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We study in this paper the structure of traffic under hypercongestion, which is a controversial issue between traditional two-phase traffic theory and Kerner's three-phase theory. By analyzing video traffic data from a section of ...
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We study in this paper the structure of traffic under hypercongestion, which is a controversial issue between traditional two-phase traffic theory and Kerner's three-phase theory. By analyzing video traffic data from a section of the Nanjing Airport Highway, it is found that traffic states inside hypercongestion are not homogeneous, which contradicts the existence of a "Homogeneous Congested Traffic" state claimed in two-phase traffic theory. Analysis of vehicle trajectories and velocities obtained from an experimental car-following study with a platoon of 25 vehicles also confirms the above findings. Furthermore, it is also found from the video traffic data that the structure of hypercongested traffic varies only slightly with location, which might be due to small jams inside hypercongested traffic merging into larger ones slowly and/or larger jams sometimes breaking into small ones. Finally, the implications of our observations on traffic modeling have been discussed. (C) 2015 Elsevier Ltd. All rights reserved.
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摘要 :
This paper investigates the optimization of traffic congestion sys-
tems via network congestion game approach. Firstly, using the semi-tensor
product(STP) of matrices, the matrix expression of network congestion game
is obtaine...
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This paper investigates the optimization of traffic congestion sys-
tems via network congestion game approach. Firstly, using the semi-tensor
product(STP) of matrices, the matrix expression of network congestion game
is obtained. Secondly, a necessary and sufficient condition is proposed to guar-
antee that the traffic systems can be transformed into network congestion game
with given performance criterion as its weighted potential function. Then an
algorithm is provided to design the trac congestion price in the case that
conversion can be established. Thirdly, by designing proper learning rule, the
optimization of traffic systems can be achieved when individuals optimize their
own utility function. Moreover, two special cases which make our results more
accord with reality and rich. Finally, an example is exploited to demonstrate
the e ectiveness of our obtained results.
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If we consider road traffic in urban areas, one of its major problems encountered nowadays is that of traffic congestion. The paper aims to provide an improvement, in terms of reducing traffic congestion, by analyzing different tr...
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If we consider road traffic in urban areas, one of its major problems encountered nowadays is that of traffic congestion. The paper aims to provide an improvement, in terms of reducing traffic congestion, by analyzing different traffic light cycles. A traffic light cycle is determined by the red and green duration of the traffic lights. Traditionally these two have a fixed duration and controlling road traffic can be achieved by modifying it, resulting in a congestion reduction. We present a comparison between the fixed and an improved fixed situation, as well as a QL algorithm to further reduce the congestion at an intersection. Urban traffic can thus be optimized, in terms of reducing congestion, on an existing traffic light system. A study case validates the results, based on road traffic data obtained from the city of Bucharest.
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Traffic congestion on major roads consequent upon existing bottlenecks at intersections is a major problem in Akure Metropolis. To change this trend, this research was carried out in order to design effective traffic control mecha...
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Traffic congestion on major roads consequent upon existing bottlenecks at intersections is a major problem in Akure Metropolis. To change this trend, this research was carried out in order to design effective traffic control mechanisms at the "troubled spots" in the metropolis. Odole intersection was identified as one of the critical intersections during a reconnaissance survey and as such, selected for study. Data on geometric features were collected using Oedometer and Google Earth software. Peak and off-peak traffic volume data were collected between 7:30 and 8:30 am and between 12.00 noon and 1.00 pm respectively every other day using Cine camera. Furthermore, discharge headway and delay data were collected using stop watch. The geometric and traffic data collected were analysed using Microsoft Excel. An appraisal of Odole Intersection indicated that the major contributors to traffic are Motorcycles (70.88%) and Passenger Cars (28.72%). Other modes of transportation account for about 0.4% of vehicles traversing the intersection. The critical traffic volume at the intersection was over 4000 veh/hr and the average delay was 22 seconds. An Average delay of 22 seconds at the intersection was an indication that the operating level of service was C (i.e. fairly stable traffic condition with average delays attributable to traffic control by personnel). By juxtaposing the results of geometric and traffic data analyses with the pros and cons of various traffic control mechanisms, traffic control by signalisation was selected and designed to suit Odole intersection. In tandem with the results of this research, appropriate measures have been recommended to ameliorate traffic and commuting problems in the metropolis.
