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Transportation scientists employ modeling and simulation techniques to capture the complexities of transportation systems and develop and assess solutions to alleviate existing and future transportation-related problems. This book introduces transportation engineering students and junior engineers to the concept of transportation network modeling, network coding, model calibration and validation, and model evaluation. Travel demand models are sensitive to demographic changes and can explain and forecast how a new transportation supply system leads to a new transportation demand pattern. This book also describes how demand models evolved from trip-based to the newer generation of activity-based and agent-based to overcome some of the shortcomings of the four-step approach and improve models' prediction power.

Abstract
The complexity of navigation in cities has increased with the expansion of urban areas, creating challenging transportation problems that drive many studies on the navigability of networks. However, due to the lack of individual mobility data, large-scale empirical analysis of the wayfinder's real-world navigation is rare. Here, using 225 million subway trips from three major cities in China, we quantify navigation difficulty from an information perspective. Our results reveal that (1) people conserve a small number of repeatedly used routes and (2) the navigation information in the subnetworks formed by those routes is much smaller than the theoretical value in the global network, suggesting that the decision cost for actual trips is significantly smaller than the theoretical upper limit found in previous studies. By modeling routing behaviors in growing networks, we show that while the global network becomes difficult to navigate, navigability can be improved in subnetworks. We further present a universal linear relationship between the empirical and theoretical search information, which allows the two metrics to predict each other. Our findings demonstrate how large-scale observations can quantify real-world navigation behaviors and aid in evaluating transportation planning.

AbstractThe aim of this study was to analyze and evaluate synchronization and stability issues for the planning, operation, and control of processes in automotive transportation networks. We modeled transportation networks by using a coupled oscillator network based on a modified Kuramoto model. Each transport process was mapped as a phase oscillator indicating the transport time, period, and delay. The method could be applied to complex networks where it has not been possible to find analytical solutions. The novel generic oscillator approach was then applied to two transport topologies, namely, milk‐run and just‐in‐sequence transport, based on real‐world problems from a German car manufacturer. We conducted a detailed study of the parameter regions where different synchronization regimes occurred and investigated how the topology influenced the stability and dynamic behavior of transport networks. In particular, we focused on how transport period offsets and transport delays affected synchronous states. We showed that by the introduction of a transport synchronization matrix, the synchronization states in a transport network could be represented in a compact and comprehensive manner. Moreover, thresholds for round‐trip stability could be calculated by analyzing the phase decoupling of a milk‐run. These results were used for the vehicle route planning of milk‐runs with synchronization constraints. Furthermore, the influence of the time delay of a track and trace system on the transport synchronization was analyzed. Finally, for the subsequent investigation of a just‐in‐sequence transport network, we showed how an adaptive control mechanism could re‐synchronize an out‐of‐tune delivery process.

The debate over Transportation Network Companies (TNCs) like Uber and Lyft has become quite polarizing in recent years, leaving many municipalities unsure how to move forward regarding regulation. Municipalities can choose to enforce traditional regulations, applying the same safety standards and supply constraints to TNCs as taxi companies. Or, municipalities can view TNCs as entities different than taxi providers and allow TNCs to regulate themselves through regulatory organizations that operate outside the scope of government intervention. States and cities such as Massachusetts, Colorado, and Houston are pioneers in the regulation of TNCs. However, each city or state has implemented regulations that fall within the spectrum of complete governmental regulation and self-regulation. Ultimately, a moderate approach to regulation of both TNCs and taxi companies is a reasonable response to the TNC debate. ; https://deepblue.lib.umich.edu/bitstream/2027.42/136582/1/Dupuy_TheRegulationOfTransportationNetworkCompanies.pdf