech
Insurance companies are also starting to use AI for risk assessment. They are creating risk profiles based on personalized data from previously owned and rented cars, driving style and accidents. Based on this risk profile Artificial Intelligence is able to predict how safe the driver is going to be and give every driver a personalized offer. This process could significantly lower insurance rates for safe drivers, while others may have to spend more than they are spending now.
AI will also help with filing claims after an accident. A special app could guide drivers with detailed instructions after an accident and explain exactly which videos, photos and descriptions will be necessary to process the claim as fast as possible. Correctly created claims could even be processed by AI again and give an immediate response about the next steps. It would even be possible that AI analyzes the videos and pictures of the damaged car and tells the driver which repair shop is able to fix the problem, how long it will take and what’s covered by the insurance.
AI and In-Vehicle Infotainment Systems
In-vehicle infotainment systems (IVI) are also known as in-car infotainment systems (ICI) and provide an unique combination of information and entertainment. These systems are the only digital component of a car and are therefore also getting more important. Infotainment systems in modern cars include audio and video content, games, social media, navigation, phone calls and even in-car office features. Despite this range of features, only 56 percent of car owners are currently satisfied with their IVI.
In-car infotainment systems are also a major factor when drivers are purchasing a new car. Modern vehicles have already evolved from hardware-driven machines to software-driven electronic devices. Because of this shift, AI is also becoming more important for ICI.
AI-powered personal assistants like Siri and Alexa have already changed the way people are interacting with technology in their homes and on their phones. These voice-controlled assistants are now also shifting the automotive industry. Voice and gesture controlled interfaces allow an easy and intuitive interaction with in-car infotainment systems. With the help of these systems drivers are able to interact with their car, without taking their eyes off the road.
MBUX (Mercedes Benz) is a good example for a voice-controlled in-car personal assistant which can change nearly every setting of the infotainment. The AI behind this system learns the drivers habits and preferences and is even able to improve from time to time. MBUX is also capable of indirect command recognition. That means that it is able to recognize sentences like “Hey Mercedes, I’m cold” and automatically changes the temperature.
Individual Marketing
In-vehicle infotainment systems can also be used for individual marketing. With the help of Artificial Intelligence, drivers and passengers could even get personalized offers or suggestions based on their preferences, needs and habits – displayed directly on the in-car infotainment. Companies could even target potential customers when they are driving by their shops – The possibilities of AI in the automotive industry are endless.
While Artificial Intelligence is getting used more now than ever before, the concept is not new. John McCarthy was already talking about “the science and engineering of making intelligent machines” back in the 1950s. Because of his numerous contributions to the field of Computer Science and AI he was also called the father of AI. Artificial Intelligence is a sub-field of Computer Science and is about how machines imitate human intelligence. It is rather about being human-like than becoming human. AI is also commonly described as any task performed by a machine that would have previously been done by a human, but there are a lot of different definitions. These definitions are shifting based on the goal the AI system has to achieve.
“The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
– Oxford Dictionary
“artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.”
– The Encyclopedia Britannica
Types of AI
Artificial Intelligence can be divided into different types. These types can either be based on the abilities/capabilities or on the level of intelligence/functionalities of the system.
Narrow AI is also known as Weak AI or Artificial Narrow Intelligence (ANI) and is focused on one single “narrow” task. This type is not able to do anything that was not programmed and targets only a single subset of cognitive abilities.
The Artificial Narrow Intelligence (ANI) is the most common type of AI at the moment. It also includes more complex systems which are able to teach themselves with Machine Learning or Deep Learning. Most people nowadays are already using this type of AI on a daily basis. It is used in all personal assistants like Siri and Alexa, chatbots on websites, translating software, the Google page ranking system and many more. Narrow AI is also used in the health sector and is able to diagnose cancer and other illnesses with a very high accuracy by analyzing images from MRI’s.
General AI
General AI is also known as Artificial General Intelligence (AGI) and these systems will have the same capabilities as humans. They can learn, perceive and understand like a human being. But because there is currently not enough knowledge about the functionality of the human brain to develop these systems, they are still under development and will not be available anytime soon.
The best attempts on Artificial General Intelligence also include simulations on the fastest supercomputers. Back in 2011 the Fujitsu K computer was able to simulate one single second of neural activity in about 40 minutes. The successor of this supercomputer, the Fugaku, is the fastest supercomputer at the moment and has a processing power of about 415 petaFlops. But the US government is already building an even faster supercomputer named Frontier. Frontier will have a processing power of about 1.5 exaFlops and will go online later this year. This supercomputer will also be the first machine with more processing power than the human mind (about 1 exaFlop).
Super AI
Super AI is also called Artificial Super Intelligence (ASI) and will be more capable than any human. This technology is currently far away from becoming real but it would be the most capable form of intelligence on earth. Artificial Super Intelligence would also be able to perform incredibly well in creative tasks like design, decision making and even in emotional relationships. These systems will be better than any human at everything they do and may even take over the world.
Reactive Machines are the oldest form of Artificial Intelligence and therefore also have extremely limited functionalities. These systems do not have a memory and are not able to learn from previously gained experiences. Reactive Machines are only using present data for solving specific tasks.
One of the most popular examples would be IBM’s Deep Blue. This machine defeated chess grandmaster Garry Kasparov in 1997. Deep Blue is able to identify the pieces on a chessboard, knows how each of them is moving and makes predictions about the next moves. But it ignores everything that happened before the present moment. It is looking at the chessboard after every move and starts deciding from there.
