Artificial intelligence (AI) decides the future of business because it resolves plenty of problems that curb growth. It answers the unprecedented question in advance with its actionable insights driven from data, especially the historical ones. Businesses being integrated with technology produce a huge amount of data every nanosecond that can be analyzed computationally to understand the trends and patterns associated with human interactions and behavior.
World leaders like Japan have already started implementing AI into the transportation systems in their nations to predict upcoming ride requests, vehicle health, and driving habit. For over a span of 10 years, there is an overwhelming stream of information that have been collected during the deployment of on-demand taxi services. By analyzing different pattern and trends, future sales/demand can be predicted. The repetition of such patterns offers a potentially accurate demand forecasting.
“Can AI forecast forthcoming demand for on-demand transportation with the data stored from previous trips?”
Obviously, yes! The increasing popularity of the ride-hailing business paves way for the researchers to get massive historical data related to taxi rides that can be utilized to predict the demand. The upcoming sales/demand can be predicted with high-level of accuracy just by activating the spatiotemporal data that are the record of cab bookings, cancellations, preferred payment options, customer behavior, trends, patterns, and other external data such as weather, traffic, days, events, holidays, and many more.
Besides the previously mentioned data, the companies are mining relevant data from the mobile phone accessing users’ calendar, contact list, and GPS location. With this information, the system can provide heatmaps of local demand or predict surges in ride bookings. Accessing personal data may raise privacy concerns; however, people are voluntarily consenting to share such information as these data will help ultimately service providers in reducing waiting time, lessening congestion, and increasing the probability of getting more rides.
AI was expected to think as does humans; however, in reality, it is doing something more than that. Humans can predict only on experience and intuition that has the equal probability of winning or losing, but the AI-based demand prediction comes with high level of accuracy and limited variance as basically the forecast is made based on real-time sales and external data. In this case, AI is outperforming human intelligence. While wondering the advanced solutions of AI and its demand prediction, hoping to get more to take the taxi industry to the level that cannot even be imagined.