PURPOSES : This study aims to develop an algorithm to solve the user equilibrium traffic assignment problem using soft link capacity constraints. This model is used to relax the hard capacity constraints model. METHODS : In the traffic assignment model that imposes the hard capacity constraints, the well-known solution algorithms used are the augmented Lagrange multiplier method and the inner penalty function method. The major drawback of using the hard-capacity constraint model is the feasible solution issue. If the capacities in the network are not sufficient to absorb the flow from the diverged flows through the hard capacity constraints, it might result in no solution; whereas, using a soft capacity constraint model guarantees a feasible solution because the soft capacity constraint model uses the penalization of constraint violation in the objective function. In this study, the gradient projection (GP) algorithm was adapted. RESULTS : Two numerical experiments were conducted to demonstrate the features of the soft capacity constraint model and the computational performance of the solution algorithm. The results revealed that imposing the soft link capacity constraints can ensure convergence. CONCLUSIONS : The proposed model can be easily extended by considering other traffic assignment models, for e.g., non-additive traffic equilibrium problem, stochastic traffic equilibrium model, and, elastic demand traffic equilibrium problem. Furthermore, the model can exist regardless of the sufficient capacity for each O-D pair to cater to their demands.

PURPOSES: This study analyzes the characteristics of traffic flow on freeway sections under daytime and nighttime conditions to improve traffic safety, and suggests a method to estimate an accurate freeway capacity value that reflects these characteristics. METHODS : The trends and differences in capacity were investigated using comprehensive field data collected under both daytime and nighttime conditions on freeway sections with designated speeds of 80, 100, and 120 kph. RESULTS : The capacity values under nighttime driving conditions were reduced by 3.3%, 6.9%, and 8.8% at 80, 100, and 120 kph, respectively. Several nighttime adjustment factors were deduced for each designated speed category from the analysis results. CONCLUSIONS : It is expected that more accurate capacity values can be estimated for freeway sections under nighttime conditions by applying the resulting adjustment factors. In addition, traffic safety will be improved through the increased efficiency of traffic management on these freeway sections.

PURPOSES: This study analyzes the available working time at work-zone on the Expressway in accordance to the new capacity manual. METHODS: Sensitivity analysis on variables were conducted to calculate the adjusted capacity at work-zone based on previous researches. RESULTS : The main factors which affect available working time at the work-zone were its capacity, number of lanes, terrain and lane width. Other factors have minimal effect on the available working time. Based on the analysis, a calendar of lane closures was suggested. CONCLUSIONS : A series of studies concluded that the capacity at work-zone in the new capacity manual reduced to 76-82% of the existing manual. As such, the available working time decreased. Furthermore, the factors affecting the available working time needs to be considered when making a plan to rehabilitate the distressed pavement.

본 연구의 목적은 차종별 교통류 모형을 이용한 편도 2차로 고속도로 공사구간의 용량 값을 산정하는 것이다. 공사구간의 교통류 모형은 공사구간의 유입부 및 유출부를 대상으로 차종별 모형과 승용차 환산계수를 적용한 전체 차량에 대한 모형으로 도출하였다. 차종별 모형에서 산정된 최대교통류율은 승용차환산계수 및 중차량 비율을 적용하여 공사구간의 용량 값으로 전환하였다. 차종별 모형의 유입부 및 유출부 최대교통류율 값은 각각 1,845pcphpl과 1,884pcphpl로 산정되었으며 차량 전체를 대상으로 한 모형의 최대교통류율은 차종별 결과보다 높게 분석되었다. 모형의 비교 검증을 위하여 최대밀도에 따른 거리 차두간격을 적용하였다. 공사구간의 용량은 공사구간의 흐름이 안정된 유출부 용량보다 공사구간 진입을 위한 차선 변경 등으로 교통흐름이 원활하지 못한 유입부 용량에 좌우되므로 유입부 교통류 모형의 최대교통류율 값인 1,800pcphpl을 편도 2차로 고속도로 공사구간 용량 값으로 산정하였다.