Limited Memory
Limited Memory is the most common type of functionality based AI’s. It is able to learn from data and base the decisions on this data. This type of Artificial Intelligence is using data from big databases as a training for future problems. Limited Memory is currently used for voice assistants, image recognition, chatbots, cars with autonomous driving capabilities and self-driving cars.
Theory of Mind
Theory of Mind will be the next level of AI systems. This type of Artificial Intelligence will be able to understand needs, emotions, beliefs and thought processes and will therefore be especially useful for researchers. Theory of Mind will be successful when systems are able to truly understand human needs.
Self Awareness
Self Awareness will be the final stage of Artificial Intelligence and is currently just existing hypothetically. Systems of this type will also have emotions, needs, beliefs and even desires of its own. Despite this technology being decades away from becoming real, people are already thinking about these systems and if they will take over humanity and enslave all humans.
Machine Learning is one of the most popular and also most important subsets of AI. It helps AI systems to learn and improve their capabilities without being programmed. Systems are becoming better and better at specific tasks because of it.
We are already using systems with ML in our daily lives. The most popular technologies powered by Machine Learning include personal assistants, targeted advertisements on social media, image recognition software and traffic predictions on services like Google Maps.
ML uses Neural Networks and other algorithms and can be divided into the following categories: Supervised Learning, Unsupervised Learning and Reinforcement Learning.
Neural Networks
Neural Networks are a subset of Machine Learning. They are modeling themselves by creating an artificial network with an algorithm based on the human brain. Neural Networks are trained by databases with a large set of labeled data. The most common databases consist of images and the correlating labels.
If you feed a Neural Network with pictures of thousands of traffic signs and their label, it is able to inspect and analyze these pictures, learn a formula based on the data, divide it into different layers and finally put the signs into different categories. A Neural Network that was trained like this is able to recognize every common traffic sign next to the road, categorize it and show the driver the current speed limit for example.
Deep Learning
Deep Learning is a Machine Learning technique and teaches machines how to learn. It is also called Deep Neural Learning and is a subset of Neural Networks.
Deep Learning is also used in the automotive industry. Systems like driverless cars or voice assistants use it to analyze thousands of hours of videos and images. Self-driving cars can learn how to drive and navigate on specific roads by studying road patterns, driving habits of existing humans and other vehicles on the road. But this process also requires a lot of data to work properly.
Artificial Intelligence is already used across nearly all industries. AI is completing our words as we type them, vacuuming our floors in every corner of the room, providing directions while avoiding high traffic roads, matching up passengers for ridesharing services and recommending what we should buy next on Amazon or watch next on Netflix.
The ongoing pandemic is not only impacting our daily lives. It is also impacting a lot of different industries. While the automotive industry was already changing drastically before the pandemic, the coronavirus is accelerating different trends even more. These trends will likely also influence the new normal after the pandemic.
Different surveys show that people are finding more and more comfort in car ownership. The usage of personal cars nearly doubled in some areas after the outbreak of the coronavirus. Additionally people in China and the US who do not own a car intended on purchasing a car for health and safety reasons. Tech-savvy car shoppers have also increasingly used services for comparing models, prices and deals online. The Google search volume for “best car deals” has grown by 70% globally in March 2020 compared to the same time one year prior. Because most of the car dealerships were closed, a survey also showed that customers would be willing to use review videos, digital showrooms, online configurators, at-home test-drives and vehicle delivery as an alternative to a visit at their local car dealership. While dealers did offer vehicle delivery and car configurators online before the pandemic, only a few of them had the resources to execute a full vehicle purchase online.
Because of the lockdown and the restrictions from the government, auto shows and large conferences and therefore also vehicle launches had been canceled. While some manufacturers shifted to online launches for their new vehicles, some of them were just delaying them. Online vehicle launches and the car buying process will not be the only parts of the connected customer journey that need to be optimized in the future. To be able to achieve the best car experience possible, all processes along the customer journey have to be improved in the future. Good examples for digital customer experiences can be found in the consumer-tech sector from companies like Amazon, Airbnb and Netflix.
The Car Experience
Brand Touchpoints
Brand touchpoints are all points of contact where a potential customer comes into contact with the company. They can either be digital or physical. Examples for digital touchpoints would be websites, e-mail, social media profiles, apps, extended reality applications and many more. Physical touchpoints in the automotive industry include showrooms and the employees there, all company buildings, employees of the company itself, the actual car, the packaging and all print products like catalogues and posters. All touchpoints together can be visualized with a customer journey.
A customer journey illustrates how a user gradually comes into contact with different touchpoints and what he/she is doing there. Customer journeys can be created for different processes or even long time usage. For the best car experience possible, it is important to improve and adapt the interaction on all touchpoints.
The car buying journey is an example for a customer journey in the automotive industry. It includes every interaction throughout all touchpoints between an automaker and their potential client.
During this journey, about 95% of new car buyers are researching online before actually contacting a dealer. This number is also likely to increase even more in the next few years. The online research includes searches on Google, watching Videos on YouTube, engagement on social media and visiting the company website. Currently about 60% of the total time a customer is spending on buying a car is spent online. While Tesla customers already have to buy the entire car online and therefore also spend a higher percentage of time online, most automakers still require their customers to go to a dealership for purchasing the vehicle. With the development during the current pandemic and the changing needs of the connected customers it is also more likely that customers from different car manufacturers will spend more time online in the future. More automakers will need to enable their customers to buy a car online without visiting the dealership first. Digital dealerships and virtual showrooms might also help improve the car experience.
