Efficient routing algorithms are essential to guarantee reliable communication in Vehicular Adhoc Networks (VANETs). In this paper, we present a twofold approach entailing the design of a new route metric for VANET communication, which considers important parameters such as the received signal strength; transmit power, frequency and the path loss. We further present an improved genetic algorithm-based route optimization technique (IGAROT) that guarantees better routing in VANETs. We used IGAROT to determine optimal routes required to communicate road anomalies effectively between vehicles in VANETs. The performance of our proposed algorithm was compared with the well-known conventional Genetic Algorithm (GA) route optimization technique under same simulation conditions. Based on the average route results obtained, our findings indicate that IGAROT provided 4.24%, 75.7% and 420% increment over the conventional GA in the low, medium and high car density scenarios, respectively. Our findings suggest that IGAROT improves road anomaly communication among vehicles thus enabling drivers to better navigate anomalous roads with the aim to reduce road-anomaly induced accidents. Further benefits of our system may include the prompt notification of road maintenance agencies concerning persisting road conditions via vehicle to infrastructure communication.