This paper aims to estimate Vessel Collision Frequency in the Singapore Strait. This frequency is obtained as the product of the number of Vessel Conflicts and the causation probability using the real-time vessel movement data from the Lloyd's Marine Intelligence Unit (Lloyd's MIU) database. The results show that the container carriers have the highest Vessel Collision Frequency while Roll-On Roll-Off (RORO) and passenger ships have the lowest frequency. Tankers cause the highest head-on collision frequency. In the Singapore Strait, the most risky overtaking area is between longitudes 103°48′E and 104°12′E. The most risky head-on area is between longitudes 103°50′E and 104°00′E while the majority of crossing collisions occur between longitudes 103°50′E and 104°12′E. The Vessel Collision Frequency is found to be 1·75 per year in the traffic lanes. Currently, westbound traffic in the Strait is more risky than eastbound traffic (the number of westbound collisions in July was 0·0991 while the number of eastbound collisions was 0·0470). Furthermore, the estimated Vessel Collision Frequency during the day is less than that at night. The results of this paper could be beneficial for the Maritime and Port Authority of Singapore to further enhance the navigational safety strategies implemented in the Singapore Strait. K E Y

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Objective: This paper aims to assess the potential crash risks across different traffic lanes (shoulder lane, median lane, and middle lane) near to ramps (before on-ramps, between ramps, and after off-ramps). Methods: Field data are collected at seven locations (90 minutes for each location) during peak hours. Two risk indices based on time to collision, individual risk and societal risk are proposed to represent the distinct interpretations of risks to transport agencies and individual motorists. One-way ANOVA is applied to analyse the risk impact of ramps in various types of locations across distinct traffic lanes. Results: Median lanes and sections after off-ramps have relatively lower risks compared to other lanes and sections. The individual and societal risks might not always be consistent since the two risk indices are proposed based on distinct perspectives: transport agencies focus on the crash/conflict frequencies in a road section and individual motorists are more concerned about the probability of being involved in a crash/conflict during their journey. Conclusions: The differences in risks mainly result from the frequent lane-changing and merging activities. This model could be used to evaluate the performance of expressway ramp design.

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Using the classification and regression tree (CART) method, this study aims to model the vehicle merging behavior at work zone merging areas during the merging implementation period. Hereafter, the merging implementation period is defined as the period from the starting time to the completion time of a merging maneuver. From the safety perspective, the times to collision (TTC) between the merging vehicle and its neighboring vehicles are regarded as the factors affecting vehicle merging decisions. The results show that a larger delay, a shorter remaining distance to the work zone, a smaller TTC to the merging lead vehicle, and a higher merging vehicle speed may encourage drivers to complete merging maneuvers early. It is also found that the merging vehicle tends to continue merging when the TTCs between the merging vehicle and its neighboring vehicles in the through lane are too small. In addition, another CART model without the use of TTC is built for comparison. The finding indicates that the use of TTC can not only contribute to a perfect result but also highlight the merging safety situation more clearly. The merging rules of this study are ready to be incorporated into the merging assistance system for guiding a safety merging at work zone merging areas.Index Terms-Merging, classification and regression tree, timeto-collision, merging implementation period. 1524-9050

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