Despite the fact that automotive customers are usually well informed, only 1 in 3 car buyers knows the exact model and make of the car they are going to buy. Potential customers in the automotive industry also rely on more personalized information from multiple channels and devices.
Every customer journey can be divided into different phases. These phases may have different names or are split up in even more phases depending on the company and product but generally they are quite similar across industries. The typical car buying journey for new car buyers is divided into the following phases.
Awareness
The first phase is all about awareness. It starts when the potential customer realizes that he/she has a problem or a specific need. In the automotive industry this problem could be that the current car is breaking down or that the customer simply wants a new car. This phase also includes organic searches online about how to solve the problem, seeing an ad for a product or solution online or engagement on social media. Potential customers might skip all of the following stages and buy the product directly but this mostly happens with smaller and cheaper products and is unlikely to happen during the car buying process.
Information Gathering / Interest / Consideration
The second phase starts when the potential customers are actually beginning with research. This research could include a simple Google search, watching videos about the product or a detailed car review on YouTube, reading a professional review, visiting the website of the automaker and more. During this phase the buyer acquires knowledge about different brands and products that will most likely solve his problem. This phase ends when the potential customer has narrowed down a list of options.
Tied in with the information phase is the decision phase. The transition from information to decision often starts with the online configuration of the dream car. During this phase the potential customer also starts visiting a dealership for further information and getting a tangible feeling for the car, the features and the quality. A test drive with the actual car plays an essential role because it is the best way to get in contact with the full car experience before actually buying it. In most cases, except for Tesla customers, this phase also marks the leap from online to physical contact with the brand and product. Because new car buyers visit only two dealerships on average before going to the next phase, it is really important to focus on giving every customer the best experience possible.
Purchase / Action
During this phase the potential customer is actually buying the product after checking deals and offers from different dealerships. This phase also includes final decisions, price negotiations and the actual signing of the contracts. But this phase is actually not the end of the car buying process and a smooth transition to the next phase is especially important for the dealership.
Retention / Service / After Sales
The retention phase is one of the hardest but also most important phases for the dealership and automaker during the car buying process. It is all about building a long lasting relationship with the customer. This phase already starts with the first interaction between dealership and buyer during the decision phase. It also includes every activity after the purchase process and is essential for turning a buyer into a loyal customer. The goal of this phase is that the customer is coming back to this dealership for every service and ideally also the purchase of the next vehicle. That is the reason why it is important to convince the buyers that this dealership is the best place for all their vehicle needs. This phase also includes personalized emails or offers already considering the exchange value of the current car or invitations to special events and test drives.
Example
The following image shows a good example of a automotive customer journey. This map tracks the customer through all phases of the car buying process and also includes the different touchpoints along this journey. But because every client is different and takes different paths when buying a car it is also important to consider different routes and touchpoints depending on the target audience.
Connected cars are vehicles that are able to connect with different services, devices or other connected cars over a network. They are able to connect to smartphones, laptops, traffic signals and many more. Another important feature of connected cars is the emergency call function. This feature is able to register accidents based on the data from different sensors and automatically calls emergency hotlines. It is also called eCall in the European Union and all new car models, approved for manufacture after 31 March 2018, must have the emergency call function installed.
Reliable networks for connected cars can only be established with powerful telematic systems. Dedicated short-range communication (DSRC) and cellular vehicle to everything communication (C-V2X) are the most promising systems that are able to handle the workload while still staying fail-safe.
DSRC is based on the newest wifi standard and tailored to the needs of the automotive industry. It is a highly secure and high-speed communication channel that is able to see around corners and operate in extreme weather conditions. The main goal of DSRC is a seamless communication between vehicles and roadside infrastructure.
Cellular-V2X is a relatively new worldwide standard by the 3rd Generation Partnership Projects (3GPP) using cellular standards of the fourth and fifth generation (4G and 5G). It enables direct communication between road users and infrastructure to ensure a more fluent traffic flow and more traffic safety. C-V2X uses the same spectrum like DSRC for the communication between two devices but is also able to connect to cellular frequencies.
At the moment it is not clear which of these two technologies is going to be used for connected cars in the future. It could be either of them or a combination of both of them. Automakers from different countries could also use different technologies based on the country’s infrastructure.
While the concept of the “Connected Car” is not new in the automotive industry, the necessary technologies and communication standards have only been made available in the last few years. The vehicle to everything communication (V2X) is the umbrella term for the following categories of communication technologies that are needed for connected cars.
Vehicle to Network (V2N)
The V2N communication allows vehicles to connect to cellular networks and therefore also the communication with the V2X system. Because of the vehicle to network connectivity vehicles are becoming a device, just like smartphones and tablets. V2N allows cars a reliable interaction with other vehicles, devices, pedestrians and important infrastructure.
Vehicle to Infrastructure (V2I)
V2I communication is an important part of intelligent transportation systems (ITS) and allows bidirectional communication between cars and roadside infrastructure. It includes detailed data about the traffic gathered by different vehicles, data from sensors used in infrastructure like traffic lights, cameras, parking meters and broadcasted data like weather conditions, speed limits and road conditions. The main goal of this communication is to enhance safety and prevent accidents with real-time information for the drivers. But this information gets even more important in the future, when autonomous vehicles get available to the public.
