Young-Ihn Lee

Spatial regression analysis of traffic crashes in Seoul

Traffic crashes can be spatially correlated events and the analysis of the distribution of traffic crash frequency requires evaluation of parameters that reflect spatial properties and correlation. Typically this spatial aspect of crash data is not used in everyday practice by planning agencies and this contributes to a gap between research and practice. A database of traffic crashes in Seoul, Korea, in 2010 was developed at the traffic analysis zone (TAZ) level with a number of GIS developed spatial variables. Practical spatial models using available software were estimated. The spatial error model was determined to be better than the spatial lag model and an ordinary least squares baseline regression. A geographically weighted regression model provided useful insights about localization of effects. The results found that an increased length of roads with speed limit below 30 km/h and a higher ratio of residents below age of 15 were correlated with lower traffic crash frequency, while a higher ratio of residents who moved to the TAZ, more vehicle-kilometers traveled, and a greater number of access points with speed limit difference between side roads and mainline above 30 km/h all increased the number of traffic crashes. This suggests, for example, that better control or design for merging lower speed roads with higher speed roads is important. A key result is that the length of bus-only center lanes had the largest effect on increasing traffic crashes. This is important as bus-only center lanes with bus stop islands have been increasingly used to improve transit times. Hence the potential negative safety impacts of such systems need to be studied further and mitigated through improved design of pedestrian access to center bus stop islands.

A Fusion Priority Signal Control Algorithm for Emergency Vehicles

본 연구에서는 긴급상황 시 긴급차량의 무정차 통과를 위해 융합형 우선신호 제어 알고리즘을 개발하였다. 융합형 우선신호는 센터제어와 현장제어를 결합한 방법이다. 센터제어는 긴급상황이 접수되면 긴급차량 경로의 각 교차로에 대하여 우선신호를 적용한다. 긴급차량 출발이전에 신호시간을 제어하기 때문에 대기차량...

A Passive Traffic Signal Priority Control Algorithm for Emergency Vehicles

본 연구에서는 긴급차량 우선신호 센터제어 알고리즘을 개발하였다. 센터제어는 긴급차량 출동 요청이 접수되면 긴급차량 경로의 각 교차로에 대하여 신호시간을 산출 및 적용한다. 긴급차량 출발 이전에 신호시간을 제어하기 때문에 대기차량을 보다 효과적으로 소거할 수 있다. 대부분의 기존 연구에서는 긴급차량 도착 ...

Short-term Speed Prediction Models for Time Dependent Shortest Path Algorithms in Car Navigation Systems

The objective of this study is the development of the short-term prediction models to predict average spot speeds of the subject location in the short-term periods of 5, 10 and 15 minutes respectively. In this study, field data were used to see the comparison of the predictability of each model. These field data were collected from image processing detectors at the urban expressway for 17 hours including both peak and non-peak hours. Most of the results were reliable, but the results of models using Kalman Filtering and Neural Networks are more accurate and realistic than those of the others.

A Dynamic Shortest Path Algorithm Using Multi-Step Ahead Link Travel Time Prediction

Route guidance systems provide motorists with step-by-step instructions on how to get from any origin to any destination in a network. The systems calculate the best route from a user-supplied origin to destination, based on each link travel time on the network. Most studies on the route guidance development have been carried out based on only one-step ahead prediction of the link travel time in order to calculate a dynamic shortest path. However, the multi-step ahead prediction process should be considered in order to represent realistically the time-varying traffic conditions of the upstream links on the dynamic time interval basis. In this paper, a multi-step ahead prediction algorithm of link travel speeds has been developed using a Kalman filtering technique in order to calculate a dynamic shortest path. The one-step and the multi-step ahead link travel time prediction models for the calculation of the dynamic shortest path have been applied to the directed test network that is composed of 16 nodes: 3 entrance nodes, 2 exit nodes and 11 internal nodes. Time-varying traffic conditions such as flows and travel time data for the test network have been generated using the CORSIM model. The results show that the multi-step ahead algorithm is compared more favorably for searching the dynamic shortest time path than the other algorithm.