Data-driven decisions for intelligent management of public transportation

Project Information

D3IMPACT

Grant agreement ID: 696935

DOI

10.3030/696935

Project closed

EC signature date 8 September 2015

Start date 1 October 2015

End date 31 March 2016

Funded under

• SOCIETAL CHALLENGES - Smart, Green And Integrated Transport

Total cost

€ 71 429,00

EU contribution

€ 50 000,00

Coordinated by

URBANRETAIL, S.L
Spain

Periodic Reporting for period 1 - D3IMPACT (Data-driven decisions for intelligent management of public transportation)

Reporting period: 2015-10-01 to 2016-03-31

Summary of the context and overall objectives of the project

The planning and management of public transport systems is essential for urban decision makers and public and private transport operators. The key for the planning of public transport systems is the knowledge of user demand.
Cities account for around 80% of the world’s economic output, and drive an even higher share of global growth . Efficient transport can attract economic activity to cities, and boost productivity by reducing time lost to travel and improving connectivity. Quality public transport requires good management and this requires reliable, accurate and updated travel demand information.
The aim of the d3IMPACT project is to assess the technological and economic feasibility of providing public transport operators and urban decision makers with affordable, accurate, permanent and real-time travel demand information by means of our State-of-Art technologies that performs passenger counting using 3D image depth sensors, Wi-Fi signal tracking, cloud computing, big data and powerful analytics tools.
The final analysis resulted in the viability of the project and in consecuense we elaborated a detailed business plan. The final analysis resulted in the viability of the project and in consecuense we elaborated a detailed business plan.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

"We performed a complete market study, using quantitative and qualitative data. We used data from a market report and from an questionnaire to potential customers in order to measure the market size and analyze the customer needs, With this information, we elaborated a PESTLE and SWOT analysis and developed the sales policy, pricing strategies and the overall marketing plan.
A technological analysis has also been performed by comparing the different technologies used by automatic people counters as well as the existing solutions from competitors. We centered our analysis in the accuracy of the solution as this is the key feature that differentiates us from other competitors. The analysis resulted in the decision to use ToF with illumination sensors and the need to certify the devices that will be installed on-board of vehicles.
A legal analysis was also performed, and with the help of a specialized firm in IPR, we assessed the novelty, freedom-to-operate and IPR strategy, with positive results.
The financial analysis, as a result of the market research, studies the costs structure, performs a sensitive analysis with three scenarios (projected, pessimistic and optimistic) establishing realistic sales projections for the following 5 years and the corresponding profit&loss analysis for each scenario. We also determined the funding needs and the strategy, resulting in applying for the phase 2 of the SME instrument, financing part of the action with own funds, and after the project, with the solution ready for market uptake, with new equity.
The feasibility study helped us in redefining certain parts of the solution that are detailed in the ""product"" section of the feasibility study.
We decided to implement an ambitious demonstration action, through a field operational test in the city of Barcelona, involving public transport authorities, and private and public operators, that will demonstrate the capabilities of our solution and allow us to gain knowledge and market recognition.
We have letters of support from public transport authorities and operators endorsing the project that are included at the end of the feasibility study.
In consequence, we developed a detailed business plan."

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

In order to detect the closest prior art to the innovation project of interest, we have conducted a search of English‐language global patent and non‐patent literature with respect to d3IMPACT, relating to a new system/method that generates accurate and permanent travel demand data and decision-making tools that will help to plan and manage public transportation systems.
Specifically, the search has been directed to the following feature:
Specifically, the search has been directed to a people counting and crowd analysis system/method for a novel integrated solution, with the purpose of:

1. Checking if the market already has similar products
2. Ensuring the freedom to operate and the market opportunity
3. Strengthening the already existing intellectual property and
4. Watching the potential competitors

The novelty is based in the accuracy of the solution, the public transport line and network modelling by being able to generate Origin-Destination matrices, the Open Data philosophy and data from different sources is aggregated to build an accurate model of passenger demand and its variation due to external factors such as meteorology or city events. Wi-Fi tracking data will allow to track passenger across different transport modalities. Smart card integration will give us some of the network trips. Ticketing will be used for fare evasion detection.
The legal analysis resulted in a positive preliminary Freedom-to-Operate and the definition of a IPR strategy to implement.

The expected potential impact of d3IMPACT will be:
For the company: ensuring the company growth and internationalisation achieving revenues of over € 27.000.000 and a headcount of 110 employees in the 5th year.
For public transport authorities: OD Matrix Knowledge, Network Optimization, and fare evasion avoidance, resulting in a public transport network that can be managed based on data driven decisions.
For public transport passengers: increased Safety, access to Open Data, and demand-oriented service, resulting in an increased usage of public transportation.
For public transport operators: Knowledge of anticipate variations, the capability to adapt offer to demand, and the Improvement of passenger satisfaction, resulting in a better managed service.

Abstract and features of d3IMPACT