In this project QoS-Aware node Selection Algorithm (QASA) for routing protocol is proposed. Our algorithm aims to select the next-hop vehicle to communication. Most VANET applications are built upon the data push communication model, where information is disseminated to a set of vehicles. In vehicular ad hoc networks (VANETs), vehicles transmit traffic and safety-related information, including traffic congestion-avoidance messages, accident warnings, and accident reports, etc., which assist drivers in making proper decisions to avoid vehicle collisions and congestion. Vehicular Ad Hoc Networks (VANETs) are created by applying the principles of mobile ad hoc networks (MANETs) – the spontaneous creation of a wireless network for data exchange – to the domain of vehicles. They are a key component of intelligent transportation systems (ITS). VANETs support a wide range of applications – from simple one hop information dissemination of, e.g., cooperative awareness messages (CAMs) to multi-hop dissemination of messages over vast distances. Most of the concerns of interest to mobile ad hoc networks (MANETs) are of interest in VANETs, but the details differ. Rather than moving at random, vehicles tend to move in an organized fashion. The interactions with roadside equipment can likewise be characterized fairly accurately. And finally, most vehicles are restricted in their range of motion, for example by being constrained to follow a paved highway. In this project, the system presents QoS- Aware node Selection Algorithm (QASA) for routing protocol, a novel multichannel TDM MAC protocol proposed specifically for a VANET scenario. Applications in vehicular networks can have different QoS requirements. Some applications require minimum delay regardless of the throughput, while others require the opposite, and some applications may need a balance between throughput and average time delay. Moreover, QASA utilizes a transmission range-based metric that can be changed as per application requirements, whether it is high throughput or minimum end-to-end delay. Simulation results show the effectiveness of our approach in terms of improved QoS metrics in different vehicular network scenarios.