When 48 leading transport, logistics and information technology stakeholders in Europe came together under the TransformingTransport project armed with a budget of 18.7 million euros, an innovative high-tech set of transport technologies and solutions emerged. To achieve this, the project partners had exploited enormous amounts of data – i.e. Big Data – from numerous sources to discern patterns and propose innovative solutions that would ultimately streamline rail, road, air and sea transport for both passengers and goods. Falling under seven different areas of transport or “domains” the new transport processes and services demonstrated how they could improve customer experience and create new business models that are set to make their mark on areas such as transport, logistics, e-commerce and even tourism.

Highways will become smarter

Imagine software that will predict highway traffic in real time and propose immediate solutions to pre-empt traffic. Two TransformingTransport pilots under the heading of Smart Highways developed high-tech approaches to alleviate traffic and make highways safer. Some of the key innovations developed to make highways smarter entail predicting accident probability to help pre-empt mishaps and installing advanced sensors to detect issues, as well as accurately anticipating traffic peaks at toll stations and managing toll booth personnel. One particularly smart solution involves combining Big Data from traffic sensors, cameras, weather reports, accidents, social media and electronic road signs to highlight the bigger picture on the road in real time and support road authorities in managing traffic. Other key achievements include the ability to display traffic and accidentality metrics every 15 minutes and to present real-time predictive traffic and accidentality models for the next 15, 30, 45, 60 and 120 minutes.

Vehicles will be connected

If a group of cars can “talk” together and report to one central database, road authorities will be able to detect patterns that will save fuel, money and lives while making transport and deliveries much more efficient. TransformingTransport’s Connected Vehicles domain developed ways to help advance the lifecycle of cars, energy efficiency, environmental footprint and passenger safety. The new technology helps drivers and car fleet managers to promote more efficient driving and reduce CO2 emissions. This part of the project has also led to solutions for helping truck fleets run more smoothly while alleviating congestion in cities and improving logistics. Technologies such as floating car data (FCD), dashboard-display software to monitor truck fleet activities, satellite imagery to predict emissions and improved estimates of trajectory times all contribute to making vehicles smarter and upgrading road transport. In numerical terms, connecting vehicles is expected to reduce driving and truck fleet handling times by 17%.

Rail maintenance will be more proactive

Under the domain of Proactive Rail Infrastructures, TransportingTransport has found ways to stop rail equipment breakdown before it happens, bringing key benefits to rail operators and passengers. New software that identifies equipment failure or weak points on rail lines and software to detect overhead line anomalies are crucial in advancing these new maintenance solutions, along with sensor data and predictive models that monitor and model track degradation. In parallel, TransformingTransport developed new maintenance models that streamline rail transport. It exploited Big Data to accurately forecast maintenance operations for electro-mechanical assets in high speed railways. This also involved processing large amounts of data in real-time and providing analyses to rail operators through new human-machine interface dashboards. Integrating these new dashboards into rail operators’ business strategy will ultimately improve performance and reduce maintenance costs. Ultimately, maintenance interventions could be reduced by 10% and maintenance costs could be reduced by 34%.

Ports will offer smarter logistics

In its valiant quest to position ports as intelligent logistics hubs, TransformingTransport made significant progress by exploiting Big Data to benefit port operations. It accessed key performance indicators in real time and developed predictive models to optimise shipyard operation. This involved analysing port terminal data, revealing operational trends and pre-empting maintenance issues, such as shifting from preventive maintenance to predictive maintenance in cranes. User-friendly data visualisation and analytics were developed to support port operators, from achieving real-time visualisation of container movements to perfecting real-time equipment monitoring and failure prediction. A key achievement in this respect was the development of predictive, deep learning analytics for proactive terminal process management. In some cases, TransformingTransport’s interventions demonstrated savings in operational costs of around 10%, as well as improved terminal efficiency by 5%.

Aeroplanes will turnaround more quickly

Under the Smart Airport Turnaround domain, TransformingTransport made excellent progress in demonstrating how to streamline the passenger flow in airports. By exploiting Big Data, it managed to reduce flight delays, avoid passenger bottlenecks and enhance passenger experience, thanks to better decision making and sophisticated passenger flow models. On the one hand, TransformingTransport used passenger demand to optimise airport resources and reduce costs, while on the other hand it showed how airports can increase non-aviation revenues by analysing passenger purchases and proposing new business opportunities. Importantly, the project demonstrations improved aircraft turnaround time significantly, thanks to the use of Big Data to better estimate landing times, taxi times and boarding times. In some cases, these predictions improved by as much as 70% compared to traditional approaches that did not leverage Big Data. Lastly, this approach is expected to optimise airport resources and reduce operational costs by up to 20%, in addition to increasing airport gate capacity by up to 10%.

Road traffic in cities will decrease

Under the heading of Integrated Urban Mobility, the TransformingTransport project used Big Data to upgrade situational awareness of city traffic. This involved improving the identification of traffic jams using traffic cameras, disseminating key traffic information to travellers through social media, and developing a parking reservation system for freight delivery in the city. With respect to better logistics in urban areas, the project built superior traffic simulation micro-models from real data to help city authorities improve the decision-making process. It developed a new planning tool for logistics companies and found ways to better understand behaviour of logistics vehicles in city centres. New models for loading and unloading trucks in the city also emerged from this endeavour. Overall, these Big Data traffic solutions are expected to increase traffic observations per day by 70% in order to radically improve traffic status information, in addition to reducing delivery vehicle use by 30%.

E-commerce logistics will improve

TransformingTransport’s development of “dynamic supply networks” in the logistics sector has demonstrated how Big Data can lead to new, more advanced e-commerce logistics processes that benefit logistics companies, online retailers and consumers. By engaging e-commerce and logistics industry experts, identifying delivery patterns and predicting future delivery demand, TransformingTransport was able to identify last-mile distribution improvements, gain better consumer insights on delivery and propose alternative shipping methods in cities. This entailed better customer segmentation models that focused on location aspects, as well as better hub replenishment in online shopping through location optimisation and clustering. Employing these supply networks has the potential to decrease the number of vehicles used per day by 38%.

 

 

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