Secret Ingredients of Autonomous Vehicles Sudhanva S Great Wall India Research and Development Pvt Ltd
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hot topic these days in automotive research is autonomous vehicles. Almost all automotive companies are racing either jointly or independently with each other to dominate the market by producing them. Nevertheless, winning the race is not as much easy as anybody thinks due to many challenges to overcome from research to market.
Challenges Investment The companies have to invest considerably high amount of research since the ratio of resource to final product is higher unlike in production which forces the companies for long-term investment planning which is very unlikely to get back the investment soon in return with margin of profit. Patience and perseverance The teams working on it require a lot of patience and perseverance as there will be times when some of the researches are successful, some take longer than usual and sometimes do not succeed. The companies have to stand with the teams and encourage which otherwise may lose all the efforts of research carried out so far. Nevertheless, at the time of a crisis, it would be difficult for the companies to get the research going. Market Readiness The market has to be ready to accept the latest technology in vogue and put it to use. May it be MaaS (mobility as a service), or ownership, how do we convince the customer to take a ride assuring that it is safe? How do ride-hailing companies 36 | Telematics Wire | January 2021
assure the same to the customer? How do we convince the owner who enjoys the ride who is very much passionate about driving the car? However, FaaS (freight as a service) might not face much difficulties as it might not pose a threat to human lives riding within the vehicle. Lack of general intelligence The trolley problem that arises in most of the common people’s mind, the answers are dependent on each individual’s psychology. With such a scenario, it is difficult to train and derive an expert system to make decisions at a sickle of time that is morally correct. For example, think of an ambulance shifting a critical patient to a hospital downhill on a hilly terrain. Suppose a pedestrian is crossing the road, avoiding pedestrians might plunge the ambulance down the cliff. On the other hand, hitting pedestrians may cause death on the spot. Should the ambulance driver kill the patient or the pedestrian? Liability In case of any accidents, if the vehicle driver is said to be liable, the vehicle was never driven by a human. If the service provider is said to be liable, who never developed the system. If the manufacturer is said to be liable, who would have not had the data of scenario for which the vehicle was not developed/tested. Same goes with traffic rule violations as well. Infrastructure Infrastructure has to be geared up to handle mechanical breakdowns like towing services or nearby repair stations to where the vehicle can drive itself. Nonetheless, software updates can be
pushed over the air with the help of recent technologies. Dilemma The society may be in a dilemma for accepting the advanced developments in technology with their implications. One such example is the doubt of loss of jobs for taxi drivers. Security and safety There are many possibilities when the security of the autonomous driving system can be compromised. One of the good examples is hacking as shown in “Fate of the furious” and other movies thereby putting the lives of riders at risk. There is also a possibility that the autonomous vehicle can get stolen or crashed somewhere making it nearly impossible to track. A nightmare would be holding the vehicles hostage and demanding ransom, unauthorized collection of customers’ pickup and drop off points to list a few. With the above facts said, a good Intrusion Detection and Mitigation System, in-vehicle SoS, along with a BlackBox like the aeroplanes have, and other safety and security systems have to be designed. With all these challenges, some automotive companies are researching on SAE Level 4 Autonomous Vehicles which are developed robustly, tested rigorously and deployed to run within a geographically fenced area under controlled environments and concentrate on plunging into the market through ride hailing as a first step on deploying their vehicles on roads. While some others are working on Adasis V3 which enables the concept of Mapping and Localization for SAE Level 3 Autonomous Vehicles
