Artificial Intelligence Helps in Deep Transportation Research

Have you tried Google Maps ever?

Travelling has never been as convenient as it is today. You don’t need a guide. Neither do you require a passerby who you ask the way to your destination. Google has laden us with loads of comfort through its Maps. But, it’s not in a monopoly. Simply put, the search engine giant is not the only busy bee that is offering convenience. The ride-hailing companies, like Uber and Lyft, are also following its footprints.

Just drill the data on the artificial intelligence (AI) powered Google Maps or Uber app. You don’t have to chew bullets to know the real-time traffic, its congestion and the directions.  The new technologies are bringing about truckloads of data for an in depth research. A decade ago, the data mining experts tracked data via telematics that the Satellite pictures offered. Also, the electronic logs in the cab meter delivered the whole data.   

Thanks to extremely valuable artificial intelligence! It’s making the difference together with IoT, data mining and machine learning. They’re manipulating the typical way of decision making, seeing things, and planning.

Here is a run-down of facts that the AI uses to call renaissance in transportation:   

1. Decision Making:

You could not foresee the traffic on the road before. But today, it can easily happen. Just navigate through the real-time data on the Google Maps. A click on the hamburger menu in the top-left can take you to an overview of the traffic. But first, you have to put the beginning and the ending location. The data that it shows comprise the ‘live traffic’ and ‘typical traffic’. The former traffic showcases the real-time traffic congestion while the latter glimpses the usual traffic at a particular time. Thereby, you could easily choose the hassle free way to move ahead.

Practically seen, the AI-driven data can automate your analysis so that you can make appropriate decisions. Moreover, it takes just a second long glance to reach the decision.

2. Predictive Analysis:

It’s not a walkover in the dog-eat-dog world of diverse corporates. The high competition always boosts entrepreneurs to cater what their audience would find just ‘a WOW deal’. It could be something that doesn’t require a deep pocket.

So! How should they pull out some mind-blowing deals?

Predictive analysis has its answer. Churn a little bit of data; estimate some targeting strategies and you’re done. The AI platform closely ties with sales and marketing data of the tour and travel based organization.

Uber, for example, has launched an AI-powered Kepler.gl analysis tool in June 2018. AirBnB, Mapbox and Limebike are a few of its renowned users.  They can input geospatial data through CSV and GeoJSON files in bulk. Within a sec, millions of points representing thousands of trips get rendered. This is how they aggregate data by averages. Even, they can add desirable filters to translate that data into eye-catching contextual insights.

3. Strategic Optimization:

Transporters, like Ola, Meru and Lyft, could never be that more successful if they fail to optimize on ‘where when and how’.  They don’t skip gathering and combing data to pull out best decisions pertaining to availability, pick and drop facility, drivers at the wheel in the nearby location, and pre-ride booking.

These all variables are not fed into the AI supported apps and software. The rest of the work, ranges from the call data crunching and defining range of the vehicle, is done automatically. If you look into the Google Maps, it aligns top ride services in the coverage area that you have input.

4. Deriving Call-To-Action (CTA):

The market research of transporters and customers opens the insight. This insight makes the travel companies richer than ever. A little bit of a push to their company’s promotion via online local ads sails it into the people talk. The promotional ads infuse call to action that gets a push from the gathered data.   Consequently, inquiries burst in overwhelmingly.