New technologies have always fascinated us. Urban mobility is undergoing a drastic change, not only from the point of view of strategic and environmental sustainability, but also with respect to new technologies that are going to change the urban landscape. AI in transport sector is all-set to bring about a paradigm shift in improving transportation and urban mobility.
The emergence of new technologies along with artificial intelligence (AI), machine learning (ML), and Internet of Things (IoT) can help improve the targeted use of vehicles. These technologies will form the mainstay of automated vehicles (AVs), and automated vehicles artificial intelligence (AVAI).
What can AI in transport really do?
The implementation of AI in transport has tremendous scope and potential. Here is what it is really capable of doing.
- Provide an improved driving experience on the road.
- Support monitoring and management of traffic.
- Create a strong base for solutions that are going to be a part of urban transport.
The challenge with AI in transport
The big question mark with AI in transport is how it will be placed in the perception of the common man in the year ahead. The inclusion of societal ethics will also raise questions.
- Societal ethics and individual morality may not always be different. Many times, both overlap and the disagreements are resolved legally.
- With AVAI, the AI-based algorithms will have to be trained and programmed on taking the right decisions.
- The major challenge would be whether AI in transport will learn from an individual driver or the society that includes millions of drivers.
Biasness raises big question marks
AI bias is an anomaly of AI algorithms. Using training data, AI systems learn to make decisions. AI systems can exhibit biases that arise from their programming and data sources.
- Artificial Intelligence will be indispensable to any autonomous city in urban mobility.
- AI in transport will constantly analyze large data sets through big data.
- However, modeling with big data may result in biases, may even be imperfect, and in many cases wrong as well.
- Even though AI as a technology has got tremendous scope and potential in improving human life and urban transport, biased datasets raise big questions.
- For example, AI in transport may be able to reduce carbon emissions and protect people from accidents, however they may also negatively change cities unalterably.
Societal ethics vs individual morals
It is important to take into consideration what people feel about how AI should be programmed, whether AVAI should learn its behavior from the society at large (ethics), or learn from an individual’s personal behavior (morals). What also needs to be factored in is whether the programming of AVAIs has anything to do with the willingness of people to adopt AVs?
AI-powered algorithmic systems usually function without any human intervention. However, considering the risks and sensitivities in the transportation sector, the key decision would be whether to give preference to ethics which the society considers correct, or instead, give priority to what is correct from an individual’s point of view.
If AVAIs are programmed as per societal ethics, many individual buyers may not trust investing in automated vehicles. Investing in such vehicles may appear to be financially unattractive to them.
Bridging the gap between ethics and morals is vital
For effective and faster adoption of AV technology, it is essential to bridge the gap between ethics and morals.
- It is a fact that automated vehicles are likely to witness an increase in demand.
- For faster and better adoption of automated vehicles, it is important for companies to understand the perception of humans.
- Research has shown that even people are divided in their perception, whether ethics or morals should control and guide the AVAIs.
- Policymakers need to bridge this gap that exists for urban mobility in autonomous cities.
- Research has also indicated that young males who have favorable perceptions about AVs, are more likely to adopt them.
Perception of risk
Although automated vehicles will most likely improve road safety, there will also be an element of risk at play. Here is how perception of risk will influence the decision of an individual to go for AV or not.
- Perception of risk is a key factor in the willingness of an individual to adopt AVs.
- The perception of risk is situational. People perceive risks differently, especially when dealing with new technologies.
- For example, when driving a vehicle, people are more willing to allow an AVAI to cause harm to a pedestrian walking on the road than themselves while driving.
- Notably, people who might have been involved in an accident in the past, are more likely to go for AV, and consider traditional driving risky.
- Perception of risk has a direct correlation with the trust element. Higher the trust, lower is the risk of perception.
- The main concern that is negatively impacting trust in automated vehicles is safety, specifically accidents and crashes.
As automated vehicles continue to proliferate at various levels in a society, the likelihood of individuals interacting with them and becoming familiar will also increase. This in turn may foster higher trust levels and reduce the risk of perception, thus increasing the chances that AI in transport will become the new normal in the modern world.
It is highly likely that there will be drastic changes in urban transport in the near future. The concept of shared mobility will most likely become true. With shared mobility, travelers will be provided with mobility solutions for their trips. These won’t be requiring vehicle ownership. Rather, vehicles would be rented and shared with the rest of the community. AI in transport will reduce the congestion on roads, lower fuel consumption, and polluting emissions as well.
With AI in transport, the urban cities must plan a seamless transition towards automated vehicles. This transition needs to be an inclusive one without any digital divide over new technologies being implemented in urban mobility. This means a complete rethink and change in mindset about the urban mobility systems, including logistics, infrastructure management, public transportation services, etc.
