Smartaxi - Innovative customer forecasting system with 32% savings in Taxi operational costs
Overview
Background & policy context:
The EU urban transport system is not sustainable, by 2050, meaning that the urban mobility systems will have consumed approximately 17.3% of the Earth’s total bio capacity.
URBAN TRANSPORT NEED: We need to optimise the efficiency and effectiveness of urban traffic management, but without sacrificing our limit our freedom of movement.
PROBLEM SOURCE: In Europe, exist more than one million taxis which represents 10-20% of urban traffic in major cities. In average, taxis drive more than 80,000 kilometres per year mostly in inner-city areas. Despite its significance, taxi transport it’s a highly inefficient system, in fact 50% of time a taxi its empty looking for customers or a booking service demand.
Taxi industry urgently needs to implement STM systems to transform it into an efficient and sustainable transport according to current smart cities.
Objectives:
OUR SOLUTION SMARTAXI: Smartaxi innovative solution is an intelligent software to make accurate and reliable prediction of time-localization customer demand. Our aim is to provide a solution to urban city congestion through the optimization of taxi management. For the first time, we will be able to anticipate customer demand (5 min-24h forecasting) with 95 % of accuracy. Smartaxi provide reliable forecast of customer demand, which suppose 32% savings in taxi operational costs and 3,5 M Tons of CO2 in Europe. The platform will disrupt the urban taxi market by introducing an innovative forecasting customer demand system 100% adaptable to any urban context.
Methodology:
Technical feasibility study: to finalized the technical validation of the system by: (1) improving the statistic models for future improvements in the predictive system, improvement on scalability and (2) user design making a friendlier intuitive application. To develop a business plan for our international expansion.
To carry out financial expectation such as best pricing and cost optimization, expected selling quantification from 2019 to 2022, risk assessment, bottlenecks and so forth
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