## 1 Introduction  
In the rapidly evolving field of wireless communication, routing protocols are essential for establishing efficient data transmission pathways in networks [1]. These protocols facilitate the exchange of information among nodes in dynamic environments, such as mobile ad hoc networks (MANETs) and vehicular ad hoc networks (VANETs) [2]. Among the most widely utilized routing protocols are Ad hoc On-Demand Distance Vector (AODV) and Greedy Perimeter Stateless Routing (GPSR) [3]. AODV establishes routes on an as-needed basis, minimizing overhead while ensuring that data packets reach their destinations, while GPSR employs geographic information to route packets based on the relative positions of nodes, which is particularly beneficial in environments with high mobility [4]. The effectiveness of these protocols, however, is challenged by the increasing complexity of modern networks, necessitating enhanced adaptability and resilience to fluctuating network conditions and varying node densities [5]. To address these challenges, bio-inspired algorithms have emerged as innovative solutions [6]. These algorithms draw inspiration from natural processes, allowing for adaptable strategies that can respond dynamically to environmental changes [7]. A notable example is the Bio-Inspired Adaptive Chameleon Method (BACM), which mimics the adaptive capabilities of the chameleon, an organism known for its ability to alter its behavior based on environmental stimuli [8]. BACM enhances AODV and GPSR by introducing a dynamic routing strategy that adjusts to changes in network topology, traffic conditions, and environmental constraints [9]. Existing research on VANET routing protocols like AODV and GPSR lacks a detailed analysis of how parameters and indicators, such as MaxJitter, Hello/Beacon Interval, and route validity time, affect performance in urban and highway scenarios, particularly for critical applications like autonomous vehicles [10]. VANET routing protocols can be broadly classified into two main categories based on the information used to calculate routing paths: geographical and topological protocols. Geographical routing utilizes vehicle positioning systems and location information to determine paths. In contrast, topological routing relies on the distribution of topology information among vehicles [11]. Topological protocols are further divided into reactive, proactive, and hybrid protocols. Geographical protocols, on the other hand, are categorized into greedy and stateless, street-aware, connectivity-aware, and infrastructure-assisted protocols. Additionally, a new paradigm based on bio-inspired algorithms has emerged and been classified into revolutionary and swarm intelligence protocols [12]. The following subsections provide further details on each category, emphasizing the principles, advantages, disadvantages, and research challenges associated with these routing protocols. Recent advances from past studies examine protocol performance, looking at the general effective. They fall short of fully addressing and exploring how variation in these parameters affects low latency, high reliability, and adaptive communication [13]. Thus, the work closes this gap by exploring the impact of parameters like MaxJitter, Hello/Beacon Interval, and route validity time on VANET routing protocols like AODV and GPSR in urban and highway settings. This will provide practical applicability for maximizing network performance, highlighting the critical role VANETs play in facilitating autonomous navigation and dependable communication. These parameters enable optimized route discovery, improved packet delivery rates, and minimized energy consumption, making it particularly suitable for dynamic network applications, including those involving autonomous vehicles [14; 15; 16]. In this work, we propose integrating the BACM into AODV and GPSR protocols to significantly enhance their performance in terms of throughput, delay, and routing overhead.