The teeming and colonized cities in the country provide a budding opportunity for bike taxi service as an alternative mode of transportation. With the headway in the mobility sector, there has been an advent of diverse latest moveability services such as application-based taxis, shared mobility, micro-mobility among others.
These services offer real-time and demand-responsive trips. Inturn these mobility services have loomed in the view of inadequate transport in order to meet both first and last-mile mobility demands. The bike taxi services are bettering the public transport ridership by providing smooth maneuver through traffic and ameliorating the mobility in edge areas.
They are becoming an upgraded tech-based version of the conventional intermediate transport mode which offers not only worthwhile and time-saving service, but also takes into consideration other parameters of comfort, reliability, safety, and convenience.
With advancements in information and communication technology, traditional services have been enhanced to provide a wide variety of real-time end-to-end commutes to humans all over the country. In recent years, the evolution of app-based ride-hailing services as ridesharing, ride-sourcing has visibly transformed the urban transportation landscape all over the world.
In urban cities getting a taxi that is safe and reliable is now nor more challenging as consumers can reach their desired destinations even in rush hours without surge pricing. Bike Taxi can cover distances in fundamentally lower time contrasted with vehicles in blocked metropolitan urban communities wherein the cost reserves are really self-evident which additionally diminishes the fuel utilization by establishing minimum effect on the environment.
To facilitate the best end-to-end experience possible for users Mopedo is one committed bike taxi service making communication with the consumers easier and more productive manner. The taxi service is leveraged with conversational AI integration by empowering to resolve user issues as accurately and effectively as quickly as possible within no time.
Further, we used this platform to lessen the potential for distracted driving by allowing pilot-partners to flawlessly communicate with riders by hand pick free and one-click chat. In the Mopedo bike taxi application, riders would make their profile, and afterward, they would be confirmed prior to allowing them to ride imparting to different travelers. So, we made a framework in the application to allow female riders to acknowledge the lone female traveler demand on the most elevated need.
Mopedo is one such cross-platform application that is being built possible due to AI in order to meet the skillsets of two or more domains for creating an end product. AI is helping bring all these specialized skills together in an all-in-one set up to benefit the end-user to have a seamless trip throughout the ride.
The preeminent role of artificial intelligence in the bike taxi service business helps to make taxi ride experiences superior. Therefore, based on historical trends taking a business decision as well as predictive analysis helps to streamline on-demand taxi services by determining the price of the ride and minimizing the waiting time.
A taxi service system in urban areas takes the taxi driver’s knowledge of the transportation network into consideration which is built from their day-to-day experience. Consumers can seek the pilot’s behavior on the basis of their expected travel time and the waiting time. This model considers the stochastic and dynamic transportation network at various levels of network knowledge on the part of the pilots.
The approach provides flexibility in modeling the nature of taxi operation as well as understanding the capability of the taxi pilot’s involvement. The eternity of the haulage display is going to uplift the standard of taxi services with Artificial Intelligence.