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Ramp-metering, which controls the onramp flow into the freeway, is successful in increasing freeway throughput and reducing overall travel-time. The maximum flow allowed from the onramp during ramp-metering is typically estimated ...
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Ramp-metering, which controls the onramp flow into the freeway, is successful in increasing freeway throughput and reducing overall travel-time. The maximum flow allowed from the onramp during ramp-metering is typically estimated so that the sum of flows from the onramp and mainline do not exceed a predetermined threshold (either the capacity of the downstream section or a threshold based on occupancy at capacity). Recent research has shown that this threshold is probabilistic and the transition from noncongested to congested conditions (i.e., breakdown) occurs stochastically. Also, research has shown that the contribution of the ramp and freeway demands on breakdown is different; 100 additional vehicles arriving from the ramp increase the probability of breakdown more than 100 additional vehicles from the freeway. This fluctuation has been studied through the development of breakdown probability models, which provide the probability of breakdown as a function of the combination of the mainline and ramp flows. The writers' objective was to develop suitable site-specific probability of breakdown models and use them within existing ramp-metering algorithms to evaluate their ability to postpone the breakdown and reduce congestion at freeway facilities with recurring congestion. The writers first develop a process for obtaining breakdown-probability models for existing critical ramps (i.e., those where breakdown starts). Next, the writers propose specific enhancements to existing ramp-metering algorithms that incorporate probability-of-breakdown models. Proposed enhancements are presented for two algorithms, as follows: (1) the Minnesota stratified ramp-metering algorithm (SZM), and (2) the Ontario COMPASS algorithm. Simulation was used to replicate these algorithms and evaluate the proposed enhancements. The results of these experiments showed that the enhancements are effective in postponing congestion at the two sites by 17-35 min.
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To better understand the characteristics of traffic congestion and efficiently employ congestion measures for interstate highway systems, this study examined the limitations of the congestion measures currently in use such as the ...
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To better understand the characteristics of traffic congestion and efficiently employ congestion measures for interstate highway systems, this study examined the limitations of the congestion measures currently in use such as the percent of congestion and the duration of continuous congestion. Based on this study, these congestion measures provided different results of the congestion severity for even the same interstate highway segment, which means that the use of a single measure might not give a reliable evaluation result. In order to minimize the potential bias and enhance the advantage of each congestion measure, this study proposed a composite congestion severity measure by combining congestion information of both percent of congestion and duration of continuous congestion measures. The writers found that the proposed composite congestion severity measure efficiently identified the levels of the congestion severity of interstate highway segments and that it could be instantly accomplished with the existing loop detector count systems in most states. This proposed measure may be a potential candidate for describing levels of congestion severity and can provide a proper guideline for transportation engineers or decision makers to efficiently allocate available budget and resources to correct applicable interstate segments.
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Traffic congestion is getting worse and has resulted in increased travel delays and costs. In order to develop effective intelligent transportation systems (ITS) strategies to mitigate traffic congestion on freeways, a good unders...
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Traffic congestion is getting worse and has resulted in increased travel delays and costs. In order to develop effective intelligent transportation systems (ITS) strategies to mitigate traffic congestion on freeways, a good understanding of its causes and impacts is vital but has not been achieved at a satisfactory level. Over the past several decades, deterministic queuing theory (DQT) has been widely used to evaluate freeway travel delays resulted from traffic congestion. However, several studies evaluated the accuracy of its delay estimates and claimed that the DQT method consistently underestimates vehicle delays. The reason for the underestimation, however, had not been clearly identified. This study aims at exploring the main cause of such underestimation problems and proposing a solution to fix it. Based on theoretical analysis and empirical justification, it was found the underestimation resulted primarily from the inappropriate estimates of the time offsets, that is, the travel times between the queue starting point and the immediate upstream and downstream traffic sensor locations. To address this issue, a microscopic approach was developed and implemented in a computer application to enhance the time offset estimation. This proposed approach was tested using the real vehicle delay data manually extracted from traffic surveillance video cameras. The test results indicated that the improved DQT-based vehicle delay estimates with appropriate time offset settings were very close to the ground-truth data. The underestimation problem associated with the traditional DQT method can be effectively addressed and fairly accurate estimates of vehicle delay can be achieved by the proposed method.
