Demo Data from VLDB 2026 / reviewers in the wild / expert
Sebastian van de Hoef
dblp:158/4973 · also Sebastian H. van de Hoef
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2020
0000-0003-3248-0187ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 3 · 2 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Smart cities and intelligent transportation · 100% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Embedded and real-time systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Smart cities and intelligent transportation › logistics
fleet management |
0.2 | 1 | 2016 | Cyber-Physical Control of Road Freight Transport · Proc. IEEE 2016 |
Smart cities and intelligent transportation › connected autonomous vehicles
vehicle platooning |
0.2 | 1 | 2016 | Cyber-Physical Control of Road Freight Transport · Proc. IEEE 2016 |
Embedded and real-time systems
cyber-physical systems |
0.2 | 1 | 2016 | Cyber-Physical Control of Road Freight Transport · Proc. IEEE 2016 |
Methods — techniques the papers use, named apart from their topics
vehicle-to-vehicle communication · 0.5simulation · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | A Predictive Framework for Dynamic Heavy-Duty Vehicle Platoon CoordinationabstractThis article describes a system to facilitate dynamic en route formation of heavy-duty vehicle platoons with the goal of reducing fuel consumption. Safe vehicle platooning is a maturing technology that leverages modern sensor, control, and communication technology to automatically regulate the inter-vehicle distances. Truck platooning has been shown to reduce fuel consumption through slipstreaming by up to 10%; under realistic highway-driving conditions. To further benefit from this technology, a platoon coordinator is proposed, which interfaces with fleet management systems and suggests how platoons can be formed in a fuel-efficient manner over a large region. The coordinator frequently updates the plans to react to newly available information. This way, it requires a minimum of customization with respect to the logistic operations. We discuss the system architecture in detail and introduce important underlying methodological foundations. Plans are derived in computationally tractable stages optimizing fuel savings from platooning. The effectiveness of this approach is verified in a simulation study. It shows that the coordinated platooning system can improve over spontaneously occurring platooning even under the presence of disturbances. A real demonstrator has also been developed. We present data from an experiment in which three vehicles were coordinated to form a platoon on public highways under normal traffic conditions. It demonstrates the feasibility of coordinated en route platoon formation with current communication and on-board technology. Simulations and experiments support that the proposed system is technically feasible and a potential solution to the problem of using vehicle platooning in an operational context. Sebastian van de Hoef, Jonas Mårtensson 0001, Dimos V. Dimarogonas, Karl Henrik Johansson |
ACM Trans. Cyber Phys. Syst. | 1 |
| 2018 | Fuel-Efficient En Route Formation of Truck PlatoonsabstractThe problem of how to coordinate a large fleet of trucks with a given itinerary to enable fuel-efficient platooning is considered. Platooning is a promising technology that enables trucks to save significant amounts of fuel by driving close together and thus reducing air drag. A setting is considered in which each truck in a fleet is provided with a start location, a destination, a departure time, and an arrival deadline from a higher planning level. Fuel-efficient plans should be computed. The plans consist of routes and speed profiles that allow trucks to arrive by their arrival deadlines. Hereby, trucks can meet on common parts of their routes and form platoons, resulting in decreased fuel consumption. We formulate a combinatorial optimization problem that combines plans involving only two vehicles. We show that this problem is difficult to solve for large problem instances. Hence, a heuristic algorithm is proposed. The resulting plans are further optimized using convex optimization techniques. The method is evaluated with Monte Carlo simulations in a realistic setting. We demonstrate that the proposed algorithm can compute plans for thousands of trucks and that significant fuel savings can be achieved. Sebastian van de Hoef, Karl Henrik Johansson, Dimos V. Dimarogonas |
IEEE Trans. Intell. Transp. Syst. | 1 |
| 2016 | Cyber-Physical Control of Road Freight TransportabstractFreight transportation is of outmost importance in our society and is continuously increasing. At the same time, transporting goods on roads accounts for about 26% of the total energy consumption and 18% of all greenhouse gas emissions in the European Union. Despite the influence the transportation system has on our energy consumption and the environment, road transportation is mainly done by individual long-haulage trucks with no real-time coordination or global optimization. In this paper, we review how modern information and communication technology supports a cyber-physical transportation system architecture with an integrated logistic system coordinating fleets of trucks traveling together in vehicle platoons. From the reduced air drag, platooning trucks traveling close together can save about 10% of their fuel consumption. Utilizing road grade information and vehicle-to-vehicle communication, a safe and fuel-optimized cooperative look-ahead control strategy is implemented on top of the existing cruise controller. By optimizing the interaction between vehicles and platoons of vehicles, it is shown that significant improvements can be achieved. An integrated transport planning and vehicle routing in the fleet management system allows both small and large fleet owners to benefit from the collaboration. A realistic case study with 200 heavy-duty vehicles performing transportation tasks in Sweden is described. Simulations show overall fuel savings at more than 5% thanks to coordinated platoon planning. It is also illustrated how well the proposed cooperative look-ahead controller for heavy-duty vehicle platoons manages to optimize the velocity profiles of the vehicles over a hilly segment of the considered road network. Bart Besselink, Valerio Turri, Sebastian van de Hoef, Kuo-Yun Liang, Assad Al Alam, Jonas Mårtensson 0001, Karl Henrik Johansson |
Proc. IEEE | 3 |