Picture of the month

Picture of the Month: Urban Street Networks for people

What role does a street play in the overall network? And how do the individual segments of the urban street network relate to each other? This is what the SpACE Lab at ISU – Institute for Sustainable Urbanism at Technische Universität Braunschweig is working on. The “Spatial Analytics and Crossdisciplinarity Experimentation Lab” develops data-driven methods and solutions for human centric sustainable mobility. In the work shown here, the interdisciplinary team focuses on developing a network-based user-centric categorisation of street segments. This can be used, for example, to make statements about the quality of the network for different street users. Our picture of the month May visualises this categorisation to get a better understanding of the Urban Street Network.

An unusual view of Braunschweig: The SpACE Lab visualised the user-centric categorisation of street segments. Picture credits: SpACE Lab/TU Braunschweig

An unusual view of Braunschweig: The SpACE Lab visualised the user-centric categorisation of street segments. Picture credits: SpACE Lab/TU Braunschweig

An Urban Street Network (USN) stems from connections created between settlement units depicting social, economic, and natural factors. By employing a machine learning approach to cluster street segments based on their centralities, which indicate their intermediary, accessibility, connectivity and the importance of the neighboring segment.

The users’ perspective

The visualisation gives a small insight into the current research of the SpACE Lab at ISU on human centric mobility. The perspective of the users determines the categorisation and clustering of street segments with similar characteristics rather than functional or administrative attributes.

The researchers use various libraries of the programming language Python, machine learning techniques and multidimensional spatial data analysis to explore multiple features, such as accessibility and connectivity, that characterise the street segments in Braunschweig.

Categorisation of street segments

The map visualises the identified clusters as well as the feature “connectivity”: Each end of a segment (node) is represented by a dot and normally represents a crossing point. The size of the dots refers to the number of other segments to which each segment end is connected. For example, a node connecting four segments (an intersection of two roads) would be larger than a node of a cul-de-sac. Larger dots therefore mean better connectivity. The colour gradients, on the other hand, show the spatial distribution of the identified cluster segments that belong to the same Network Street Category (NSC) developed by the interdisciplinary team.

This analysis can be used to identify strengths and weaknesses of specific segments in the street network. It is then possible to propose appropriate changes to the transport network, to monitor and analyse the traffic flow of the different modes of transport, especially pedestrians and cyclists, and to assess the resilience and reliability of the network to disruptions or congestion, such as traffic jams.

Better transport network for pedestrians and cyclists

For instance: In a residential street, the noise level should normally be lower due to the speed limit. However, if the road is busy and well connected due to its importance in the urban street network, a noise detector can be placed in the identified road segments to check if the noise level is higher than what is expected in residential streets. If a section with high topological importance – meaning that it mathematically represents the best connection from A to B, for example, or is linked to numerous other segments – does not yet have a bike lane, it could be a potential candidate for the construction of a bike lane. From the perspective of encouraging the more sustainable and active transportation modes, such as walking or cycling, increasing the functionality of a street segment may also contribute to a higher connectivity of the network for pedestrians or cyclists.

“For investment decisions on the location of new infrastructures or businesses, collecting data is often resource-consuming or even impossible,” agree Dr Hsiao Hui Chen, Olaf Mumm and Prof Dr Vanessa Carlow. “Analysis using the proposed method offers cost- and time-efficient recommendation and direction as the starting point in a decision-making process before further evaluation in the next stage.”

 


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You photograph yourself and would like to submit a picture? We are looking forward to your suggestions! Your picture should meet the following conditions:

  • Image size: min. 2030px wide and 480px high
  • Copyrights: You own the copyrights to the image and are willing to transfer the unrestricted rights of use to us free of charge.
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  • Description: Tell us in three sentences what can be seen on your picture and where it was taken.

Does everything fit? Then send us your photo with the subject “Picture of the month” to presse@tu-braunschweig.de. We reserve the right to decide which photos to publish.


Pictures of previous months

Picture of the month April 2022

Close-up of a piece of fabric measuring about four by two centimeters, located at various points on the inside of a so-called ECG T-shirt. Photo: Markus Hörster/TU Braunschweig

Our picture of the month April 2022 does not show a landscape on a distant planet, but a special fabric. The piece of fabric, which measures about four by two centimetres, can be found in various places on the inside of a so-called ECG T-shirt. It is used to measure an electrocardiogram (ECG) without the patients noticing anything. The Peter L. Reichertz Institute for Medical Informatics (PLRI) at Technische Universität Braunschweig and the Medizinische Hochschule Hannover is using this to research the future of health monitoring. Read more

Picture of the month March 2022

A moving robot with radar unit creates ground scans down to a depth of 40 centimetres. Picture credits: IMN/TU Braunschweig

The picture shows a scan of a ground-penetrating radar. It shows unchanging objects in the ground. If the data is combined with the position from laser measurements, a map developed from this information can be used for the navigation of mobile robots. A laser or cameras would then no longer be necessary. The Institute for Mobile Machines and Commercial Vehicles is conducting research on this in the “LoBaBo” project. Read more

Picture of the month February 2022

Picture credits: Michael Kraft/TU Braunschweig

Here they are, the first early bloomers in the Botanical Garden poking their little heads out. The native winter aconite is one of the quickest. With its bright yellow flowers, it already has its big moment in February. Under the still leafless trees, the small tuberous flowers form dense flower carpets and set bright colour accents. Reason enough to take a closer look at the plants in our picture of the month. Read more

Picture of the month January 2022

A view into the interior of the gas chromatograph at the Battery LabFactory Braunschweig (BLB). Picture credits:
 Dominik Emmel, Daniel Schröder/ TU Braunschweig

For the researchers, the headspace GC/MS system shown in the Picture of the Month is an eagerly awaited addition for battery analysis. It was purchased for BLB diagnostic line. It will now make it possible to better understand battery aging and develop longer-lasting batteries. It is a system for the analysis of liquid electrolytes or soluble surface deposits in the components of a battery. Read more

You can find more pictures of the month in our magazine.