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Resultaten van de TransportLAB Hackathon bekend

June 22, 2016

In een blog van 18 mei 2016 riep Paul Swaak, oprichter en eigenaar van TransportLAB jullie op om mee te doen aan de TransportLAB Hackathon. Het volledige bericht lees je hier.

Er zijn zeven ideeën uit voort gekomen, hieronder lees je welke.

 

Delivery time predictability tool

DELIVERY TIME PREDICTIBILITY TOOL Background Imagine you are a Dutch importer of roses from Kenya. Most likely you would want to know when the roses arrive at your warehouses, amongst others to be sure not to miss important moments like Valentine’s Day. In fact, all customers of freight forwarders want to know when their imports arrive at their gates and when land-side travel times are shortest.

 

Time prediction model for the full logistics chain

Using the data provided in combination with open AIS data on ship port calls, we can trace the whole logistics chain from the ships origin (previous port call) to á containers loading onto a hinterland mode. The chain includes many events that may affect the total time need, most of which have a high uncertainty of duration.

 

Opening up a marketplace for Multi Modality Optimization

So the port of Rotterdam is has many vessels entering and leaving the port each day. Besides the seagoing vessels an even bigger part of these vessels are related to inland (river going) barges. The data clearly shows the limited availability of the terminals that transfer cargo from ship to ship. The idea is: Why not create a Single modality optimization...

 

Predicting traffic jams based on weather conditions

What if we could predict the probability of a traffic jam happening at any part of the road network ahead of time? Can we increase the prediction accuracy by taking the weather conditions into account? As a first step, we investigated the influence of weather conditions on the probability of a traffic jam occurring. We obtained historical weather data from the KNMI weather stations...

 

Providing information on expected congestion considering weather forecasts

We work on the development of a tool to provide information on expected congestion/ traffic flows considering weather forecasts. Until now we have been focusing on the A20 highway from Kethelplein to Gouda which, according to the challenge description, is one of the busiest roads in the Netherlands, particularly the part between Kleinpolderplein and Terbrechtseplein.

 

Predict ship calls port of Rotterdam 

Our idea is to predict the number of incoming ships at the port of Rotterdam. A split is made between seagoing vessels and rivergoing vessels. These two categories sometimes compete for the same terminal handling capacity, depending on the specific dock. This leads to serious delays, which results in additional costs. To tackle this problem, we want to improve the scheduling. 

 
A13: A case study on traffic analysis, junction profiling and congestion prediction.
Based on the list of troublesome intersections shown in the challenge description, we decided to pick one of them and use it as a case study for developing tools and insights that can be extended to other roads and intersections. We decided to work on analyzing the A13 highway, with particular focus on its intersection with the N470 road, in the direction from The Hague to Rotterdam. 
 
Voor meer informatie, neem contact op met
 
 

 

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