Vehicle to Vehicle (V2V)
The V2V communication enables different vehicles to connect to each other. Because this communication is done wirelessly with DSRC frequencies it works similar to a mesh network. Its main advantage is that every car becomes a node and can therefore capture and send data and even retransmit data from other cars. This system allows the cars to get a 360 degree representation of the surroundings (about 300m radius) in real-time. Because of this overview it is able to inform drivers of other cars or autonomous vehicles. This overview could include information like speed, destinations and locations of traffic jams or accidents. V2V communication enhances road safety and could, according to NHTSA, prevent more than 600.000 accidents in the United States per year.
Vehicle to Cloud (V2C)
V2C communication uses the access to cellular networks to exchange data with the cloud. This data could include navigation services depending on the current traffic situation, remote diagnostic for car maintenance, over the air (OTA) updates for the vehicles software and communication with internet of things devices or digital assistants. V2C could also play an important role in carsharing in the future. The car from the carsharing service could download the drivers preferences and automatically adjust seat, mirrors, ambient lights and music playlists according to his past usages of the service.
Vehicle to Pedestrian (V2P)
The V2P communication is one of the newest and probably also hardest technologies to master. Its main goal is the reduction of accidents with pedestrians. While the other categories allow communication with smart sensors in different objects and devices, pedestrians and children are not wearing sensors to create awareness about their presence. That is the reason why automakers are currently using systems like LiDAR, 360 degree cameras and blind spot warning to detect pedestrians and cyclists. Another part of the vehicle to pedestrian communication gets more important when autonomous cars get available to the public. Currently, the driver can signal pedestrians that they are able to cross the street but if there is no driver left the autonomous car has to communicate with the pedestrian as well.
Vehicle to Device (V2D)
V2D is one of the most popular and well known communication categories. It allows vehicles to exchange data with smart devices, usually via Bluetooth. The most popular applications of this technology are Apple CarPlay and Android Auto. They allow smartphones, tablets and smart watches to seamlessly interact with the vehicles infotainment system and are already available in a lot of different cars.
Vehicle to Grid (V2G)
The V2G communication is especially useful for all electrified vehicles. It allows bidirectional data exchange between the different types of electric vehicles (PHEV, BEV, FCEV) and the smart grid. V2G will allow the next-gen electric grid to balance loads more efficiently, reduce utility bill costs and shorten waiting times.
Connected cars are also transforming the in-car experiences like never before. While digital interfaces are still tiny and have a horrible usability in a lot of cars, some automakers are already improving their in-vehicle infotainment systems and therefore also the whole in-car experience.
Tesla
Despite Tesla being known for their tech-first approach and their great software, their in-car infotainment is actually not that great if you take a closer look. Tesla’s car interface will be great somewhen in the future, when the cars are driving autonomously but not at the moment. The Model 3 for example has only one large screen in the center of the cockpit. There are nearly no additional buttons, switches or levers. Everything is displayed and controlled on the huge display. The driver has to look at the screen for every interaction and therefore also has to take the eyes off the road. One Tesla owner in Germany even recently (August 2020) got a one month driving ban because he crashed into trees while trying to change the speed of his windshield wipers.
Because the infotainment system of the Model 3 just got a huge UI Update (2020.48.26) in the last weeks, there is no up-to-date video about the detailed functionality of the new version. There is only a video about the previous version of the software. But while the new interface looks a lot nicer now, it still has a similar functionality. The windshield wiper settings for example now got a dedicated button in the bar on the bottom. Detailed changes will be analyzed and published by a lot of Tesla Model 3 owners soon.
Mercedes Benz
Because the first version of Mercedes MBUX was already a good system with multiple screens and a decent experience, especially for such an old and traditional company, there were high hopes for the following generations of MBUX. While the visual style may look outdated to some designers, the functionality was still a huge step forward in the right direction and created an advantage over infotainment systems of similar brands. The second generation of MBUX will be released alongside the new S-Class and started shipping a few weeks ago. Because of this there is currently no full review of the new infotainment system..
Mercedes also recently announced another new version of the MBUX infotainment system for the upcoming EQS. The EQS will be the electric counterpart of the new S-Class and is announced for later this year.
Porsche
Porsche’s first electric car, the Porsche Taycan, also has a completely new infotainment system. Because the Volkswagen group has just recently started to create their own infotainment software in-house and plans on hiring 10.000 designers, analysts and engineers to build one platform for all subsidiaries, the Porsche Taycan Infotainment is still using another system. (https://www.kurbos.com/de/projekt/porsche)
The Taycan infotainment is minimalistic, well structured and also usable. This infotainment has one main goal – supporting the user. While it currently is one of the best infotainment systems on the market, the lower central screen can also lead to a lot of driver distraction and therefore also decrease the safety.
Creating the perfect in-car infotainment system is nearly impossible, but a lot of different automakers are already working on improving their in-car experience. While there is no perfect system at the moment, there are a lot of different good solutions for specific problems available. Each system has unique advantages and disadvantages. The main goal of the next generation in-vehicle interfaces should be to provide a safe, usable and enjoyable experience for the driver and passengers. With the release of new electric vehicles like the Lucid Air, Byton M-Byte and Rivian R1S in Europe later this year, the development of in-car experiences will get more and more interesting and competitive in the upcoming years. Another interesting change for in-vehicle infotainment systems will be the change from human drivers to autonomous vehicles.
Shared mobility describes the shared usage of transportation when it is needed. They can either be shared after another or simultaneously and include the sharing of buses, vehicles, motorcycles, bicycles, scooters and more. Especially with the rise of autonomous vehicles, shared mobility will play an important role in urban areas. Shared mobility is currently divided into the following groups. Some of them may not be available or work differently during the ongoing COVID-19 pandemic.
source: https://www.sae.org/shared-mobility/
Public Transit
Public transit is one of the most popular and well-known modes of shared mobility. It includes publicly or privately owned fleets of buses, trains, subways, ferries, airplanes and more. They usually operate on fixed routes and predefined schedules. Because public transit is primarily available in large cities, there are already a lot of different services available for suburbs and rural areas.
