ArticleData in brief2026
Heavy commercial vehicles' disposition: Anonymized dataset of German truck freight transport order trips (DT-DISPO).
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This article presents an anonymized dataset of real-world transport order trip data spanning a total operational period of 16 months. The original data has been provided by two German freight forwarding companies as an export from their respective Transport Management System (TMS). All personal and company-identifiable information has been anonymized to ensure privacy while maintaining relational integrity for research purposes. The dataset comprises 31,352 disposition records from two fleet operators: one with a fleet of 37 heavy-duty vehicles spanning a continuous 5-month period in 2024, and the second with 83 heavy-duty vehicles spanning a continuous 10-month period in 2024. Both fleets comprise only internal-combustion engine vehicles. The dataset provides granular data regarding start and end locations (coordinates), schedule time windows, driving distances, allocated vehicles, and allocated drivers. This dataset can be used by researchers in logistics and transportation engineering to develop and benchmark vehicle routing and disposition/dispatching algorithms, analyse freight transport behaviour, develop demand prediction models, or novel electric vehicle disposition modelling.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.