The main objectives of Task Order 4136 are (1) the design of improved freeway on-ramp metering strategies that make use of recent developments in traffic data collection, traffic simulation, and control theory, and (2) the testing of these methods on a 14-mile segment of Interstate 210 Westbound in southern California. To date, the major accomplishments of this project include (i) the development of a complete procedure for constructing and calibrating a microscopic freeway traffic model using the Vissim microsimulator, which was applied successfully to the full I-210 test site, (ii) a simulation study, using the calibrated Vissim I-210 model, comparing the fixed-rate, Percent Occupancy, and Alinea local ramp metering schemes, which showed that Alinea can improve freeway conditions when mainline occupancies are measured upstream of the on-ramp (as on I-210 and most California freeways), as well as when occupancy sensors are downstream of the on-ramp, (iii) development of computationally efficient macroscopic freeway traffic models, the Modified Cell Transmission Model (MCTM) and Switching-Mode Model (SMM), validation of these models on a 2-mile segment of I-210, and determination of observability and controllability properties of the SMM modes, (iv) design of a semi-automated method for calibrating the parameters of the MCTM and SMM, which, when applied to an MCTM representation of the full I-210 segment, was able to reproduce the approximate behavior of traffic congestion, yielding about 2% average error in the predicted Total Travel Time (TTT), and (v) development of a new technique for generating optimal coordinated ramp metering plans, which minimizes a TTT-like objective function. Simulation results for a macroscopic model of the 14-mile I-210 segment have shown that the optimal plan predicts an 8.4% savings in TTT, with queue constraints, over the 5-hour peak period.

These proceedings collect selected papers from the 7th International Conference on Green Intelligent Transportation System and Safety held in Nanjing on July 1-4, 2016. The selected works, which include state-of-the-art studies, are intended to promote the development of green mobility and intelligent transportation technology to achieve interconnectivity, resource sharing, flexibility and higher efficiency. They offer valuable insights for researchers and engineers in the fields of Transportation Technology and Traffic Engineering, Automotive and Mechanical Engineering, Industrial and System Engineering, and Electrical Engineering.

This edited book focuses on recent developments in Dynamic Network Modeling, including aspects of route guidance and traffic control as they relate to transportation systems and other complex infrastructure networks. Dynamic Network Modeling is generally understood to be the mathematical modeling of time-varying vehicular flows on networks in a fashion that is consistent with established traffic flow theory and travel demand theory. Dynamic Network Modeling as a field has grown over the last thirty years, with contributions from various scholars all over the field. The basic problem which many scholars in this area have focused on is related to the analysis and prediction of traffic flows satisfying notions of equilibrium when flows are changing over time. In addition, recent research has also focused on integrating dynamic equilibrium with traffic control and other mechanism designs such as congestion pricing and network design. Recently, advances in sensor deployment, availability of GPS-enabled vehicular data and social media data have rapidly contributed to better understanding and estimating the traffic network states and have contributed to new research problems which advance previous models in dynamic modeling. A recent National Science Foundation workshop on “Dynamic Route Guidance and Traffic Control” was organized in June 2010 at Rutgers University by Prof. Kaan Ozbay, Prof. Satish Ukkusuri , Prof. Hani Nassif, and Professor Pushkin Kachroo. This workshop brought together experts in this area from universities, industry and federal/state agencies to present recent findings in this area. Various topics were presented at the workshop including dynamic traffic assignment, traffic flow modeling, network control, complex systems, mobile sensor deployment, intelligent traffic systems and data collection issues. This book is motivated by the research presented at this workshop and the discussions that followed.