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30 I N N O VAT I O N S I N T R AV E L D E M A N D M O D E L I N G , V O L U M E 1 25% decrease in in-vehicle travel times in the Dal- comfort and risk. Reliability is such a large element of lasFort Worth area. This analysis was conducted to the travel experience that individuals who are risk assess the reasonableness of the predications. The adverse will have a different behavior than those who activity-travel patterns were predicted for the entire syn- are risk prone. Monetary expenditures are also included. thetic population of 3,452,751 from 1,754,674 house- Numerous activities have a social content, which may holds for the base case and each of the four changes in focus on doing things with or for others. Agent-based vehicle travel times. The impact of the changes in in- microsimulation might offer the opportunity to address vehicle travel time on aggregate activity-travel patterns these issues. was examined for trip frequency, person miles of travel, Microsimulation models should include a learning vehicle miles of travel (VMT), and person hours of travel approach. On the one hand, they model scheduling-- (PHT). what an agent does, by which mode and route, and with The 10% increase in in-vehicle travel times reduced whom. On the other hand, they model competition for the total number of trips by 1%, whereas a 25% increase slots on networks and facilities. Initially, iterations in in-vehicle travel times decreased the total number of between scheduling, the mental map, and the competi- trips by 2.4%. A 10% decrease in the in-vehicle travel tion will help revise the cost estimates. The parameter time increased total trips by 1.1% and a 25% decrease estimation is typically not included because of complex- resulted in an increase in total trips of 3.1%. An increase ity, but it should really be included. in in-vehicle travel times decreases VMT and a decrease A first step in the use of microsimulation models is in in-vehicle travel times results in an increase in VMT. creating a description of the world. The availability of An increase in in-vehicle travel times increases the PHT accurate data is critical in this step. MATSIM-T provides for work and decreases the PHT for nonwork purposes, various tools to deal with these and other issues. resulting in an overall increase in PHT. A decrease in in- MATSIM-T implements numerous elements to create the vehicle travel times reduces the PHT for work and world and to manage the different resolutions. It pro- increases the PHT for nonwork purposes, resulting in an vides an agent database, which is in memory. It provides overall decrease in PHT. various tools to implement the competition for a slot on the network. Various dynamic traffic assignment tools can be selected. There are also various tools to schedule MATSIM/PLANOMAT: A MICROSIMULATION activities. SYSTEM OF ACTIVITY DEMAND The focus is on modeling household interaction. This household interaction includes choosing an Kay Axhausen optional allocation of time over a day and decisions on joint activities, journey destination, and journey mode. Kay Axhausen described an open-door Java-based A tool searches for the optimum schedule, which takes toolkit, which provides the user with various instruments numerous iterations. These iterations currently take a lot to implement activity-based models and scheduling- of time to run. based models. The model is called Multi-Agent Trans- Zurich is being used as a test bed because it has a portation SIMulation Toolbox (MATSIM-T). The detailed navigation network, available timetables for following points were covered in his presentation. public transport, and information on facilities available for each mode. The agent population has been generated First, it is beneficial to examine how current behav- using seven dimensions. Estimates of travel demand are ior is being modeled at the microscopic level. Elements available from a national travel survey and from include generalized costs of the route-mode-location observed counts. The initial analysis indicated that the alternative. Budgets and long-term commitments are smarter the agent and the more variability of adjustment included. Tastes include values, attitudes, and life style by the agent, the faster convergence or a steady state is by sociodemographics. One of the big attractions of reached. If the agents in the optimization are allowed a using microsimulation is that there is a national frame- wider search base, they find solutions quicker. This work to account for differences in tastes between per- analysis indicates that fewer interactions may be needed sons. There is also an increased awareness that the to reach a steady-state system. choices that individuals make are driven not only at the The software will be available at www.source individual level and at the household level, but also for others to use. Efforts are under way to within the larger social network, which will decide and regain the capabilities of the full scheduler. Parameter influence location choices and activity choices. estimation also needs to be performed. Visualization and The generalized cost of a route-mode-destination analysis tools are also being considered, along with alternative includes time and reliability, adjusted for both methods to integrate social networks.