Queue Length Before and After Conversion of a Conventional Intersection into an Alternative Intersection

This paper presents a traffic operational comparison of seven new alternative signalized intersection designs with three critical phases: 1) offset thru-cut, 2) thru-cut, 3) seven-phase, 4) redirect left and through from one minor road (redirect L&T), 5) reverse reduced conflict intersection (reverse RCI), and 6) and 7) two new versions of partial median U-turn (MUT) intersection. These designs will also be compared with the four-phase conventional intersection and two alternatives with two-phase traffic signals: full MUT and reduced conflict intersection (RCI) designs under various traffic conditions at near-capacity levels. Overall, 1,800 simulation runs were conducted to estimate traffic operations under different traffic conditions with varying traffic volumes, traffic distributions, and turning traffic ratios. Traffic signals were optimized for all the tests, and the optimized signal data was imported into microsimulation to evaluate the performance of the 10 intersections included. According to the results, four of the three-phase intersection designs (offset thru-cut, thru-cut, MUT #1, and reverse RCI) could result in significantly shorter travel times than the conventional intersection. The traffic operations of these four intersection designs were found to be similar to the two-phase designs and even better than the full MUT in scenarios with high turning traffic ratios. The other three intersection designs (seven-phase, redirect L&T, and MUT #2) also showed potential as possible substitutes for existing four-phase intersections under conditions with higher turning traffic demands.

Input-queued scheduling algorithms are designed to improve the throughput which use the input and output terminal in the router to obtain the maximum packets. And the length of the input queue is an important target, that can decides the superiority-inferiority about the capability of the input algorithm. With the existing algorithms, the main content about the scheduling algorithm are ensuring the packets’ high priority and low level. But most of these algorithms do not consider the length of queue. In this paper, we consider the change of queue length when the packets enter the input channel at the router, and put forward a shortest queue time-slot adapting algorithm (SQTA algorithm). First of all, SQTA algorithm can base the changes of transmittion time to control the packets’ sending time interval, and this action can make SQTA algorithm match the processing power about the router, and at the same time, this algorithm can reduce the length of the packets queue. Second, SQTA algorithm can control of a phenomenon that the packets may overflow when the length of queue is full, and that also make the packets transmitted more stable in network. The experimental result shows that this scheduling algorithm can control the length of queue effectively and reduce the waiting time with packets queue, It can be shorten the remaining service time, and can improve the network operation obviously.

Real time queue length estimation for signalized intersections using travel times from mobile sensors

Roundabouts are classified as alternative intersection forms because they provide operational conditions not found at conventional intersections (e.g., a low-speed environment and fewer possible vehicle conflicts). Such conditions provide a combination of safety and operational benefit that normally is not achievable at a conventional intersection. The ability to predict capacity accurately is important when alternative intersection designs are examined. Highway Capacity Manual 2010 provides a current method for determining the capacity of a roundabout approach in which vehicles that exit on the same approach are considered not to influence capacity. However, the inclusion of exiting vehicles in the model creates a different circulating vehicle gap distribution (dividing larger gaps into smaller gaps) that reduces the number of opportunities to measure follow-up headway. Also, most critical headway values for the analysis are smaller than the critical headway values found when exiting vehicles are excluded. Capacity equations were developed from video imagery recorded for 28 approaches at 13 roundabouts, and the impact of including exiting vehicles in the analysis of single-lane roundabout capacity was evaluated. Vehicles exiting the roundabout were found to have a measurable impact on the estimated capacity of the roundabout approach. Both follow-up and critical headway values decreased when exiting vehicles were included. Also, the estimated capacity including exiting vehicles was found to increase or decrease (relative to capacity estimates that excluded exiting vehicles) depending on the percentage of conflicting vehicles that were exiting vehicles.

The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series. The predicted congestion information is backward to the node. NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction. Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.

The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series. The predicted congestion information is backward to the node. NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction. Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.

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This study evaluated the operational impacts of an unconventional outside left-turn lane design used at some signalized intersections in China. Using traffic data collected from 10 approaches to five signalized intersections where both traditional inside and unconventional outside left-turn lanes are installed, the research team compared turning speeds and saturation flow rates for left-turning vehicles from inside and outside left-turn lanes. The team found that vehicles turning from outside left-turn lanes had relatively higher turning speeds than those turning from inside left-turn lanes. The differences in speed were statistically significant for both passenger cars and heavy vehicles. However, the higher speeds did not result in higher left-turn lane capacity. Unconventional outside left-turn lanes provided slightly lower, but generally comparable, left-turn saturation flow rate when compared with traditional inside left-turn lanes. The differences in discharge headways from inside and outside left-turn lanes were not statistically significant. A binary logit model was developed to quantify the impacts of various factors on the probability of a driver selecting the outside left-turn lane to make a left turn. The chance of a left-turning driver choosing the outside left-turn lane would increase with an increase in the traffic volume of the major street and the queue length in the inside left-turn lane and would decrease with an increase in the distance from the upstream right-side side street to the signalized intersection. Drivers of heavy vehicles and those from upstream right-side side streets were more likely to select outside left-turn lanes.

