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No matter you are a student, a tourist, a business traveler, a bus driver or a hub operator. No matter if you are travelling by foot, car or bus, there is no way you cannot be affected by a traffic jam or mobility problems in a city, metropolitan area, port or airport hub nowadays…

According to the European Commission Impact Assessment “Roadmap to a Single European Transport Area” (2011) traffic congestion cost Europe about 1% of GDP every year, huge impact right?

Between 2012 and 2014 the Hamburg Port Authority conducted a survey of forwarding agents as part of smartPORT logistics initiative, they found that 70% truck waiting time was spent at hubs.

If we move to an individual’s space, the city of Vienna found a 90% mileage increase by private commuting cars when they performed a Mobility analysis – “Mobilitäts-Szenarien 2035”.

From a public policy perspective and according to The World Bank (2013) Study “Building Urban Resilience”, short-sighted infrastructure investments affect urban resilience for the next 20-30 years for spatial plans and up to 50 years for infrastructure design.

 

We don’t have only to anticipate, but to act!

 

I mentioned different types of objectives involved in a holistic approach. Today’s best practices consider an Economical, People, Environmental, Mobility, Governance and living “smart flavor”. Furthermore all of these single aspects should be in the perfect mix in order to achieve a proper balance between the right to mobility and the use of resources and its emissions.

Urban Analytics targets an innovation driven app framework. It aggregates existing, future, our very own and your or 3rd party elements.

It addresses the needs of the ecosystem and its public and private entities in a city. It consists of visualization tools as well as community enablement functions:

In our Innovation Center @ Nanjing, founded in 2012 and focused on Smart Traffic Innovations, we have created an “Intelligent Traffic Management Platform” as a perfect example and foundation of our solutions for Urban Traffic and Transportation Management. We have conceived basically 5 different scenarios so far in order to achieve Urban requirements:

Intelligent Traffic Management System provides instant insight from traffic big data and works as a foundation of smart traffic applications. It centralizes traffic data from various sensors, ensures data quality via data auto-correction and cleaning algorithms, and builds traffic data model with best practice to support up-level applications. In addition, it provides powerful tool-kits and flexible interface and to enable a easy deployment and value added innovations.

Traffic congestion management supports decision making to mitigate traffic jam smartly by leveraging value of big data. It evaluates accurately city traffic status by setting up a quantitative measurement system, it provides early discovery on traffic abnormal to reduce response time,  offers congestion analysis for smart decision making to reduce traffic jams and support public travel guidance service to benefit both citizen & enterprise.

Traffic planning excellence supports city government on city level traffic policy making(issue of new vehicle license plate, vehicle restriction in peak hour) and infrastructure planning(like public transportation service for new CBD area) by offering what-if analysis and analysis of city travel pattern, definition of   traffic analysis zone, prediction of traffic time between traffic zones, auto identifies the key routes and so on.

Public Transit management helps the government to improve the public transit operation efficiency and service level. It provides tool to support bus/metro line planning, matches taxi demand and supply, makes what-if analysis to support the ticket pricing adjustment or allowance to public transit operators and so on.

Traffic Emission Management aims to analysis the traffic impact to environment and help on emission related policy making.

Traffic Data Management ensures the traffic data quality and reduces the cost of hardware maintenance, it discovers data fault automatically, finds the root cause and generates hardware maintenance plan for traffic sensors.

I hope you’ll find this this brief interesting and hopefully you can let me know your comments and ideas about it,

Alejandro.

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