Traffic logistics is an extremely important topic for our society. Research on traffic logistics seeks to reconcile economic, social and ecological objectives. Transport and logistics should be maximally efficient, with minimum delay and limited adverse impact on the environment.
Novel technological developments, including autonomous driving and the massive availability of
data, pose new opportunities, and offer interesting challenges to researchers.
In this meeting, we aim to bring together researchers from academia and from industry at large.
We shall have five sets of “duo lectures”, devoted to five different areas of traffic logistics.
The first talk of each duo centers mainly on the problem and the second talk focuses more on scientific solution methodology.
Some of the talks may be mathematically oriented, but generally speaking we aim to make this day accessible for a rather broad audience.
The meeting is supported by the Gravity program NETWORKS and PWN (Platform Wiskunde Nederland), as part of their outreach activities.
|Marko Boon||Eindhoven University of Technology|
|Onno Boxma||Eindhoven University of Technology|
|Richard Boucherie (University of Twente)|
|Bas van der Bijl (Sweco)|
|Stijn Fleuren (Eindhoven University of Technology)|
|Maurice Kwakkernaat (TNO)|
|Rob van der Mei (CWI)|
|Wim van Nifterick (ARS Traffic & Transport Technology)|
|Frank Ottenhof (TrafficLink)|
|Remko Smit (Rijkswaterstaat)|
|Maaike Snelder (TNO-TU Delft)|
|Maarten Steinbuch (Eindhoven University of Technology)|
Challenges in optimal traffic control
Through a series of examples we illustrate both the practical and mathematical challenges in optimal traffic control. Starting from a single intersection we will gradually build more complicated network structures, including an intersection with vehicle actuated control and a green wave through multiple intersections. Practical constraints such as push-button controlled traffic lights for pedestrians, public transport priority, and the lane structure of road sections may be included in detailed simulation models. For some idealised cases mathematical models have been developed that provide further structural insight in traffic control. New technologies like local vehicle-infrastructure communication and longe range tracking radars increase the knowledge of the traffic state and its dynamics but also raise the level of expectation and make the processing more challenging.
The future of mobility
In the future we will increasingly be surrounded by intelligent technology; both inside our homes as outside on the street, in visible as well as invisible ways. Cars will evolve into iPads on wheels and all kinds of robots will help do our job and take care for the ill and elderly. Living with a private robot will be as common as keeping a pet. Every day the interaction between humans and technology will increase. It will change society and this revolution offers opportunities for solving social problems. For the high tech industries it means that technological changes will speed up, connectivity of machines will enable new services, and processing of smart materials will enlarge the design space. The systems thinking, integration and multi-disciplinary aspects will become key enablers for innovation. The automotive sector will change in the next decade more than in the past 100 years.
The Next Generation of Traffic Light Control
The rise of autonomous vehicles has a great impact on urban traffic light control. The next generation vehicles have an increased demand of traffic light controllers: not only the current phase of the signals is required, but also the future state changes. A reliable prediction of the expected state changes enables (semi-)autonomous vehicles to adopt their approach to the controlled intersection resulting in a more efficient passage of the intersection. On the other hand, the future promises also an increase in available traffic data for traffic light controllers. The presence of vehicles is not only measured by loop detectors, the vehicles continuously communicate their position and route to the traffic light controller. This additional knowledge of the traffic allows an optimized control of the traffic which results in a higher throughput of the controlled intersection. Sweco presents a novel methodology for traffic light control which meets the demands of autonomous vehicles and makes use of the additional data provided by (semi-)autonomous vehicles. This methodology is already applicable and shows promising results.
Optimization of fixed-time traffic light control and lane markings at isolated intersections
When a traffic intersection is designed, this design is usually based on the forecasted demands at the intersection in the upcoming years. Typically the current demands are estimated or counted and some growth factor is applied to estimate the future demands. An important problem in the design of a traffic intersection is deciding what lane-use-arrows to use for each lane at the intersection. These lane-use-arrows indicate what movements are allowed at that specific lane, e.g., should there be one or two lanes permitting a left-turn movement? It is desirable to choose these lane-use-arrows so that the maximum sustainable growth factor is as large as possible; the time period during which the intersection can handle the amount of traffic that arrives at it is then as large as possible. To this end, a mixed-integer programming problem is formulated that chooses the lane-use-arrows such that the growth factor is maximized. Besides optimizing the lane-use-arrows it also optimizes fixed-time traffic light control, i.e., it returns a signal group schedule that visualizes when each of the traffic-lights have a green, yellow and red indication. The optimization program returns the signal group schedule that can handle the forecasted demands for the maximized growth factor.
Real-time network management and effective incident management
No abstract available yet.
Do we need more or less road infrastructure when automated vehicles hit the market?
No abstract available yet.
To register for this event, please fill in the online form: Registration Traffic Logistics
Eurandom, Mathematics and Computer Science Dept, TU Eindhoven,
De Groene Loper 5, 5612 AE EINDHOVEN, The Netherlands
Eurandom is located on the campus of Eindhoven University of Technology, in the MetaForum building, 4th floor (more about the building). The university is located at 10 minutes walking distance from Eindhoven main railway station (take the exit north side and walk towards the tall building on the right with the sign TU/e).
Accessibility TU/e campus and map.
For those arriving by plane, there is a convenient direct train connection between Amsterdam Schiphol airport and Eindhoven. This trip will take about one and a half hour. For more detailed information, please consult the NS travel information pages.
Many low cost carriers also fly to Eindhoven Airport. There is a bus connection to the Eindhoven central railway station from the airport. (Bus route number 401) For details on departure times consult Public Transport.
The University can be reached easily by car from the highways leading to Eindhoven. For details: Route and map TU/e campus.
● Conference facilities
Conference room, MetaForum Building “MF11 & 12”.
The meeting-room is equipped with a data projector, an overhead projector, a projection screen and a blackboard. Please note that speakers and participants giving an oral presentation are kindly requested to bring their own laptop or their presentation on a memory stick.
Should you need to cancel your participation, please contact Patty Koorn, the Workshop Officer.
Mrs. Patty Koorn, Workshop Officer, Eurandom/TU Eindhoven, email@example.com