Micro mobility is mainly used for short trips and as a fast first and last mile option in cities and densely populated areas. It includes all small and low-speed vehicles but the most popular options at the moment are e-bikes and e-scooters.
Bike sharing is available with electric motors and without in different cities worldwide and allows users to rent bikes for a few minutes up to one hour or longer, depending on the rental company. There are two different versions of bikesharing – docked and dockless. While docked bikes are normally available on a dense network of static locations throughout the whole city, dockless bike sharing is relying on smart, GPS-enabled bikes with integrated locks that can be unlocked with an app on the smartphone.
Scootersharing is working like the dockless bike sharing and is currently becoming more and more popular. Most of the service providers are using electric kick scooters with a tempo limit which can be driven without a drivers license.
Car sharing is a service that provides a fleet of cars for a limited time. Because it is usually available for a few hours, it is ideal for mid range trips, shopping or smaller cargo. This service is usually limited for members who have to pay a monthly fee and undergo a screening by the provider before renting their first car. The hourly rates for the cars usually include fuel, insurance, parking and tolls and depend on the demand and day. The cars can be pre-booked with an app and accessed with the phone or a special access card. Sometimes the fleet of cars is also sourced from the members itself. This version of the service is also called peer-to-peer car sharing. Normally these services include electric vehicles as well as cars with combustion engines. Car sharing is also available in Graz. It is currently provided by TIM.
Another automobile-based mode is called ride on demand. This service is usually provided by transportation network companies (TNCs) or taxis. The most popular TNCs are Uber and Lyft. Ride on demand is also called ride hailing or ride sourcing and is used for airport travel or recreational trips most of the time. This service is especially useful for low or moderately populated areas or suburbs with bad connectivity to public transport. It is also available outside of business hours of other services and more convenient for tourists.
The last mode in this group is called micro transit. It is a different form of ride on demand and is currently primarily available in major cities and their suburbs. Micro transit is an extension of the traditional ride on demand. It bridges the gap between ride on demand and classic public transport. This service consists of a combination of flexible and scheduled routes and on demand mobility and mainly uses larger vehicles and vans for up to 20 people.
The commute-based modes can also be called ridesharing and are about transporting a few people with similar origins and destinations. Most of the time ridesharing is based on arrangements between private people and therefore not commercial. These arrangements are between the drivers, who are already making a trip, and their passengers, who want to go in the same direction or to the same destination.
The easiest form of ridesharing is carpooling. Carpooling could be done on a set schedule with the same driver and passengers for daily commuting to university or work or randomly with different individuals on every trip organized by services like BlaBlaCar.
For larger companies or business districts in suburbs or more rural areas it could also pay off to administer vanpooling for their employees. Vanpooling works like carpooling but because of the higher amount of passengers it is also more complicated to organize. Usually the passengers pay a monthly fee that covers all the costs including insurance, maintenance and gas.
MaaS is a highly efficient concept for user centered and custom mobility. This service is based on the actual needs of the users and tries to deliver the easiest and most convenient transportation solution for their passengers. It is bundling the most important means of transport into one package and therefore one seamless experience. The goal of MaaS is to create one single application for access to all modes of mobility. Depending on the users preferences it combines different mobility services to deliver the best user experience possible. The ultimate goal of this concept is to be able to offer a more convenient, more sustainable and cheaper alternative to the usage of private cars. MaaS will also be able to avoid congestions during rush hours on public transport. Megacities like London and Singapore are already gaining experiences with this service while companies in Austria and Germany just started. Because these services need to work seamlessly across all channels, different companies like Daimler, BMW, Uber, Siemens and Google are already working on a solution. The most promising MaaS services in Germany at the moment include Jelbi (Berliner Verkehrsbetriebe), Free Now (Daimler and BMW) and Free2move.
MaaS in Austria
The concept “Mobility as a Service made in Austria” (MaaS miA) describes how to implement MaaS in Austria. This concept was released in September 2019 and is divided into the following levels.
Level 0 describes the current situation in Austria. The transportation services of the different companies are currently not connected and the passengers have to buy tickets on their own.
Level 1a is characterized by the connection of information between available mobility services. On this level the passengers will be able to continuously plan their entire trip with public transit but they still have to buy their tickets separately when changing lines or means of transportation. One example for a service like this would be the app qando.
Level 1b also integrates private mobility services like car sharing in this process.
Starting with level 2 the passengers will be able to book and pay their entire trip with the MaaS-System. The payments for the separate services will be handled by the MaaS service company.
MaaS miA-Level 3 describes the step from providing mobility services to holistic experience, including social and environmental aspects.
An electric vehicle is a vehicle that is powered entirely or partially by electric motors. The term electric vehicles is an umbrella term for all electric vehicles – E-Scooters, E-Bikes, E-Cars and E-Trucks.The biggest advantage of EVs is that they have a huge potential to significantly reduce pollution in the long term. There are already a lot of different types of electric vehicles on the market. Each type has its own advantages and disadvantages. Most of the following types are currently only available for cars, but some of them are also available for trucks.
