Cyclist priority at traffic lights through the “eyes” of CAVs
Prioritizing cyclists at signalized intersections using observations from connected autonomous vehicles
Connection with the internet and Internet of Things (IoT): also in traffic we can no longer do without. Nowadays, in the Netherlands, all new traffic light controllers (TLCs) will be connected to the cloud, and will connect to surrounding traffic, making the TLC to an iTLC (intelligent, informative TLC). The iTLC has more information about the traffic state near the intersection, and can optimize the control, and can inform traffic participants about the state of the traffic light (groenvoorspeller).
In modern cars, communication with the traffic controller is often built in. Cyclists can be detected by detectors, cameras (slimme verkeerslichten voor fietsers) and radar to inform the traffic light controller. Cyclists can also announce their arrival with mobile apps, as ring-ring or Schwung.
However, using more loop detectors or cameras to detect cyclists is expensive, and mobile apps have their disadvantages as well, for instance privacy, battery drainage, and cyclists who forget to activate the app.
CAVs must continuously sense the environment to function safely. This sensor information also can be used for advanced traffic monitoring and control applications. This makes the information gained by these sensors not only suitable for the CAV itself, to find its way through traffic, but it can also observe cyclists on a nearby cycle path. This makes CAV observations ideal for a new available source of information.
The poster highlights the potential of using cyclist observations by CAVs to augment the situational awareness of traffic signal controllers. The approach is implemented in a simulation study and quantifies the benefits of prioritizing cyclists and reducing lost times in the control cycle. The poster has been presented at the TRBAM 2023, the accompanying paper will be published in the TRR journal, and then will be added to this page.
Credits Figure 1 of the poster: adapted Photo by Mj on Unsplash
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