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Innovations in Travel Demand Modeling, Volume 2: Papers (2008)

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Suggested Citation:"T57054 txt_192.pdf." National Academies of Sciences, Engineering, and Medicine. 2008. Innovations in Travel Demand Modeling, Volume 2: Papers. Washington, DC: The National Academies Press. doi: 10.17226/13678.
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position with arbitrary position accuracy. The accuracy can be changed from 10 cm to 50 m by changing the type of RFID tag, and various behaviors can be authenticated. Unlike conventional questionnaire and GPS surveys, in which the authentication of precise behavior spaces was difficult due to low position accuracy, reliable authenti- cation of transport mode is made possible by installing RFID tag readers in buses and in bicycle parking lots or by attaching RFID tags to bicycles. And the collection of data on purchase behaviors of individuals is made possi- ble by installing readers at cash registers. Applications of survey techniques are shown Figures 2 and 3. This survey system has been implemented with passive- and active- type RFID tags, adds points accord- ing to the content of individuals’ history of town walk- ing, and transmits the content in real time, through cooperation with the e- mail system of mobile phones. The granted points become the incentive compensation for the subjects. Three major characteristics of such a survey system are as follows: 1. It is possible to capture detailed migration behav- iors of subjects in a small area. 2. It is possible to revitalize the commercial activities in the target area by introducing (a) purchase incentives according to migration patterns and (b) advertising dis- tribution according to location. 3. Subjects will come to provide accurate behavior data to obtain these incentives. Although the investigator only unilaterally observed and surveyed the behaviors of subjects in conventional survey systems, the real- time collection and accumula- tion of behavior data of subjects who used such commu- nication functions enable interactive marketing analysis and make it possible to induce various life behaviors in a planned way by distributing information on the basis of the results of analysis. Figure 3 shows the overview and results of the social experiment on town- walking points. In this social exper- iment, an RFID tag–based survey system was imple- mented in a commercial mall in the urban center of the Matsuyama metropolitan area. A system was prepared by installing passive tag readers (with an effective range of 10 cm), which authenticate people who have put a card over a reader, and active tag readers (with an effec- tive range of a 50-m radius), which tell the locations of passage and personal IDs of passers without their cards being put over a reader, in several locations in a town. By using this system, more points were granted to peo- ple whose duration of stay was longer and who migrated to specific stores rather than having points uniformly assigned to people who have simply visited a commercial mall. A longer duration of stay in a commercial mall has a greater tendency of producing purchase behavior and revitalizing a town. In addition, an attempt was made to increase the number of visited stores and the number of purchases by granting more points to people who suc- cessively migrated to highly associated commercial facilities. The experiment was implemented for 1 month. The number of participants in the experiment was 260; the number of samples for only passive tags was 130; and the number of samples for active–passive tags was 130. Analysis of the results shows that the visit frequency to the city center was 1.5 times per week before the experi- ment was started, but it increased considerably to 2.5 times per week, on average, after the experiment began. Moreover, the duration of stay in the city center increased from 100 to 120 min, and the average pur- chase increased from 2,000 to 2,700 yen by the intro- duction of the incentives. The introduction of this system, called a town- walking point system, to shopping malls and similar locations will make possible analysis of the migration patterns specific to the commercial malls in real time and the design of the incentives. An important point is that the implementation of results of travel behavior analyses and behavior models that have conventionally been used in this field as an information system will directly help the revenue man- agement of commercial areas. Modeling of the reactions to incentives for each segment that are predicted by behavior models will enable the construction of an opti- mum online- type revenue management system. Further- more, the accumulation of such longitudinal behavior data on town walking, which are collected in real time, will lead to a better understanding of travel behavior, such as (a) the differences in duration of stay, purchased items, and purchase frequency between shoppers who have visited the central urban area by car and by public transportation and (b) the extent to which behaviors are related to daily activity patterns and their day- to- day perturbations. Example of Behavioral- Context Addressable Loggers in the Shell Both questionnaire surveys and the probe person survey, which is aided by GPS mobile phones and a web diary, can be said to be survey methods that try to obtain more accurate behavior data by requesting subjects to perform some kind of operation for recording. Such recording methods as completing questionnaire forms, responding to web questionnaires, pressing a button of a GPS at the time of departure, or putting a card incorporated with an RFID tag close to a reader at the time of arrival require the subjects themselves to perform an act of recording, and therefore these methods tend to result in 192 INNOVATIONS IN TRAVEL DEMAND MODELING, VOLUME 2

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TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 2: Papers includes the papers that were presented at a May 21-23, 2006, conference that examined advances in travel demand modeling, explored the opportunities and the challenges associated with the implementation of advanced travel models, and reviewed the skills and training necessary to apply new modeling techniques. TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 1: Session Summaries is available online.

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