4
CHAPTER 1
INTRODUCTION: INTELLIGENT VEHICULAR COMMUNICATIONS
scenarios. And, as a matter of fact, we partially succeeded by exploring and extending position-based
routing methods for vehicular scenarios. Actually, we were so successful that when observing the
route-finding capability of position-based methods on highways, the theoretically
achievable num-
ber of hops seemed to be almost unlimited. However, informal probing of the IETF MANET people
quickly showed that getting a protocol proposal on the standards track would require a tremendous
effort and would encounter significant opposition, since they were fiercely trying to reduce the number
of candidate protocols. Nevertheless, since the Fleet Net agenda called for
a proof-of-concept demon-
stration platform, we felt it appropriate to implement position-based routing in Linux with the ultimate
goal of performing some real-world measurements on the road.
1.2
EVOLUTION OF TRANSPORTATION MODELS
A transportation network can be categorized in numerous different ways. Nevertheless, we are more
interested in tracking the evolution of transportation modes in response
to the trends in technology
advance, methodology concepts, and practical requirements over a long time horizon. From this per-
spective, transportation models can be classified into different generations. By summarizing what has
been achieved in the past generations, we can offer some projections of what may be expected in
future generations (e.g., the next 30 years)
of transportation models, considering some promising ITS
technologies that are being, or expected to be, implemented. If one looks back into the history of the
transportation research, three major waves can be identified.
The first wave began in the 1950s with the construction and massive use
of freeway systems world-
wide, such as the US interstate system, which was based on earlier experience with the German auto-
bahn and American turnpikes. These projects provided new perspectives in transportation engineering.
Researchers and engineers were motivated to study the detailed characteristics of the new transporta-
tion systems and explore methods of operating and managing the expanding systems. Due to the dif-
ficulty and complexity of collecting data at that time, models during this period
were primarily empiri-
cal and static. Models and theories are developed based on either ideal assumptions, or very limited
experimental and survey data. However, they still serve as basic guidelines that help plan, construct,
and operate the early transportation systems. Transportation models developed during this time period
(1950s–1980s) are here referred to as first-generation models.
The second wave was triggered by the rapid development of information technologies after 1980,
as well as the legislation progress regarding
transportation systems, such as ISTEA, which is the emer-
gence of the ITS technologies. During this time period, the most critical issue that emerged was the bal-
ance between the limited supply that can be added to the existing infrastructure and the ever-growing
travel demands. Different
approaches have been taken, including exploring the additional capacity
of the existing infrastructure and using planning strategies to balance the transportation supply and
demand by promoting alternative transportation modes. Tackling such issues relies on more detailed
and dynamic information regarding travelers’ demands and road conditions. Information technolo-
gies, along with the developments in vehicle sensing technologies, allow engineers and researchers
to collect, analyze, model, and predict transportation phenomena more rapidly,
more efficiently, and
more accurately than ever before. During this period, dynamic, statistical, and disaggregated transpor-
tation models with rigorous formulations and efficient numerical methods originating from physics,
economics, computer science, and other scientific fields, suitable for network or system performance
