Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
The highD Dataset: A Drone Dataset of Naturalistic Vehicle Trajectories on German Highways for Validation of Highly Automated Driving Systems
2018861 citationsRobert Krajewski, Julian Bock et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Lutz Eckstein's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lutz Eckstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lutz Eckstein more than expected).
This network shows the impact of papers produced by Lutz Eckstein. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lutz Eckstein. The network helps show where Lutz Eckstein may publish in the future.
Co-authorship network of co-authors of Lutz Eckstein
This figure shows the co-authorship network connecting the top 25 collaborators of Lutz Eckstein.
A scholar is included among the top collaborators of Lutz Eckstein based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Lutz Eckstein. Lutz Eckstein is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bock, Julian, et al.. (2017). Database approach for the sign-off process of highly automated vehicles. RWTH Publications (RWTH Aachen).24 indexed citations
10.
Bardow, André, et al.. (2017). Latentwärmespeicher in PlugIn-Hybridfahrzeugen. RWTH Publications (RWTH Aachen).1 indexed citations
11.
Zlocki, Adrian, et al.. (2017). Absicherung hochautomatisierter Fahrfunktionen mithilfe einer Datenbank relevanter Szenarien. RWTH Publications (RWTH Aachen).3 indexed citations
12.
Flemisch, Frank, et al.. (2016). Wirksamkeitsanalyse von Fahrerassistenzsystmen in Bezug auf die Verkehrssicherheit. RWTH Publications (RWTH Aachen).2 indexed citations
13.
Eckstein, Lutz, et al.. (2014). How to deal with large data sets in naturalistic driving tests? An effective approach for detection of critical driving situations without video data. Transportation Research Board 93rd Annual MeetingTransportation Research Board.1 indexed citations
Eckstein, Lutz & Adrian Zlocki. (2013). Safety Potential of ADAS – Combined Methods for an Effective Evaluation. RWTH Publications (RWTH Aachen).16 indexed citations
16.
Zlocki, Adrian, et al.. (2013). Impact Assessment of Adaptive Cruise Control (ACC) and Forward Collision Warning (FCW) Within a Field Operational Test in Europe. Transportation Research Board 92nd Annual MeetingTransportation Research Board.3 indexed citations
Zlocki, Adrian, et al.. (2012). Detailed FOT for the Analysis of Effects between Nomadic Devices and ADAS - Evaluation of Critical Events. 19th ITS World CongressERTICO - ITS EuropeEuropean CommissionITS AmericaITS Asia-Pacific.1 indexed citations
19.
Zlocki, Adrian, et al.. (2011). Incident Detection Based on Vehicle CAN-Data Within the Large Scale Field Operational Test “euroFOT”. RWTH Publications (RWTH Aachen).25 indexed citations
20.
Hamacher, Michael, et al.. (2011). Assessment of Active and Passive Technical Measures for Pedestrian Protection at the Vehicle Front.4 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.