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The nature of congested traffic flow has been not fully understood until now. An isolated bottleneck on the expressway generally influences a limited segment length, which means attenuation effects of the bottleneck on traffic str...
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The nature of congested traffic flow has been not fully understood until now. An isolated bottleneck on the expressway generally influences a limited segment length, which means attenuation effects of the bottleneck on traffic stream by a distance within the influence area. However, such effects of bottleneck on speed-flow relationship have been inadequately emphasized. This paper investigates the location effects of a bottleneck on the speed-flow relationship. With consecutive 5 weekday median lane data collected by dual loop detectors on a congested expressway in Shanghai, integral speed-flow relationships including upper limb, lower limb, and capacity area are obtained from six sites. Further analyzing those sites on the same basic expressway segment unveils that it is the movement of the upper limb and lower limb that produces the integral curve. The right end of the upper limb gets an increase speed in with the site farther to its upstream bottleneck, whereas the lower limb gets a drop in speed with the site closer to its downstream bottleneck. Such a movement feature is in agreement with general driving behaviors of discharging or approaching a bottleneck. The factors intensifying or weakening the movement tendency are also identified.
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There are many traffic information services that provide realtime road speed for road users to inquire, informing them whether the traffic is in congested status or not. However, it is not enough to provide only current informatio...
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There are many traffic information services that provide realtime road speed for road users to inquire, informing them whether the traffic is in congested status or not. However, it is not enough to provide only current information in many circumstances. We believe that the convenience of traffic information for road users can be improved by providing prediction results. Our research aims at collecting and analyzing traffic data through statistical method and raising architectures for congestion detection and prediction. With the history trend of each road, it is possible to foresee appearances and durations of incoming congestions. Validated by historical data, the measurement of accuracy shows that over 94% of congestion can be predicted properly. It also revealed that the MAE(Mean Absolute Error) and MAPE(Mean Absolute Percentage Error) of proposed method outperform the results generated by simple average method.
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This paper presents a fuzzy-based methodology for quantification of congestion level for traffic control on expressways using traffic flow speed and density. Inductive loop detector data on the Interstate 880 obtained through the ...
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This paper presents a fuzzy-based methodology for quantification of congestion level for traffic control on expressways using traffic flow speed and density. Inductive loop detector data on the Interstate 880 obtained through the Freeway Performance Measurement System were used to estimate congestion levels following the fuzzy logic approach. In comparison with the Highway Capacity Manual, the results generally show a good correspondence. However, unlike the Highway Capacity Manual that defines step-wise measurement of levels of service based entirely on density, the proposed fuzzy inference system allows a flexible combination between speed and density to provide a more detailed indication of congestion intensity to describe the gradual transition of traffic state. For comparison, the congestion indices evaluated with both density and speed were compared to those evaluated with either speed or density using the same data set. Results from this comparative study reinforce the statements from previous studies that expressway speed is conservative under free-flow and light traffic conditions, but decreases significantly just before the flow rate approaches the road capacity. The results also show significant differences between the congestion indices evaluated using a single quantity, while the congestion indices using both density and speed tend to neutralize in between and scale up in a stable manner with the levels of service. Considering the abstract nature of congestion terminology, it is necessary to quantity traffic congestion on the expressways using both variables to minimize the potential bias in representing the operation of expressway traffic properly, which is particularly important under heavy congested conditions. (C) 2021 Elsevier B.V. All rights reserved.
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