Mild Hybrid
Mild hybrid cars use an electric motor, powered by a small battery. This motor is only used to provide assistance to the petrol or diesel combustion engine. It is providing additional power during accelerations and helps to make the powertrain more efficient. Mild hybrid cars cannot run purely electrically but they reduce the fuel consumption and emissions, especially in heavy traffic. The small battery is solely recharged by regenerative braking. Mild hybrid cars are currently sold by nearly every automaker but most consumers don’t really know it.
source: https://www.volvocars.com/at/v/cars/xc90
Full Hybrid
Full hybrid cars are also called self-charging hybrids. They are using a combination of an electric motor and a conventional combustion engine. Depending on the situation, these engines can work together or independently. That means that fully hybrid vehicles can also drive fully electric or fully on diesel or petrol. But most of the time the system of the car is intelligently distributing the power between the two engines to deliver the best and most efficient result. Pulling away and driving at low speeds is mostly done electric, while the combustion engine is more efficient when cruising on highways. For quick acceleration both motors can also combine their power and work together. The battery of self-charging hybrid cars can be charged by regenerative braking, like the mild hybrid car, or by the combustion engine itself. That is the reason why full hybrid cars do not need to be plugged in at all. Full hybrid cars are also offered by a lot of different automakers. But the most popular, especially for taxi drivers, self-charging hybrid that nearly everybody knows is the classic Toyota Prius.
source: https://newsroom.toyota.eu/media-library/
Plug-in Hybrid (PHEV)
The plug-in hybrid is a more advanced version of the classic full hybrid car. Most of the time, plug-in hybrids also offer the driver different modes to choose between power sources for themselves. In addition to that, they also offer larger batteries and therefore also allow the driver to drive longer distances fully electric. Because of these larger batteries, plug-in hybrid vehicles have to be plugged in to a charger to be able to fully charge the battery. While short trips like daily commuting and shopping can be done fully electric and emission free, plug-in hybrids also allow long trips without charging the battery by mainly using the combustion engine. Popular plug-in hybrid powered cars include the VW Golf GTE, Hyundai Ioniq and a lot of different models from Audi, BMW and Mercedes with the small letter “e” in the model identification.
Battery electric vehicles are also called pure electric vehicles or fully electric vehicles. Most people also refer to BEVs when talking about electric cars, even though there are a lot of different types of electric cars. Battery electric vehicles do not include a conventional combustion engine. They are solely powered by electric motors and large batteries and therefore also need to be charged with dedicated chargers at home, work or during a trip. While BEVs can be more expensive to buy than equivalent combustion or hybrid cars, they are cheap to run on a daily basis and also offer emission free traveling. Because battery electric vehicles need to be charged to be able to drive, they also rely on the availability of charging infrastructure, especially during longer journeys. The most popular automaker for BEVs is Tesla. The Tesla Model 3 is also the battery electric car with the most units sold, followed by the Nissan Leaf, Tesla Model S and Renault Zoe. New models with this type of powertrain are announced nearly every month and include the Audi e-tron GT, Ford Mustang Mach-E, Polestar Precept, BMW i4, VW ID.4, Hummer EV, Lucid Air/SUV, Rivian R1S/R1T, Byton M-Byte, Lightyear One, Faraday Future FF91 and the Tesla Cybertruck.
Fuel cell electric cars are also powered fully electrically, but they do not need to be plugged in to a charger. The fuel cells in these cars are using hydrogen from the on-board tank and oxygen from the air to generate electricity. Because the only waste product from this process is water, FCEVs are also considered as zero emission vehicles. While these on-board tanks have to be refilled only every few hundred miles and the process is much faster than the charging process from battery electric vehicles, the hydrogen refueling infrastructure is very limited at the moment. Another disadvantage of fuel cell electric vehicles is that they are more expensive compared to other types of electric vehicles and that there is just a limited amount of models available. The most popular fuel cell cars currently on sale are the Hyundai Nexo and Toyota Mirai. Mercedes-Benz also had the GLC F-Cell on sale but they stopped the production earlier this year. Hyundai is currently also testing trucks in Switzerland that are using two fuel cells of the Hyundai Nexo.
Autonomous vehicles are capable of sensing the environment and fully operating the vehicle without the help of human drivers. In fully autonomous cars, the driver is not required to do anything at all while still being able to get from point A to point B. While most of the cars that can be purchased at the moment offer advanced driver assistance systems (ADAS), autonomous cars are currently only tested by different automakers and startups. Because distinguishing the different levels of automation was important as well, the SAE (Society of Automotive Engineers) defined 6 different levels of driving automation back in 2014. They are ranging from Level 0 (fully manual) to Level 5 (fully autonomous).
The terms self-driving and autonomous are currently often used interchangeably, but actually they have a slightly different meaning. While self-driving cars would fall under SEA Level 3 or 4 because a human driver has to be present all the time and also constantly ready to take over, autonomous cars could go anywhere without human help and are therefore limited to Level 5.
Making these fully autonomous vehicles is harder and more expensive than most of the startups predicted. That is the reason why these self-driving startups are now teaming up with tech giants like Alphabet (Google) or Amazon and big automakers like General Motors or Volkswagen. Aptiv has established a partnership with Hyundai, Waymo with Jaguar, Cruise with GM, Voyage with Fiat-Chrysler and Argo AI with Ford and Volkswagen. Currently, the only big exception that is building self-driving vehicles and operating fleets of them on their own is Tesla. But there are already rumors that Tesla is thinking about merging with or buying Daimler (Mercedes Benz).
