부산대학교 도서관

Many agencies are exploring the use of probe-based traffic monitoring systems to collect information on system performance. Although these systems offer the potential of directly measuring travel times and of significantly reducing the cost per mile of traffic monitoring systems, the issue of identifying the number of samples required to produce reliable and accurate condition information has not been adequately examined. Most existing research into this issue addresses the problem from a very broad perspective, offering a single percentage of vehicles in an area that must be equipped as probes to provide good coverage of the area. This approach ignores variations in flow conditions through time and across different links of the network. The described research addresses the issue of sample sizes for different links and measurement intervals from a rigorous statistical perspective. First, the issue of producing sample sizes on the basis of the central limit theorem (CLT) is empirically examined by using Virginia freeway speed data to assess this method's validity even when the underlying speed population is nonnormal. Applying the CLT to the speed data shows that fluctuations in flow conditions over time and across different locations require varying sample sizes, which the static sample sizes proposed in previous research do not take into account. Finally, the CLT-based sample sizes are compared with a representative static sample size proposed in the literature to illustrate how the CLT method can reduce sample sizes while maintaining the desired confidence and accuracy levels.