PURPOSES: The density in uninterrupted traffic flow facilities plays an important role in representing the current status of traffic flow. For example, the density is used for the primary measures of effectiveness in the capacity analysis for freeway facilities. Therefore, the estimation of density has been a long and tough task for traffic engineers for a long time. This study was initiated to evaluate the performance of density values that were estimated using VDS data and two traditional methods, including a method using traffic flow theory and another method using occupancy by comparing the density values estimated using vehicular trajectory data generated from a radar detector. METHODS: In this study, a radar detector which can generate very accurate vehicular trajectory within the range of 250 m on the Joongbu expressway near to Dongseoul tollgate, where two VDS were already installed. The first task was to estimate densities using different data and methods. Thus, the density values were estimated using two traditional methods and the VDS data on the Joongbu expressway. The density values were compared with those estimated using the vehicular trajectory data in order to evaluate the quality of density estimation. Then, the relationship between the space mean speed and density were drawn using two sets of densities and speeds based on the VDS data and one set of those using the radar detector data. CONCLUSIONS: As a result, the three sets of density showed minor differences when the density values were under 20 vehicles per km per lane. However, as the density values become greater than 20 vehicles per km per lane, the three methods showed a significant difference among on another. The density using the vehicular trajectory data showed the lowest values in general. Based on the in-depth study, it was found out that the space mean speed plays a critical role in the calculation of density. The speed estimated from the VDS data was higher than that from the radar detector. In order to validate the difference in the speed data, the traffic flow models using the relationships between the space mean speed and the density were carefully examined in this study. Conclusively, the traffic flow models generated using the radar data seems to be more realistic.

PURPOSES: This study was initiated to analyze the characteristics of bus traffic accidents, by bus types, using the decision tree in order to establish customized safety alternatives by bus types, including the intra-city bus, rural area bus, and inter-city bus. METHODS: In this study, the major elements involved in bus traffic accidents were identified using decision trees and CHAID algorithm. The decision tree was used to identify the characteristics of major elements influencing bus traffic accidents. In addition, the CHAID algorithm was applied to branch the decision trees. RESULTS : The number of casualties and severe injuries are high in bus accidents involving pedestrians, bicycles, motorcycles, etc. In the case of light injury caused by bus accidents, different results are found. In the case of intra-city bus accidents, the probability of light injury is of 77.2% when boarding a non-owned car and breaching of duty to drive safely are involved. In the case of rural area bus accidents, the elements showing the highest probability of light injury are boarding an owned car, vehicle-to-vehicle accidents, and breaching of duty to drive safely. In the case of intra-city bus accidents, boarding owned car, streets, and vehicle-to-vehicle accidents work as the critical elements. CONCLUSIONS: In this study, the bus accident data were categorized by bus types, and then the influential elements were identified using decision trees. As a result, the characteristics of bus accidents were found to be different depending on bus types. The findings in this study are expected to be utilized in establishing effective alternatives to reduce bus accidents.

PURPOSES : Expressways experience chronic and recurring congestion, especially during weekends and holidays, because of the increased demands for leisure-related travel. The alternatives to solve chronic and recurring congestion may be three-fold: (1) physical expansion of expressway capacities, (2) road pricing, and (3) temporal and spatial distribution of traffic demands. Among these, the third alternative may be the most cost-effective method for the Korea Expressway Corporation (KEC) that can be achieved by using the existing ITS infrastructure. METHODS : KEC initiated a pilot study in which the traffic on congested expressways was managed by providing traffic condition information (i.e., travel times) of neighboring national highways for taking detours via variable message signs (VMS). This study aimed to estimate the detour rate, and the two pilot studies on Seohaean and Yeongdong expressways yielded many benefits. RESULTS: It was revealed that the total length of congestion segments decreased by 7.8 km, and the average travel speed increased by 5.3 km/h. CONCLUSIONS: Based on these findings, it was concluded that the propagation of detour information via VMSs during congestion hours can help reduce congestion on expressways and increase the benefits of the entire network.

PURPOSES : The control delay in seconds per vehicle is the most important traffic operational index to evaluate the level of service of signalized intersections. Thus, it is very critical to calculate accurate control delay because it is used as a basic quantitative evidence for decision makings regarding to investments on traffic facilities. The control delay consists of time-in-queue delay, acceleration delay, and deceleration delay so that it is technically difficult to directly measure it from fields. Thus, diverse analysis tools, including CORSIM, SYNCHRO, T7F, VISTRO, etc. have been utilized so far. However, each analysis tool may use a unique methodology in calculating control delays. Therefore, the estimated values of control delays may be different by the selection of an analysis tool, which has provided difficulties to traffic engineers in making solid judgments. METHODS: This study was initiated to verify the feasibility of diverse analysis tools, including HCM methodology, CORSIM, SYNCHRO, T7F, VISTRO, in calculating control delays by comparing estimated control delays with that measured from a field. RESULTS : As a result, the selected tools produced quite different values of control delay. In addition, the control delay value estimated using a calibrated CORSIM model was closest to that measured from the field. CONCLUSIONS: First, through the in-depth experiment, it was explicitly verified that the estimated values of control delay may depend on the selection of an analysis tool. Second, among the diverse tools, the value of control delay estimated using the calibrated microscopic traffic simulation model was most close to that measured from the field. Conclusively, analysts should take into account the variability of control delay values according to the selection of a tool in the case of signalized intersection analysis.

PURPOSES: Because expressway ramps are very complex segments where diverse roadway design elements dynamically change within relatively short length, drivers on ramps are required to drive their cars carefully for safety. Especially, ramps on expressways are designed to guarantee driving at high speed so that the risk and severity of traffic accidents on expressway ramps may be higher and more deadly than other facilities on expressways. Safe deceleration maneuvers are required on off-ramps, whereas safe acceleration maneuvers are necessary on onramps. This difference in required maneuvers may contribute to dissimilar patterns and severity of traffic accidents by ramp types. Therefore, this study was aimed at developing prediction models of the severity of traffic accidents on expressway on- and off-ramps separately in order to consider dissimilar patterns and severity of traffic accidents according to types of ramps. METHODS: Four-year-long traffic accident data between 2007 and 2010 were utilized to distinguish contributing design elements in conjunction with AADT and ramp length. The prediction models were built using the negative binomial regression model consisting of the severity of traffic accident as a dependent variable and contributing design elements as in independent variables. RESULTS: The developed regression models were evaluated using the traffic accident data of the ramps which was not used in building the models by comparing actual and estimated severity of traffic accidents. Conclusively, the average prediction error rates of on-ramps and offramps were 30.5% and 30.8% respectively. CONCLUSIONS: The prediction models for the severity of traffic accidents on expressway on- and off-ramps will be useful in enhancing the safety on expressway ramps as well as developing design guidelines for expressway ramps.