Description

The growing popularity of micromobility services has sparked new challenges to the pursuit of achieving zero fatal road accidents. Between 2021 and 2022, the incidence of injuries related to micromobility and e-bikes witnessed a troubling surge, marking a 21% increase. Moreover, since 2017, the frequency of injuries has exhibited an average annual rise of 23% in the United States. European statistics reveal that a mere 4% of e-scooter riders involved in accidents had been wearing helmets at the time of the incident. Meanwhile, German statistics bring attention to a troubling rise in fatal accidents involving e-bikes, a trend linked to their higher speeds compared to traditional bicycles. These findings underscore the growing necessity for innovative technologies dedicated to enhancing road safety for electrically supported vulnerable road users (e-VRU’s).

Integrating e-VRUs with the infrastructure and surrounding traffic through technologies such as Vehicle-to-Everything (V2X) holds significant promise in addressing current challenges. This approach has the potential to enhance communication and coordination between various elements of the transportation ecosystem, fostering a safer and more efficient environment for all road users. To unlock the full benefits of connected e-VRUs in different application scenarios, there is a need to optimize the communication channel with respect to the number of cyclists and other road users in the environment.

In this thesis, the student will analyze the optimal theoretical sampling rate of VAM messages for cyclists and e-bikes with varying position, speed and heading using our previous established model for cyclists. This will also involve e-bike cyclists travelling with adjusted speed for coordinated formations (platoon) and optimal traffic flow. A subsequent practical test will serve to validate the theoretical findings in comparison with measured VAM sampling rates in the field.