Law and Policy Dimension of Flying Taxis in Dubai

Transportation is critical; it has always been a priority for governments and is the most dynamic pillar of communities worldwide. Smart cities are constantly searching for new modes of transportation to reduce congestion and improve the climate. Many smart cities around the globe have investigated air mobility, which has the potential to improve cities in terms of mobility and the environment. “Air Taxi” “flying car” or “flying taxi” is one of RTA’s initiative, aimed at achieving Dubai’s self-driving mobility strategy of transforming 25% of Dubai’s flights into self-driving vehicles by 2030. The RTA is collaborating with the Dubai Civil Aviation Authority, the General Civil Aviation Authority, and Dubai Air Navigation Services to develop a unique comprehensive framework for running such vehicles in Dubai. Air taxis are environmentally conscious, sustainable vehicles with vertical take-off and landing capabilities (e-VTOL). State-of-the-art technologies in this field have been developed globally, with a maximum range of 241.4 kilometers and a maximum speed of 300 kilometers per hour. It has the capacity for four passengers as well as an air taxi commander. In the beginning, the fly taxi Dubai will operate autopilot then the next step will be to operate autonomously, also Experts estimated the price of the trip between AED 500-800.

However, numerous factors raise concerns among UAE residents regarding the use of flying taxis. First, the regulatory landscape is not clear. Secondly, there is safety concerns. People’s mistrust stems from inherent concerns that are difficult to quantify and models, such as safety, trust, privacy, accessibility, and ethics. In this project, we will examine the regulatory landscape of drones and assess its adaptability to flying taxis. In addition, we will collect data through an online survey intended for UAE residents in order to understand their concerns and the factors influencing them. We are approaching the adoption of flying taxis in the UAE as a binary classification problem, in which machine learning algorithms will be used to classify survey respondents that represent the likelihood to use flying taxis. Ada-boost, KNN, Neural Networks, SVM, Decision Trees, Random Forest, Nave Bayes, and Gradient Boosting will all be used as machine learning techniques. The research project will compare the applied Machine-Learning classifiers in order to determine the best classifier model, which will represent the prediction model for the UAE public’s adoption of future mobility technologies. Our aim is to accurately predict the use of flying taxis in the UAE based on user data.