Tires are the interface between a vehicle and the ground providing forces and isolation to the vehicle. For vehicle safety, stability, maintenance, and performance, it is vital to estimate or measure tire forces, inflation pressure, and contact friction coefficient. Estimation methods can predict tire forces to some extent however; they fail in harsh maneuvers and are dependent on road surface conditions for which there is no robust estimation method. Measurement devices for tire forces exist for vehicle testing but at the cost of tens of thousands of dollars. Tire pressure-monitoring sensors (TPMS) are the only sensors available in newer and higher end vehicles to provide tire pressure, but there are no sensors to measure road surface condition or tire forces for production vehicles. With the prospect of autonomous driving on roads in near future, it is paramount to make the vehicles safe on any driving and road condition. This is only possible by additional sensors to make up for the driver's cognitive and sensory system. Measuring road condition and tire forces especially in autonomous vehicles are vital in their safety, reliability, and public confidence in automated driving. Real time measurement of road condition and tire forces in buses and trucks can significantly improve the safety of road transportation system, and in miming/construction and off-road vehicles can improve performance, tire life and reduce operational costs. In this thesis, five different types of sensors are designed, modelled, optimized and fabricated with the objective of developing an intelligent tire. In order to design these sensors,~both electromagnetic generator (EMG) and triboelectric nanogenerators (TENG) are used. In the first two initial designed sensors, with the combination of EMG and TENG into a single package, two hybridized sensors are fabricated with promising potential for self-powered sensing. The potential of developed sensors are investigated for tire-condition monitoring system (TCMS). Considering the impressive properties of TENG units of the developed hybridized devices, three different flexible nanogenerators, only based on this newly developed technology, are developed for TCMS. The design, modelling, working mechanism, fabrication procedure, and experimental results of these TENG sensors are fully presented for applications in TCMS. Among these three fabricated sensors, one of them shows an excellent capability for TCMS because of its high flexibility, stable and high electrical output,and an encapsulated structure. The high flexibility of developed TENG sensor is a very appealing feature for TCMS, which cannot be found in any available commercial sensor. The fabricated TENG sensors are used for developing an intelligent tire module to be eventually used for road testing. Several laboratory and road tests are performed to study the capability of this newly developed TENG-based sensor for tire-condition monitoring system. However the development of this sensor is in its early stage, it shows a promising potential for installation into the hostile environment of tires and measuring tire-road interacting forces. A comparative studies are provided with respect to Michigan Scientific transducer to investigate the potential of this flexible nanogenerator for TCMS. It is worth mentioning that this PhD thesis presents one of the earliest works on the application of TENG-based sensor for a real-life system. Also, the potential of commercially available thermally and mechanically durable Micro Fiber Composite (MFC) sensor is experimentally investigated for TCMS with fabricating another set of intelligent tire. Several testing scenarios are performed to examine the potential of these sensors for TCMS taking into account a simultaneous measurement from Michigan Scientific transducer. Although both flexibility and the cost of this sensor is not comparable with the fabricated TENG device, they have shown a considerable and reliable performance for online measuring of tire dynamical parameters in different testing scenarios, as they can be used for both energy harvesting and sensing application in TCMS. The extensive road testing results based on the MFC sensors provide a valuable set of data for future research in TCMS. It is experimentally shown that MFC sensor can generate up to 1.4 $\mu W$ electrical power at the speed of 28 $[kph]$. This electrical output shows the high capability of this sensor for self-powered sensing application in TCMS. Results of this thesis can be used as a framework by researchers towards self-powered sensing system for real-world applications such as intelligent tires.