Reducing the effects of cross traffic in packet-pair based bottleneck capacity measurements

The current geometric design guide provides a methodology to analyze intersection sight distance for right-turning vehicles at signalized and two-way stop-controlled intersections based on the gaps accepted by the majority of drivers as measured from the field. That methodology is based mainly on driver behavior without considering the actual capabilities of the turning vehicle when accelerating from rest to the speed of the cross-traffic stream. This paper introduced the new design gap concept, which was based on the actual distance and time needed for the turning vehicle to accelerate to the same speed of the cross-traffic stream to avoid a collision. The acceleration capabilities of the turning vehicle were based on field measurements collected by GPS data logger devices that recorded the positions and instantaneous speeds of different turning vehicles at 1-s intervals; based on that, regression models were developed to establish an acceleration profile for a typical vehicle turning to the right from rest. Design tables were provided to help road designers select appropriate design gaps needed for different design speeds and grades of the crossing roadways. In comparison to the new design gaps, the measured gaps used in design were found to be generally inadequate. After implementation of the newly developed design gaps, turning drivers will potentially be able to accelerate comfortably without forcing other drivers in the cross-traffic stream to reduce their speeds or to change lanes to avoid colliding with turning vehicles.

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Study on the morning peak commuting problem with variable bottleneck capacity under the restriction measures of Metro passenger flow

10.1117/12.2619590 ◽

2021 ◽

Author(s):

Zhuo Shi

Keyword(s):

Passenger Flow ◽

Morning Peak ◽

Commuting Problem ◽

Bottleneck Capacity

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Using AIS Data for Navigational Risk Assessment in Restricted Waters

Advances in Environmental Engineering and Green Technologies - Marine Technology and Sustainable Development ◽

10.4018/978-1-4666-4317-8.ch015 ◽

2013 ◽

pp. 245-254

Author(s):

Adi Maimun ◽

Istaz F. Nursyirman ◽

Ang Yit Sian ◽

Rahimuddin Samad ◽

Sulaiman Oladokun

Keyword(s):

Risk Assessment ◽

Traffic Flow ◽

Assessment Method ◽

Collision Probability ◽

Traffic Density ◽

Automatic Identification ◽

High Concentration ◽

Marine Traffic ◽

Cross Traffic ◽

Strait Of Malacca

The Strait of Malacca is one of the most important shipping lanes in the world. It averages 150 ship passes a day and more than 50,000 ships annually. With a high concentration of vessels in a narrow path, multiple risk situations arise. Analyzing traffic density is made harder by cross traffic and an unknown traffic density at the Strait. In 2009, Universiti Teknologi Malaysia (UTM), through a collaboration with Kobe University, successfully installed an Automatic Identification System (AIS) receiver. Through the AIS receiver, data of ship movements in the Strait of Malacca and Singapore could be recorded. A program was established by UTM to retrieve the data for the purpose of marine traffic collision risk analysis. In this research, a risk assessment method using AIS data is proposed for restricted waters such as for the Strait of Malacca and Singapore. The Risk Assessment Methodology requires the estimation of collision probabilities. The collision probability of the proposed method considers the Traffic Density, directions of traffic flow (with respect to a subject vessel), and probability of navigational failure. An area in the Strait of Singapore between the latitudes of 1°13’N and 1°07’N and Longitudes of 103°4’E and 103°56’E was selected to illustrate the method. By analysing the AIS data of traffic flow, the probabilities of collision for the area were determined. The effect of vessel parameters of length and speed on the risks of collision are also shown.

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General Identifiability Condition for Network Topology Monitoring with Network Tomography

Sensors ◽

10.3390/s19194125 ◽

2019 ◽

Vol 19 (19) ◽

pp. 4125 ◽

Cited By ~ 1

Author(s):

Shengli Pan ◽

Zongwang Zhang ◽

Zhiyong Zhang ◽

Deze Zeng ◽

Rui Xu ◽

...

Keyword(s):

Network Topology ◽

Network Monitoring ◽

Time Varying ◽

Network Tomography ◽

Accurate Knowledge ◽

Cross Traffic ◽

End To End ◽

The Cross

Accurate knowledge of network topology is vital for network monitoring and management. Network tomography can probe the underlying topologies of the intervening networks solely by sending and receiving packets between end hosts: the performance correlations of the end-to-end paths between each pair of end hosts can be mapped to the lengths of their shared paths, which could be further used to identify the interior nodes and links. However, such performance correlations are usually heavily affected by the time-varying cross-traffic, making it hard to keep the estimated lengths consistent during different measurement periods, i.e., once inconsistent measurements are collected, a biased inference of the network topology then will be yielded. In this paper, we prove conditions under which it is sufficient to identify the network topology accurately against the time-varying cross-traffic. Our insight is that even though the estimated length of the shared path between two paths might be “zoomed in or out” by the cross-traffic, the network topology can still be recovered faithfully as long as we obtain the relative lengths of the shared paths between any three paths accurately.

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