ELABORATOR Project / e-Trikala

Overview

This material presents baseline data from a questionnaire assessing the safety and quality of bike lanes in Trikala. It supports a planned intervention focused on redesigning cycling infrastructure and improving monitoring through sensor-based data collection. The findings provide insights into user behaviour, perceived safety, and key barriers to cycling. The results aim to inform evidence-based improvements for safer and more accessible cycling conditions. The survey contributes to data-driven urban mobility planning within the ELABORATOR project.

Highlights

The survey, conducted over three weeks with 311 responses, shows that most participants are middle-aged urban residents, with a slight majority of men (pages 3–6). As shown in the chart on page 7, bicycles are widely used alongside cars, with many respondents cycling frequently, often on a daily basis (page 8).

Cycling is mainly used for commuting, shopping, and leisure, as illustrated in the chart on page 9. However, safety remains a concern. While some users feel moderately safe, a notable share report low safety levels, and around 79% have experienced dangerous situations on bike lanes (page 14). Key risks include illegal use of bike lanes by other vehicles and unsafe driving behaviour (page 13).

Qualitative responses highlight recurring issues such as incomplete cycling networks, poor lighting, lack of separation from traffic, and illegal parking on bike lanes (pages 17 and 21). Night-time safety is particularly problematic, with many respondents reporting low confidence when cycling after dark (page 18). Suggested improvements include better infrastructure design, stricter enforcement, improved signage, and continuous, well-connected bike lane networks.

Conclusion

This material provides a clear evidence base for improving cycling safety in Trikala. It highlights the need for continuous and protected bike lane infrastructure, stronger enforcement of traffic rules, and better urban design to support cyclists. The findings support the implementation of sensor-based monitoring systems and targeted infrastructure upgrades. For cities, this approach demonstrates how combining user feedback with real-time data can guide effective and inclusive cycling interventions.