The rapid progress of information technology (IT) may provide us with new insights into understanding traffic phenomena, and could help mitigate traffic problems. One of the key applications of IT to traffic and transport analysis is the identification of the location of moving objects using the Global Positioning System (GPS). It is expected that detailed traffic analysis could be carried out using these data. In this article, we first summarize the various applications of probe data in transport analysis. GPS data are merely a sequence of locations, and further data transformation such as map-matching, data-reduction, processing, and reporting is needed to use them effectively. We then discuss the application of bus probe data to evaluating travel time variability and the level of service (LOS) of roads. A methodology for evaluating the road network from the viewpoint of travel time stability and reliability using busThe rapid progress of IT may provide us new insights into understanding traffic phenomena, and could help mitigate traffic problems. One of the key applications of IT to traffic and transport analysis is the identification of the location of moving objects using GPS. It is expected that detailed traffic analysis could be carried out using these data.GPS consists of a series of satellites that orbit the earth, broadcasting signals to receivers on the ground. A receiver can determine its location using data from at least four satellites. GPS was developed by the U.S. Department of Defense for military purposes, and was opened for public use in 1984. There are now 31 GPS satellites available. The performance of the GPS had, This research was supported by the Innovation and Integration of Technologies for a New Society project funded by the Japanese Ministry of Land, Infrastructure, and Management. We wish to thank the Institute of Systems Science Research and our former students, Yusuke Nagahiro and Yusuke Yamawaki, for supporting the analysis of bus probe data.Address correspondence to Nobuhiro Uno, Department of Urban Management, Kyoto University, Kyoto, Japan. E-mail: uno@trans.kuciv.kyotou.ac.jp in the past, been limited by artificial degradation of the signal through the process of selective availability (SA), but the US Government removed that on May 1, 2000. Ochieng and Sauer (2002) reported that the 74% of data are accurate within 10 m without SA, compared to only 24% with SA. Furthermore, no significant difference is apparent between the level of accuracy achievable with differential positioning and post-SA stand-alone navigation.Zito and colleagues (1995) were the first to address the use of GPS data for traffic engineering. They discussed the accuracy of the GPS and its potential for traffic analysis, and suggested that geographical information systems (GIS) could be used efficiently for managing the data obtained by the GPS. They demonstrated that, whenever possible, the direct GPS speed should be used because calculating a speed using the time between two locations gives poor results....

We analyzed the influence of road alignments such as sags and curves and the leading vehicle's behavior on carfollowing behavior in a driving simulator experiment. Parameters of a car-following model were estimated from following-vehicle trajectory data collected for 37 participants. Then, relationships between the parameters and environmental factors were analyzed. The results showed that the parameters of the following-behavior model were significantly influenced by expressway alignments such as sags and curves, whereas differences in the leading vehicle's behavior did not significantly affect the estimated parameters. These findings indicate that measures to assist the following vehicle's acceleration and deceleration such as adaptive cruise control could be effective in preventing the breakdown of traffic flow.

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Network reliability indices are generally expressed as a multiplier of the probability that the specific event may occur and the consequence of the event. It means that an inaccurate estimation of the probability of event occurrence may lead to different evaluation of the reliability. In contrast, the concept of "network vulnerability" has been proposed for evaluating the network component only by the consequence of the degradation. Though the concept of vulnerability may have avoided the uncertainty of the capacity degradation, it still requires an exact measurement of the traffic demand in the network which may not be accurate especially in the case of the disaster. We thus propose the method of critical link identification from the topological point of view, i.e., connectivity vulnerability. The concept of the k-edge-connectivity is applied in this study. The number of distinct paths with acceptable travel time between each origin-destination (OD) pair is used to measure the connectivity of that OD pair (similar to the concept of k-edge connectivity). A mathematical program for identifying acceptable distinct paths between each OD pair is formulated. The proposed method and indicator of connectivity vulnerability is then tested with the Kansai road network.

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