The recent increase in demand for performance-driven and outcome-based transportation planning makes accurate and reliable performance measures essential. Vehicle miles traveled (VMT), the total miles traveled by all vehicles on roadways, has been utilized widely as a proxy for traffic impact assessment, vehicle emissions, gasoline consumption, and crashes. Accordingly, a number of studies estimate VMT using diverse data sources. This study estimates VMT in the urban area of Bucheon, South Korea, by predicting the annual average daily traffic for unmeasured locations using spatial interpolation techniques (i.e., regression kriging and linear regression). The predictive performance of this method is compared with that of the existing Highway Performance Monitoring System (HPMS) method. The results show that regression kriging could provide more accurate VMT estimates than the HPMS method and linear regression, especially with a small sample size. additional control variables. Pathomsiri et al. [16] develop an econometric model for estimating VMT in multivehicle households and apply it to the 2001 National Household Transportation Survey. Erlbaum [17] applied the fuel-sales-based method to estimate VMT. White [18] and Greene [19] used odometer reading data to estimate annual VMT by driver. However, the previously mentioned methods, based on household activity surveys, fuel sales, and odometer reading data, are too resource-intensive and costly to perform regularly. Also, these methods reflect personal travel and do not reflect the total number of vehicles on the road.Traffic-count-based VMT estimation methods are currently the most commonly performed and preferred method because they are based on actual data for vehicle movement [20]. The predictive accuracy of traffic-count-based methods depends on the quality and coverage of traffic count data, given that the length of all road network sections is known. Thus, it can be said that if traffic counts were available for all roads in a network, the VMT estimate would be the most accurate measure of vehicle movement. Traffic counts are, however, only available at segments of road networks where there is a count station because of the relatively high cost of the stations. For urban areas, traffic count data are collected less frequently than in other areas because of the complexity of measurement [21]. For this reason, the Highway Performance Monitoring System (HPMS) method of VMT estimation, a representative traffic-count-based method performed in the USA, simply extrapolates the VMT of a sample section into other sections, so long as the other sections are in the same strata of traffic volume group and road functional system [20]. Despite the advantages of being a relatively simple and quick procedure, the HPMS method has been criticized by its accuracy and sample size demand needed to achieve the required precision level. Moreover, stratification of sampling by traffic volume group requires knowledge of the traffic count information on all roads [14]. A number of rec...
In this study, tour-based travel demand models were developed to describe the travel pattern of courier vehicles; the models overcome the limitations of four-step freight demand modeling. This study used a microsimulation-based modeling framework. The study area, Seoul, South Korea, was divided into block-based smaller traffic analysis zones, and the travel data from real-world courier service companies were used for model development and validation. The developed tour-based urban freight demand models were composed of eight steps: tour start, departure time choice, next-stop destination choice, vehicle movement, stop duration, next-stop purpose choice, return, and tour termination. After specific models were developed for each of the eight modules, the proposed modeling framework was applied, and the results were compared with the data observed in regard to average trip distance, trip length distribution, accuracy, sensitivity, specificity, number of stops, and average travel distance of the tours. Overall, results of the proposed models were reasonable from the perspective of urban freight demand modeling.
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