Abstract
Modern traffic control systems are key to cope with current and future traffic challenges. In this paper information obtained from a microscopic traffic estimation using various data sources is used to feed a new developed traffic control approach. The presented method can control a traffic area with multiple traffic light systems (TLS) reacting to individual road users and pedestrians. In contrast to widespread green time extension techniques, this control selects the best phase sequence by analyzing the current traffic state reconstructed in SUMO and its predicted progress. To achieve this, the key aspect of the control strategy is to use Model Predictive Control (MPC). In order to maintain realism for real world applications, among other things, the traffic phase transitions are modelled in detail and integrated within the prediction. For the efficiency, the approach incorporates a fuzzy logic preselection of all phases reducing the computational effort. The evaluation itself is able to be easily adjusted to focus on various objectives like low occupancies, reducing waiting times and emissions, few number of phase transitions etc. determining the best switching times for the selected phases. Exemplary traffic simulations demonstrate the functionality of the MPC-based control and, in addition, some aspects under development like the real-world communication network are also discussed.
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Notes
- 1.
Depending on the used sensor technology, the pedestrian count can be a binary value (push buttons) or a measured number (e.g., radar sensors). The waiting times are applied and calculated respectively.
- 2.
LISA is a comprehensive proprietary software package for traffic engineering, testing control systems and for supplying ECU.
- 3.
The traffic consists of eight different vehicle types (passenger, delivery, bicycle, bus, trailer, semi-trailer, truck and motorcycle).
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Acknowledgment
The research is funded by the Ministry of Economy, Innovation, Digitalization and Energy of North Rhine-Westphalia, Germany. The authors would like to thank all partners of the Pilot Project Schlosskreuzung for their support and the provided data.
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Malena, K., Link, C., Bußemas, L., Gausemeier, S., Trächtler, A. (2022). Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments. In: Klein, C., Jarke, M., Helfert, M., Berns, K., Gusikhin, O. (eds) Smart Cities, Green Technologies, and Intelligent Transport Systems. VEHITS SMARTGREENS 2021 2021. Communications in Computer and Information Science, vol 1612. Springer, Cham. https://doi.org/10.1007/978-3-031-17098-0_12
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