To achieve the goals which have been set regarding climate change, adjustments have to be made in many areas of daily life. Road transport is one aspect that is especially in the focus of public attention. At the present moment, most vehicles on the road are equipped with conventional internal combustion engines. In this context, it is mandatory to restrict pollutant emissions to a minimum level by implementing a target-oriented traffic management strategy. There is however the problem that more complex traffic management solutions lead to increased costs as well as to higher energy consumption in the course of data capture and processing. A more widespread use of these systems leads to the same consequences.
With the GIGA project, this trade-off is addressed by developing a new type of traffic detector which works acoustically. Multiple sensors are connected via a network that is designed based on an edge cloud approach. Data processing is organised decentrally which means that just a small amount of extracted metadata has to be transferred over the network. Thus, data traffic and resulting energy consumption can be minimised. Every sensor is equipped with an array of inexpensive MEMS microphones. Compared to conventional traffic detectors, the costs are low and therefore more sensors can be installed throughout the traffic infrastructure. This leads to a higher precision of the obtained real time data which can be used for an improved traffic management. The new system accounts for energy efficiency on the control level as well as on the level of vehicle traffic itself.Copyright: © ISB 2021, Bing Maps 2021
The main research focus of the ISB in the wake of GIGA lies on the impact the new sensors have on traffic management. For the investigations, a microscopic transport model of the so-called Aachen avenue ring is employed. The reference section includes several junctions with traffic lights that are coordinated. In the model, the relevant intersections are furnished with the new acoustic traffic detectors. The traffic light control logic is then adapted to the added sensors. In this connection, fluidity of traffic and travel time do not serve as key performance indicators. Instead, the pollutant emissions that are generated by the vehicles shall be minimised. To compare the reference case versus the planned case, emission values are estimated using the Handbook Emission Factors for Road Transport (HBEFA). Furthermore, accuracy requirements are derived from the model that can be taken into account during the development process of the sensors.
Course of action
- Configuration of a digital traffic flow simulation model for a reference section of the Aachen avenue ring
- Development of emission-optimised traffic signal control algorithms for multiple traffic scenarios with acoustic sensors implemented into the simulation
- Potential analysis: simulation of a reference case and a planned case, deduction of statements about potential regarding energy savings and emission reduction under assumption of realistic sensor characteristics
In conclusion, the traffic flow simulation shows that the potential for emission reductions is lower than 5 %. Earlier studies with optimized traffic light control lead to higher potentials. This is due to the fact that in these studies, the status quo has been taken as the reference case, while the GIGA project assumed a reference case which was already significantly optimized compared to the current situation.
Project management at the ISB
10.2020 - 06.2021
Chair and Institute of Urban Transport Planning (ISB), RWTH Aachen University
Chair of Integrated Digital Systems and Circuit Design (IDS), RWTH Aachen University [coordinator of the collaboration]
Laboratory for Communications Engineering (NTLab), FH Münster
HEAD acoustics GmbH, Herzogenrath