Waymo
Waymo is one of the most well known players in this industry. It started as Google Self-Driving Car Project back in 2009. Waymo has already done millions of miles of testing in Arizona and California with additional safety drivers monitoring the system behind the wheel. From October 2020 they also started their services with fully driverless taxis in Phoenix, Arizona. While the Waymo vehicles are still a little too cautious around pedestrians, there are already a lot of really positive reviews of their driverless service.
source: https://waymo.com/press/
Cruise
Cruise, acquired by General Motors back in 2016, unveiled their shuttle van in San Francisco back in January 2020. The name of the orange, white and black van with sliding doors and two sets of three seats facing each other is Origin. It is meant to be shared by riders in a ride-hail service and will be starting in San Francisco. Cruise is planning on offering their service significantly cheaper than current, human-powered ride-hail services like Uber and Lyft. They also announced a separate Origin configured for carrying packages. Cruise is currently starting their self-driving-taxi service with five modified Chevrolet Bolts in San Francisco with the plan to operate truly driverless cars before the end of the year.
Zoox, acquired by Amazon for roughly $1.2 billion in June 2020, recently announced their robotaxi. The company was founded in 2014 and has been working on their robotaxi for the last six years now. Zoox is planning on using their autonomous vehicles on a ride-hail network in large cities like Las Vegas and San Francisco. Because of this, their vehicle is able to drive bidirectionally and also offers a tight turning radius. These robotaxis will be able to run up to 16 hours on a charge and travel fully autonomously at speeds up to 75 miles per hour (approximately 120 kilometers per hour). Zoox has not announced a release date yet, but the technology from their robotaxis has been tested with other cars in San Francisco since 2017. The design of the Zoox vehicles is similar to a lot of other different autonomous vehicles revealed over the past few years like the Cruise Origin. Due to its rectangular shape, the robotaxi platform could also be used for packages.
“We’ve made the decision to maximize the interior space and minimize the exterior space,”
Jesse Levinson, Zoox’s Co-Founder and CTO
Tesla
While Tesla’s Full Self-Driving (FSD) feature was released as a closed beta to a few selected vehicles in October 2020, they are also aiming to release their FSD for all compatible Teslas by the end of this year. Since this feature was only rolled out to a limited number of people and is currently updated regularly, there is also limited knowledge about the functionality and safety of these features.
“Despite the name, the Full Self-Driving Capability suite requires significant driver attention to ensure that these developing-technology features don’t introduce new safety risks to the driver, or other vehicles out on the road,”
Jake Fisher, Senior Director of auto testing at Consumer Reports
The rapid development of new technologies in combination with the drastic change of consumer preferences offers great potential for the digitization of the automotive industry. The preferences of the younger and technically savvy generations are not only changing the behaviour of the consumers, but also the relationship between them and their vehicles. To be able to meet these needs, automakers are currently prioritizing the in-vehicle experiences like never before. They are trying to optimize their customer experience across all facets of the car journey. From vehicle entry and ignition to parking at the final destination, everything is going to change during the ongoing digitization of the automotive industry.
source: https://www.lucidmotors.com/media-room
Nobody can anticipate how the industry will look like in 10 to 15 years but the current industry leaders are able to shape this process. Shaping this evolution is currently based on the development of the following disruptive and technology driven trends.
Autonomous Vehicles
Autonomous or self-driving vehicles are currently not publicly available but a lot of different car companies are already testing semi autonomous and autonomous cars on public roads. These self-driving cars will minimize the need for human drivers and transform the everyday mobility of millions of people. Advanced driver assistance systems (ADAS) are already slowly preparing the consumers, regulators and insurance companies for the next step.
Driving automation is divided into six different stages (Level 0 – 5) defined by the SAE levels of automation. At the moment, most of the publicly available cars are limited to SAE Level 2 automation, where the human driver still has to monitor the environment. With the step to the next level, SAE Level 3 automation, the system is able to monitor the environment independently and the driver will be a passenger for a part of the trip. These semi-autonomous cars will drastically change the interaction between drivers and their cars. The driver’s role will shift from driving the car to supervising the automated driving system until he has to take back control over the steering wheel and gas pedal.
https://www.youtube.com/watch?v=EzylsrXtkxI
Technological challenges like the development of artificial intelligence, machine learning and deep learning will be the key factor for the speed of this transformation. But country specific regulations and the acceptance of the consumers are additional hurdles for the release of semi-autonomous and autonomous vehicles. By reducing accidents based on human errors or fatigue, self-driving cars will help to improve the safety of individual and public transportation in the short term, lead to more productivity in the mid term and to a much better traffic flow in the long term.
Fully autonomous cars will also allow their drivers to use the transit time during their ride for additional activities. Work while commuting, scrolling through social media on the way to the grocery store or even sleeping while long distance road trips will become normal in the future.
Connected Cars
Modern cars are much more than a simple way of transportation for getting from point A to point B. For many people, a car is also an extension of themselves. Connected cars are also extensions of the customers home, school or office. A modern car is equipped with hundreds of sensors and systems that are connected to the internet as well as the surroundings to be able to deliver more convenience to the drivers. With these sensors, cars are already part of the Internet of Things and will get more and more connected features in the future. Current functionality of connected cars include smartphone apps with the most important car data, automated maintenance planning based on the driving habits or automatic emergency calls after accidents. In the future they will also be able to communicate with other cars, traffic lights, fuel stations or even toll stations to be able to deliver the most convenient ride possible.
The digitization of the automotive industry will drastically change the way we are interacting with our vehicles. Starting with a fingerprint sensor on the door for unlocking the car and personalization of the seating position, light color and social media channels up to a completely immersive entertainment hub with new retail channels. The passenger experience will become the most important feature of connected cars in the future.
