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121 Lifelong Education as a Necessary Foundation for Success in Travel Modeling Rick Donnelly, PB Consult Remarkable theoretical and practical advances intravel forecasting have taken place over the past twodecades. An unintended consequence of this has been a widening gap between research and practice, which this conference is designed to help overcome. There are many reasons for this gulf of knowledge, one being that most practitioners have not been able to stay current with new techniques. A lifelong training program to help close that gap is proposed as an essential part of the advancement of travel modeling. Travel demand forecasting has been an important tool for policy and investment analyses in the United States for more than 40 years. A loosely defined standard prac- tice was established during the early years and is still in use. The principles of this practice, based upon four- step sequential models of travel demand, are well known and documented in the literature. Several universities, as well as federal and some state transportation agencies, offer courses in the subject. Most transportation planners in the United States are familiar with the process, with many possessing the experience necessary to apply, extend, and maintain such models. There has been considerable R&D in the past decade that seeks to move the field beyond sequential models. Activity- and tour- based models have been widely dis- cussed in the literature, and several promising implemen- tations have been achieved. Freight has become an important issue in transportation planning, but its dynamics do not map well to the familiar four- step mod- eling paradigm. Work on large- scale simulation models such as Transportation Analysis and Simulation System has also opened new frontiers in travel modeling. Plan- ning applications of dynamic traffic assignments have sprung up within the past year, and seem to be ideal com- plements for activity- and tour- based models. Finally, there is a resurgence of interest in and development of integrated land useâtransport models in several locations. This new- age modeling is rapidly moving beyond lim- itations of the current practice in transportation plan- ning, which has required researchers to draw from a number of disciplines not normally encountered in travel modeling. Recent advances and techniques from other large- scale simulations in meteorology, operations research, economics, natural resources modeling, and logistics are all integral parts of the current research. Moreover, software development has become an impor- tant part of R&D. The skill set needed to approach many of these new models is impressive in its breadth, as well as its departure from current practice: ⢠Travel choice behavior (solid foundation in discrete choice modeling concepts); ⢠Activity- based travel analysis; ⢠Traffic science, control systems, and intelligent transportation systems; ⢠Network dynamics and disequilibrium; ⢠Simulation analysis and modeling, with emphasis on microsimulation and sample enumeration; ⢠Object- oriented programming; ⢠Database systems; ⢠Spatial analysis tools and techniques; and ⢠Integrated land useâtransport modeling.