University of Twente Student Theses


Early Warning System for Safe Lateral Maneuver of Bicycles

Kalaiselvan, Kaushik (2021) Early Warning System for Safe Lateral Maneuver of Bicycles.

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Abstract:Sustainable and smart mobility strategies are now starting to be adopted to reduce the CO\textsubscript{2} emission as well as take advantage of digitalization and automation to achieve seamless, safe, and efficient transportation. Bicycles and e-bikes are considered to be the leaders of this transition, as they are cost-effective and have a positive impact on health. With the growing popularity and usage of bicycles, cycling safety becomes more critical. The lateral maneuver of bicycles is a typically apprehended maneuver on the roads and improper assessment of the surroundings during this typically causes various accidents. Although this action is highly similar to the lane change maneuver performed in cars, the assistance systems developed for cars will not be effective for bicycles, due to the characteristics traits of bicycles such as limited size/space, low cost, low weight, vehicle dynamics, and their road infrastructure. This brings many challenges to the system design. The solutions for bicycles are required to be cost-effective, less complex in terms of hardware and software design, efficiently provide maximum utility with minimal resources, and provide a relatively good accuracy across different environments at the same time. In this work, we design and demonstrate a novel multi-modal early warning system to assist cyclists in identifying dangerous situations during lateral maneuvers. To the best of our knowledge, this is the first work that addresses the constraints, designs a complete system for lateral maneuver of bicycles, and validates it using extensive experiments in real-road scenarios. It consists of a 76GHz millimeter wave (mmWave) radar sensor and two ultrasonic sensors to detect targets such as cars, trucks, bicycles, and pedestrians in the rear-side blind-spot regions as well as approaching from behind; and using the combination of Time-to-Collision (TTC) and Minimum-Safe-Distance (MSD) metrics to assess and generate warnings about potential danger at an early stage. The warnings generated by the system include two distinct information and provide improved utility towards the safety of bicycles. The warnings indicate the side of potential maneuvering hazard to host cyclist and of a dangerously approaching vehicle right behind the host bicycle. This additional information can be used to alert the cyclist of the approaching bicycle to be aware of the host bicycle to mitigate a collision. From the extensive experiments in real-road scenarios, the method is deemed feasible and can identify threats and warn the rider about 5 seconds in advance with an accuracy of 95.2%.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:55 traffic technology, transport technology
Programme:Embedded Systems MSc (60331)
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