This book develops a methodology for designing feedback control laws for dynamic traffic assignment (DTA) exploiting the introduction of new sensing and information-dissemination technologies to facilitate the introduction of real-time traffic management in intelligent transportation systems. Three methods of modeling the traffic system are discussed:
Techinques accounting for the importance of entropy are further new inclusions at various points in the text.
Researchers working in traffic control will find the theoretical material presented a sound basis for further research; the continual reference to applications will help professionals working in highway administration and engineering with the increasingly important task of maintaining and smoothing traffic flow; the extensive use of end-of-chapter exercises will help the graduate student and those new to the field to extend their knowledge.
Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.Shows the reader how to make more accurate predictions of and control traffic flow by providing a full treatment of the feedback-based dynamic traffic assignment problem
Derives conrol laws usable in real world traffic management
Each chapter provides codes so that readers can test and improve the simulations discussed
Pushkin Kachroo
Distributed-parameter Systems Dynamic Traffic Assignment Feedback Control Godunov-based Entropy Highway Infrastructure ITS Intelligent Transportation Systems Traffic Flow Traffic Networks landscape/regional and urban planning