Correlations in Spatiotemporal Headway Dynamics of Road Traffic Using Extremely Accurate Microscopic Empirical Data

As we recently showed by using empirical data there is a certain behavior referring to the development of the headway between two consecutive human driven vehicles. Following on from this, we investigate correlations of the change in temporal headway over two subsequent road segments as the main goal of the present work and found a strongly correlated behaviour for increasing temporal headways. In this way a strong improvement for short-term prediction algorithms of conventional road users should be achieved. A stationary infrared-based sensor system was developed for this purpose, which has been mounted at reflector posts next to an urban street over a distance of about 50m. Due to its good accuracy, we are able to resolve vehicle following times down to 25 milliseconds and to determine speeds more precisely. In 45 hours of measurement the system detected over 20,000 passing vehicles

An Assessment of the Capacity Drops at the Bottleneck Segments: a Review on the Existing Methodologies

The term of capacity is very useful to quantify the ability of transport facilities in terms of carrying traffic. The capacity of the road is an essential ingredient in the planning, design, and operation of roadways. It is desirable for traffic analyst to be able to predict the time and places where congestion will occur and the volumes to be expected. Most of urbanized areas have been experiencing of traffic congestion problems particularly at urban arterial systems. High traffic demand and limited supply of roadways are always the main factors produced traffic congestion. However, there are other sources of local and temporal congestion, such as uncontrolled access point, median opening and on-street parking activities, which are caused a reduction of roadway capacity during peak operations. Those locations could result in reduction of travel speed and road, as known as hidden bottlenecks. This is bottleneck which is without any changes in geometric of the segments. The Indonesian Highway Capacity Manual (IHCM, 1997) is used to assess urban arterial systems till current days. IHCM provides a static method for examining the capacityand does not systematically take into account of bottleneck activities. However, bottleneck activities create interruption smooth traffic flow along arterial streets, which in turns stimulate related problems, such as, excessive air pollution, additional energy consumption and driver\u27s frustration due to traffic jammed. This condition could happen simultaneously; mostly repetitive and predictable in same peak hour demands. Therefore, this paper carefully summarize on the existing methodologies considering required data, handled data processing and expected output of each proposed of analysis. We further notice that dynamic approach could be more appropriated for analyzing temporal congestion segments (median opening, on street parking, etc.). Method of oblique cumulative plot seems to be more applicable in terms of convenient, surveying tool and the accuracy of analysis. This method is easy to handle and powerful in identifying flow and speed fluctuations during breakdown occur

Disruption analytics in urban metro systems with large-scale automated data

Urban metro systems are frequently affected by disruptions such as infrastructure malfunctions, rolling stock breakdowns and accidents. Such disruptions give rise to delays, congestion and inconvenience for public transport users, which in turn, lead to a wider range of negative impacts on the social economy and wellbeing. This PhD thesis aims to improve our understanding of disruption impacts and improve the ability of metro operators to detect and manage disruptions by using large-scale automated data. The crucial precondition of any disruption analytics is to have accurate information about the location, occurrence time, duration and propagation of disruptions. In pursuit of this goal, the thesis develops statistical models to detect disruptions via deviations in trains’ headways relative to their regular services. Our method is a unique contribution in the sense that it is based on automated vehicle location data (data-driven) and the probabilistic framework is effective to detect any type of service interruptions, including minor delays that last just a few minutes. As an important research outcome, the thesis delivers novel analyses of the propagation progress of disruptions along metro lines, thus enabling us to distinguish primary and secondary disruptions as well as recovery interventions performed by operators. The other part of the thesis provides new insights for quantifying disruption impacts and measuring metro vulnerability. One of our key messages is that in metro systems there are factors influencing both the occurrence of disruptions and their outcomes. With such confounding factors, we show that causal inference is a powerful tool to estimate unbiased impacts on passenger demand and journey time, which is also capable of quantifying the spatial-temporal propagation of disruption impacts within metro networks. The causal inference approaches are applied to empirical studies based on the Hong Kong Mass Transit Railway (MTR). Our conclusions can assist researchers and practitioners in two applications: (i) the evaluation of metro performance such as service reliability, system vulnerability and resilience, and (ii) the management of future disruptions.Open Acces

An assessment of The Capacity Drops at The Bottleneck Segments: A review on the existing methodologies

The term of capacity is very useful to quantify the ability of transport facilities in terms of carrying traffic. The capacity of the road is an essential ingredient in the planning, design, and operation of roadways. It is desirable for traffic analyst to be able to predict the time and places where congestion will occur and the volumes to be expected. Most of urbanized areas have been experiencing of traffic congestion problems particularly at urban arterial systems. High traffic demand and limited supply of roadways are always the main factors produced traffic congestion. However, there are other sources of local and temporal congestion, such as uncontrolled access point, median opening and on-street parking activities, which are caused a reduction of roadway capacity during peak operations. Those locations could result in reduction of travel speed and road, as known as hidden bottlenecks. This is bottleneck which is without any changes in geometric of the segments. The Indonesian Highway Capacity Manual (IHCM, 1997) is used to assess urban arterial systems till current days. IHCM provides a static method for examining the capacityand does not systematically take into account of bottleneck activities. However, bottleneck activities create interruption smooth traffic flow along arterial streets, which in turns stimulate related problems, such as, excessive air pollution, additional energy consumption and driver’s frustration due to traffic jammed. This condition could happen simultaneously; mostly repetitive and predictable in same peak hour demands. Therefore, this paper carefully summarize on the existing methodologies considering required data, handled data processing and expected output of each proposed of analysis. We further notice that dynamic approach could be more appropriated for analyzing temporal congestion segments (median opening, on street parking, etc.). Method of oblique cumulative plot seems to be more applicable in terms of convenient, surveying tool and the accuracy of analysis. This method is easy to handle and powerful in identifying flow and speed fluctuations during breakdown occur