What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Computer network
Kai Nagel spends much of his time researching Simulation, Traffic simulation, Distributed computing, Cellular automaton and Transims.
His Simulation research incorporates themes from Microsimulation, Pedestrian, Traffic wave, Flow network and Queueing theory.
His biological study deals with issues like Representation, which deal with fields such as Focus.
His research in Cellular automaton intersects with topics in Mathematical model, Mathematical optimization, Applied mathematics and Traffic flow.
His Traffic flow research is multidisciplinary, incorporating perspectives in Flow, Iterated function, Stochastic modelling and Probabilistic logic.
His research investigates the link between Microscopic traffic flow model and topics such as Newell's car-following model that cross with problems in Nagel–Schreckenberg model.
His most cited work include:
- A cellular automaton model for freeway traffic (2897 citations)
- Two-lane traffic rules for cellular automata: A systematic approach (386 citations)
- Two lane traffic simulations using cellular automata (358 citations)
What are the main themes of his work throughout his whole career to date?
Kai Nagel focuses on Simulation, Transport engineering, Operations research, Traffic simulation and Microsimulation.
His study in Simulation is interdisciplinary in nature, drawing from both Traffic flow, Mathematical optimization, Relaxation, Adaptation and Queue.
His biological study spans a wide range of topics, including Traffic generation model, Statistical physics and Cellular automaton.
His research integrates issues of Routing and Process in his study of Operations research.
His studies in Traffic simulation integrate themes in fields like Transportation planning and Distributed computing.
His Microsimulation research integrates issues from Scale and Fidelity.
He most often published in these fields:
- Simulation (25.51%)
- Transport engineering (18.48%)
- Operations research (19.35%)
What were the highlights of his more recent work (between 2015-2021)?
- Transport engineering (18.48%)
- Simulation (25.51%)
- Operations research (19.35%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Transport engineering, Simulation, Operations research, Mathematical optimization and Econometrics.
His work on Public transport and Parking guidance and information as part of general Transport engineering research is frequently linked to Parcel delivery and Simulation based, thereby connecting diverse disciplines of science.
His Simulation research includes themes of Calibration, Road traffic, Link and Queue.
The Operations research study combines topics in areas such as Routing, Use case and Congestion pricing.
His Mathematical optimization research is multidisciplinary, relying on both Core and Economic cost.
His study explores the link between Econometrics and topics such as Marginal cost that cross with problems in Payment and Computation.
Between 2015 and 2021, his most popular works were:
- The Multi-Agent Transport Simulation MATSim (296 citations)
- An Assignment-Based Approach to Efficient Real-Time City-Scale Taxi Dispatching (63 citations)
- Towards High-Resolution First-Best Air Pollution Tolls (37 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Computer network
Kai Nagel mainly focuses on Operations research, Transport engineering, Simulation, Public transport and Travel behavior.
His Operations research study incorporates themes from Span and Constraint.
The concepts of his Transport engineering study are interwoven with issues in Test, Order, Revenue and Data set.
His Simulation research incorporates elements of Road traffic, Separation, Mathematical optimization, Residential area and Stage.
His Travel behavior study combines topics in areas such as Transportation planning, Paratransit, Complex adaptive system, Use case and Implementation.
The concepts of his Vehicle routing problem study are interwoven with issues in Service, Traffic flow, Cost efficiency, Congestion pricing and Dynamic pricing.
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