Embedded sensors and actuators are revolutionizing the way we perceive and interact with the physical world. Current research on such Cyber-Physical Systems (CPSs) has focused mostly on distributed sensing and data gathering. The next step is to move from passive information extraction from the physical world towards an active framework where information is retrieved, processed, and acted upon in situ. As an example of such sensor-actuator systems that provide large-scale, distributed coordination, we consider Intelligent Transportation Systems (ITSs), with the goal of increasing travel safety and efficiency. The proliferation of wireless technologies enables different actors (e.g., pedestrians, motorists, traffic operators) to communicate with each other cheaply, efficiently, and securely. By embedding computational intelligence, communication and control into such ITSs, it will be possible to build collaborative transportation applications that help solve, for example, congestion and parking problems. This thesis explores the following question: To what extent is it possible to build distributed ITS systems that rely exclusively on local communication between nodes? The potential benefits of building such systems without infrastructure are numerous, including lower fixed and variable costs, avoiding regulatory hurdles, lower entry barriers for new players, and more control over privacy. On the other hand, self-organized ITSs without infrastructure have to operate under challenging conditions: large scale, high mobility, lack of end-to-end connectivity, ephemeral contacts between wireless nodes, and heterogeneous node capabilities. Although the networking research community has invested a significant effort in designing service abstractions that mimic traditional IP connectivity on top of wireless ad hoc networks, the ITS scenarios considered in this work are too challenging to implement such a service model. The main goal of this thesis is to design communication service models and their underlying protocols that can operate in collaborative transportation applications, and to demonstrate their effectiveness through analysis of traffic data and through realistic simulations. A key point is that the ITS applications we consider can rely on more limited service primitives, because they do not require a general any-to-any delivery service with strict performance guarantees. We first define the collaborative transportation applications of interest. Then we quantify their potential benefits and discuss their functional requirements. Next, we focus on the problem of the collection of large-scale mobility data. We propose a new method for collecting such data and introduce a novel mobility data mining framework, which is necessary to study collective mobility patterns in the context of wireless ad hoc networking. Relying on the analysis of real-life mobility traces, we find that despite the high node mobility, clusters of time-stable connectivity emerge and last at specific locations. Outside such clusters the connectivity between nodes remains sparse. This leads us to the proposal of a new mobility model that captures in an elegant way two phenomena observed in reality, i.e., emergence of stable clusters and network partitioning. This mobility model, called Heterogeneous Random Walk (HRW), appears to be the worst-case mobility model for many mobility-assisted protocols. Moreover, we show that the HRW mobility model predicts the performance of an epidemic dissemination protocol more accurately than other, similarly parsimonious models. Based on the lessons learned from the mobility data analysis, we propose a new abstraction that allows us to capture collective mobility patterns. This abstraction, called a Mobility Map, can be shared globally among mobile nodes and it can be used to improve communication in mobile partitioned networks (MPNs). Notably, we present a new geocasting protocol called GeoMobCast, which uses Mobility Maps to minimize message delay. This protocol is designed to provide the users of the collective transportation applications with the required communication service. Finally, we turn our attention on the real-life implementation of the distributed ITS that leverage short-range wireless communication. To this extent, we present the results of our experimental work with wireless sensor network technologies. We also present the necessary simulation toolbox designed to implement and evaluate collaborative transportation applications.