The use of personal light electric vehicles (PLEVs), such as electric scooters,
has rapidly increased in recent years. However, their widespread use has raised
concerns about rider safety due to their vulnerability in shared traffic spaces.
To address this issue, this paper presents a radar-based rider assistance system
aimed at enhancing the safety of PLEV riders. The system consists of an adaptive
feedback system and a single-channel anti-lock braking system (ABS). The
adaptive feedback system uses multiple-input multiple-output (MIMO) radar
sensors to detect nearby objects and provide real-time warnings to the rider
through haptic, visual, and acoustic signals. The system takes into account
traffic density and uses online data to warn about obscured objects, thereby
improving the rider’s situational awareness. Results from testing the feedback
system show that it effectively detects potential collisions and provides
warning signals, reducing the risk of accidents. The ABS is designed to prevent
dangerous braking scenarios in single-track vehicles, such as rear-wheel
lift-off and front-wheel locking. A virtual model was created to simulate
critical riding situations and determine suitable control parameters. Testing of
the MiniMAB ABS in real road tests using these parameters showed that it
effectively prevented rear-wheel lift-off on high-grip roads and front-wheel
locking on low-friction surfaces during emergency braking, improving riding
stability and steerability. In conclusion, the results of this study indicate
that the use of the proposed rider assistance system has the potential to
greatly contribute to the safe and conflict-free shared use of traffic spaces.
The system provides real-time warnings to the rider, thereby reducing the risk
of accidents. The implementation of the ABS improves riding stability and
steerability, providing a safer and more pleasant riding experience. The system
offers a new and improved solution to the growing concerns surrounding the
safety of PLEV riders.