Electrification
The electrification of all vehicles is currently the best and most effective way for reducing emissions. This process will also be the basis for making mobility 100% emission-free in the future. Since fossil fuels are limited on our planet and their harm done to the environment is huge, the European Green Deal is planning on becoming climate neutral by 2050.
Currently, electric vehicles (EV) are too expensive, have poor batteries and also a poor range. The charging infrastructure is not where it should be and most of the time the charging stations are also not powered by renewable energy and therefore also not emission-free. Lower battery costs and more charging stations are new possibilities for all electrified vehicles. Electrified vehicles do not only include battery powered electric cars like a Tesla, they also include hybrid cars, plug-in hybrids and hydrogen fuel cell cars. With the combination of classic combustion engines and electric engines, hybrid cars will make up a large percentage of future vehicle sales and be especially popular for people living in less dense populated areas.
The biggest growth for all electrical vehicles will take place in large or densely populated cities. Especially megacities like Tokyo or Paris or cities with strict emission regulations and consumer incentives like a lower tax, special parking or driving privileges will profit more from the electrification of the automotive industry than the rural areas.
Shared Mobility
Shared mobility is not really a new concept. The first car sharing was already offered back in the 1940ies in Switzerland. But the tech-enabled shared mobility we know today just started a few years ago. It is an umbrella term for all services where the actual vehicle is shared like the classic car sharing and where just the ride is shared like public transportation, taxis, carpooling, ride sharing and ride hailing.
Shared mobility will become a viable alternative to classic vehicle ownership in the future, especially in big cities. If people stop paying for the vehicle itself and are starting to pay for mobility, they will also be able to choose the best solution for every specific purpose rather than using their cars as all-purpose vehicles. Everything will depend on the purpose. If you just want to commute to your office for a few kilometers on a sunny day in summer you may just need a E-Scooter or small car, while you may need a bigger car for a shopping trip with your whole family. This focus on the purpose may also lead to the development of vehicles optimal for only one specific task to fully meet the needs of the consumers.
source: McKinsey – Auto Report 2030 (2016)
When self-driving cars are available to the public, shared mobility will be a key driver for the growth of the automotive industry. There are already early signs that the importance of car ownership in megacities is declining in favor of shared mobility. Owning a car in a big city has a lot of different disadvantages. From limited and more expensive parking, to higher congestion fees and more traffic jams. Everything is getting more and more complicated when owning and using a personal car in a densely populated area. While the people living in rural areas will still prefer owning a private car, there will be a huge potential for a lot of completely new business models and also new players in the industry along this transformation.
Shared Autonomous Electric Vehicles (SAEV)
Shared autonomous vehicles will have the largest disruptive potential by simply combining all four trends to one concept. From the customer’s point of view all SAEV’s will be more flexible and more personalized while still emitting less exhaust fumes and noise into the environment. Additionally they will also take up less time because they are moving fully autonomously and drivers can do whatever they want during the ride. Shared autonomous vehicles will also be more accessible for people with physical disabilities or people without a drivers licence and also more affordable because you only need to pay for mobility when you really need it.
The future in-vehicle experience does not only offer a huge potential for automakers and industry leaders. It is also a great opportunity for UI and UX designers. While the in-vehicle user experience has been quite static for decades, automotive interaction designers have already fundamentally changed the in-car experiences in the last few years. Automotive interaction designers will be the bridge between the highly advanced technologies and the passengers in future. Enabling the passengers to access these technologies in a user friendly and simple way will be the biggest challenge for interaction designers in the automotive industry. Possible research questions for interaction designers could include but are not limited to:
How can autonomous vehicles (SAE Level 3-5) gain the trust of the passengers?
Is the current usage of ADAS in SAE Level 2 cars helping to gain trust in the systems and preparing passengers, insurance companies and regulators for the next step?
How is the role of the driver changing during the development of more advanced cars with more and more self-driving features?
How are we interacting with our cars in 10 years?
How can we adapt and optimize the in-car experiences to the needs of different drivers and passengers?
Is the usage of touchscreens safer and better than the usage of classical knobs for different purposes?
How does the in-vehicle infotainment of the future look like and what does it offer to the different passengers?
How does the most convenient ride look like for different target groups?
How immersive is the future in-vehicle experience going to be?
Does the usage of extended reality in cars add value for the passengers?
Is artificial intelligence going to affect the design of the in-vehicle infotainment systems and how the passengers are interacting with it?
Is shared mobility going to skyrocket after the release of the first SAE Level 5 cars?
Is shared mobility a viable alternative to classic vehicle ownership throughout Europe?
Resources:
Accenture – Mobility as a Service; Auto 2030 Report; StartUs Insights – Automotive Industry Report; CBInsights – Future Of In-Vehicle Experience; Frances Sprei – Disrupting Mobility; Experiences per Mile – 2030 Report; PWC – Five trends transforming the automotive industry;
Best practise examples for connected cars in 2020:
Tesla Infotainment, Rivian Infotainment, Lucid Air Infotainment, Byton Connected Car, Mercedes-Benz MBUX, Porsche Connect, Polestar Android Automotive, Audi MMI, BMW iDrive
R&D Centers of car manufacturers, Center for Automotive Research; Harman; McKinsey Center for Future Mobility; Accenture Automotive; Startus Insights Automotive; CBinsights Automotive; Deloitte Digital – Ericsson Automotive; IBM Institute for Business Value
