With the emergence of connected and autonomous vehicles, sensors are increasingly deployed within car. Traffic generated by these sensors congest traditional intra-vehicular networks, such as CAN buses. Furthermore, the large amount of wires needed to connect sensors makes it hard to design cars in a modular way. These limitations have created impetus to use wireless technologies to support intra-vehicular communication. In this dissertation, we tackle the challenge of designing and evaluating data collection protocols for intra-car networks that can operate reliably and efficiently under dynamic channel conditions. First, we evaluate the feasibility of deploying an intra-car wireless network based on the Backpressure Collection Protocol (BCP), which is theoretically proven to be throughput-optimal. We uncover a surprising behavior in which, under certain dynamic channel conditions, the average packet delay of BCP decreases with the traffic load. We propose and analyze a queueing-theoretic model to shed light into the observed phenomenon. As a solution, we propose a new protocol, called replication-based LIFO-backpressure (RBL). Analytical and simulation results indicate that RBL dramatically reduces the delay of BCP at low load, while maintaining its high throughput performance. Next, we propose and implement a hybrid wired/wireless architecture, in which each node is connected to either a wired interface or a wireless interface or both. We propose a new protocol, called Hybrid-Backpressure Collection Protocol (Hybrid-BCP), for the intra-car hybrid networks. Our testbed implementation, based on CAN and ZigBee transceivers, demonstrates the load balancing and routing functionalities of Hybrid-BCP and its resilience to DoS attacks. We further provide simulation results, obtained based on real intra-car RSSI traces, showing that Hybrid-BCP can achieve the same performance as a tree-based protocol while reducing the radio transmission power by a factor of 10. Finally, we present TeaCP, a prototype Toolkit for the evaluation and analysis of Collection Protocols in both simulation and experimental environments. TeaCP evaluates a wide range of standard performance metrics, such as reliability, throughput, and latency. TeaCP further allows visualization of routes and network topology evolution. Through simulation of an intra-car WSN and real lab experiments, we demonstrate the functionality of TeaCP for comparing different collection protocols.