The changes in length, at equilibrium, of drawn and undrawn 66 nylon yarns on heating and on immersion in swelling agents, have been investigated. Both treatments produce reversible and irreversible changes. On heating, the reversible change in length is caused by an increase in entropy; the length of drawn yarn decreases and the length of undrawn yarn increases. A swelling agent gives a reversible increase in length which is a reflection of the increase in volume caused by uptake of the agent. The irreversible changes in length are believed to be caused by the rupture of some interchain bonds followed by the relaxation of chain segments associated with these bonds; some of the broken interchain bonds then re-form to give a ‘set’ structure which is stable under the conditions of treatment. The mechanism of setting by heat is essentially the same as that of a swelling agent and the actions of the two treatments are supplementary. Increase in the severity of a treatment causes rupture of more interchain bon...

Airlines can optimize surface operations using real-time surface surveillance data. The Federal Aviation Administration (FAA) Technology Development Office (formerly Safe Flight 21 and Surface Technology Assessment) began examining the operational impacts of surface surveillance data sharing in current and future FAA tools. This study investigates the operational impact of surface surveillance data provided to Federal Express (FedEx) at Memphis International Airport (MEM) through a joint FAA/National Aeronautics and Space Administration (NASA) project. We first use an unexpected loss of surface surveillance data as an opportunity to gauge impacts. The analysis measures changes in taxi-out times, queue lengths, and departure rates before, during, and after the surveillance outage. We repeat the analysis comparing a baseline period before implementation of surface surveillance with a post-implementation period. Analyses of both data sets displays a reduction in taxi-out times and indicates an increase in effective departure capacity (approximately 5–10 aircraft per hour greater) during times when surveillance was available.

Congestion tracking control for uncertain TCP/AQM network based on integral backstepping

The HSBQ algorithm is the one of active queue management algorithms, which orders to avoid high packet loss rates and control stable stream queue. That is the problem of calculation of the drop probability for both queue length stability and bandwidth fairness. This paper proposes the HSBQ, which drop the packets before the queues overflow at the gateways, so that the end nodes can respond to the congestion before queue overflow. This algorithm uses the change of the average queue length to adjust the amount by which the mark (or drop) probability is changed. Moreover it adjusts the queue weight, which is used to estimate the average queue length, based on the rate. The results show that HSBQ algorithm could maintain control stable stream queue better than group of congestion metric without flow information algorithm as the rate of hybrid satellite network changing dramatically, as well as the presented empiric evidences demonstrate that the use of HSBQ algorithm offers a better quality of service than the traditionally queue control mechanisms used in hybrid satellite network.

In general, nodes in Wireless Sensor Networks (WSNs) are equipped with limited battery and computation capabilities but the occurrence of congestion consumes more energy and computation power by retransmitting the data packets. Thus, congestion should be regulated to improve network performance. In this paper, we propose a congestion prediction and adaptive rate adjustment technique for Wireless Sensor Networks. This technique predicts congestion level using fuzzy logic system. Node degree, data arrival rate and queue length are taken as inputs to the fuzzy system and congestion level is obtained as an outcome. When the congestion level is amidst moderate and maximum ranges, adaptive rate adjustment technique is triggered. Our technique prevents congestion by controlling data sending rate and also avoids unsolicited packet losses. By simulation, we prove the proficiency our technique. It increases system throughput and network performance significantly..

Most existing discussions regarding the time-dependent distribution of queue length was undertaken in the context of isolated intersections. However, computing queue length distributions for a signalized network with generic topology is very challenging because such process involves convolution and nonlinear transformation of random variables, which is analytically intractable. To address such issue, this study proposes a stochastic queue model considering the strong interdependence relations between adjacent intersections using the probability generating function as a mathematical tool. Various traffic flow phenomena, including queue formation and dissipation, platoon dispersion, flow merging and diverging, queue spillover, and downstream blockage, are formulated as stochastic events, and their distributions are iteratively computed through a stochastic network loading procedure. Both theoretical derivation and numerical investigations are presented to demonstrate the effectiveness of the proposed approach in analyzing the delay and queues of signalized networks under different congestion levels.

Probe vehicle data are increasingly becoming more attractive for real-time system state estimation in transportation networks. This paper presents analytical models for the real-time estimation of queue lengths at traffic signals using the fundamental information (i.e., location and time) that probe vehicles provide. For a single queue with Poisson arrivals, analytical models are developed to evaluate how error changes in queue length estimation as the percentage of probe vehicles in the traffic stream varies. When the overflow queue is ignored, a closed-form solution is obtained for the variance of the estimation error. For the more general case with the overflow queue, a formulation for the error variance is presented, which requires the marginal probability distribution of the overflow queue as the input. In addition, an approximate model is presented for the latter case, which yields results that are comparable with the exact solution. Overall, the formulations presented here can be used to assess the error in queue length estimation from probe data without conducting simulation runs for various scenarios of probe vehicle market-penetration rates and congestion levels.