Road Safety Impacts and User Acceptance of Smart Connected Bikes
The last two decades have seen a growing trend towards electric bicycles (e-bikes). Due to the increasing living cost and the shift to environmentally friendly transport modes, the number of e-bikes will continue to increase. The growing popularity of e-bikes has many advantages, but at the same time, the number of crashes with (mainly elderly) e-bike users has grown rapidly. Recently there has been a surge of interest in new technologies such as sensors and IoT on bicycles in order to reduce cycling crashes, especially for e-bike users. A possible solution for it could be the Smart Connected Bike (SCB) which will be connected to urban infrastructure as well as with other vehicles through wireless technologies to increase safety and comfort.
This research project aims to evaluate the impacts of SCB prototypes on traffic safety and user’s acceptance level. This thesis comprises four parts: first, technologies potentially incorporated on SCB affecting safety will be studied through a literature review analysis. This part will also define bicycle smartness levels based on their functionalities and evaluate the Technology Readiness Levels of bicycle technologies. Second, the user’s acceptance level and Willingness to Pay for smart features and SCB will be investigated by conducting a survey in several European countries. Third, a traffic safety model will be created based on existing crash data, build environment characteristics and weather conditions across the Netherlands in order to investigate hot-spot locations and predict new high-risk locations. This model will inform cyclists when they enter critical locations to avoid crashes. Finally, in the fourth part, the traffic safety impacts of the SCB will be examined through field trails in multiple cities across the Netherlands, investigating the perceived safety and riding behavioural changes of the users under different traffic environments.
The methodological approach in this study is a mixed methodology starting with a literature review and will continue with a survey. Advanced psychological, econometric and statistical models will be used in order to draw out the results.
The PhD project is funded by Accell Group and part of the Smart Connected Bike research and innovation programme led by Prof. Paul Havinga, Pervasive Systems group, Dpt. of Computer Science, University of Twente and prof. Karst Geurs, Transport Engineering and Management Group, dpt. of Civil Engineering, University of Twente.
Through this study, there will be the opportunity for BSc and MSc students to investigate human behavioural factors towards e-bikes and state-of-the-art bicycle technologies, barriers to using bicycles in different countries, and crash risk prediction models based on the collected data.
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