TRANSFORMING TRANSPORT TRUCKS

PILOTS : SUSTAINABLE CONNECTED TRUCKS FROM AMSTERDAM TO FRANKFURT

BIG DATA VALUE IN MOBILITY AND LOGISTICS

LOCATION    AMSTERDAM

COUNTRY    NETHERLANDS

CONTACT NAME    MICHAEL SCHYGULLA, JASMIN GRAF

WEB    https://transformingtransport.eu/transport-domains/sustainable-connected-trucks-pilot

EMAIL    ,

PILOT PRODUCT DESCRIPTION

The main objective for this pilot is the enhancement of planning and optimization systems for planners, fleet managers or technical systems. To achieve this goal, it is necessary to assess the transportation process and all aspects of it such as the traffic flow for truck journeys and to detect and analyse logistic hotspots such as terminals, toll stations and ferry stations. The main challenges that have to be faced here are high customer expectations, unexpected situations in the day-to-day business and a lack of information for truck-related tasks.

Large amounts of Big Data processing, specifically related to truck fleets all over Europe, are necessary for this task. Additionally, the use of satellite images as an extra data source on different planning stages in the context of applications for truck fleet managers is incorporated in this pilot to detect not only the current state of a location but also its changes over time.

As part of the analyses, the pilot concentrates on the use case of a defined truck corridor between Amsterdam and Frankfurt with alternative routes and points of interests along the corridor. This truck corridor is investigated in terms of routing and travel times as well as different analyses on specific points of interest. These points include traffic situations along the corridor and operative times at the airport. On exemplary analysis of such a point is displayed in the figure below. Here, different activities of truck drivers are mapped to the area around Frankfurt Airport to investigate where and when different activities such as handling or resting take place.

Mapped to this use case, a dashboard is developed for analyses on this geographical area. With the help of this dashboard and the underlying data analytics, the planning process of logistics service providers can be better understood and improved.

Covering the objective of getting insights into truck-related information based on satellite images, the following figure gives an impression how to identify the speed of vehicles with the help of a single picture. In this case, different spectral ranges of the light can be identified and based on this visual effect, a speed estimation can be given.

Further fields of application within the pilot and also beyond are the identification of vehicles, landslide forecasts or air quality mapping.

OBJETIVE OF THE PILOT

The objectives and expected results of the pilot are:

  • Usage of the Big Data approach on traffic and movement data specifically related to truck fleets and investigating whether and how these results can be implemented into traffic models and used in routing / planning applications for logistics service providers to enhance the planning processes.
  • Development of a reliable routing approach to estimate on-time arrival times more accurately.
  • Provision of truck-specific traffic information to gain information for different geographical areas throughout Europe.
  • Event-related information on specific points of interest to feed planning activities with further information to enable more precise planning.
  • Analyses on infrastructure, events, lane-specific traffic conditions for trucks based on satellite images to track topographic information or changes in emissions over a longer period of time.

EXPECTED RESULTS

The objectives and expected results of the pilot are:

  • Usage of the Big Data approach on traffic and movement data specifically related to truck fleets and investigating whether and how these results can be implemented into traffic models and used in routing / planning applications for logistics service providers to enhance the planning processes.
  • Development of a reliable routing approach to estimate on-time arrival times more accurately.
  • Provision of truck-specific traffic information to gain information for different geographical areas throughout Europe.
  • Event-related information on specific points of interest to feed planning activities with further information to enable more precise planning.
  • Analyses on infrastructure, events, lane-specific traffic conditions for trucks based on satellite images to track topographic information or changes in emissions over a longer period of time.

KPIS AND METRICS

The main KPIs of the pilot are:

  • Reduction of the average duration of stay at (un)loading points along the chosen truck corridor by a better management of idle times [Minutes]
  • Increase of the accuracy of the estimated time of arrival at handling locations [%]
  • Reduction of the total trip time including driving and handling activities [Minutes]
  • Increase of the average data volume collected daily [GB]

PILOT PARTNERS

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