Lately, significant research efforts are put in the area of designing smart cities by both academia and industry focusing on making use of city facilities (buildings, infrastructure, transportation, energy, etc.) in order to improve people’s quality of life and create a sustainable environment. Vehicular ad hoc networks (VANET) play a main role in supporting the creation of smarter cities. VANET are based on “smart” inter-vehicle communications and with the infrastructure via so called V2X communications (i.e. V2V – vehicle-to-vehicle and V2I/I2V – vehicle-to-infrastructure/infrastructure-to-vehicle). V2X communications demonstrated their huge potential when designing not only intelligent transportation solutions, but also green transportation solutions. Most of the research in this area targets a single class of VANET users represented by the car drivers. This thesis addresses different types of users, mainly the cyclists, as cycling is one of the most sustainable and green forms of transportation. The thesis proposes three main solutions: Speed Advisory System for Electric Bicycles (SAECy), an Energy Efficient Weather-aware Route Planner solution for Electric Bicycles (eWARPE) and a Fuzzy Logic-based Clustering Scheme (FuzzC-VANET) over vehicular networks. SAECy provides on-route assistance to the cyclists in order to improve their cycling experience and reduce the energy consumption in the particular case of electric bicycles. SAECy uses mainly I2V communication for obtaining traffic light related information, but also weather information. eWARPE provides off-route assistance to the cyclists in order to support them in avoiding the adverse weather conditions as much as possible, but also to save the battery in the particular case of electric bicycles. FuzzC-VANET is a generic clustering scheme dedicated for VANET that can be employed for information dissemination in SAECy’s context in order to enhance its performances and to increase the accuracy of weather information. FuzzC-VANET is also a response to two of VANET main issues, stability and scalability, and extends its benefits on all the other classes of users (i.e. drivers of different types of vehicles) in VANET. The performance of the proposed solutions was evaluated through multiple assessment techniques: experimental testing based on a real test-bed, interviews and online questionnaire to measure the need for the solution proposed and the interest of users and simulations based on highly realistic scenarios.The results clearly show improved performance of the proposed solutions in comparison with other similar state-of-the-art solutions.