Analytical models and traffic microsimulation are two widely used platforms for evaluating roundabout operations. The application of the correct inputs and proper specification of calibration ...parameters should precede the actual simulation, to replicate field traffic conditions. In this sense, simultaneous data collection and estimation of the input, calibration, and validation variables, along with knowledge of their definitions, are crucial. Although simultaneity of data gathering is virtually guaranteed with the use of wide-frame videos captured with an unmanned aerial system (UAS), there are cases where sight distance restrictions may obscure observations of the back of queue and arrival patterns. This paper explores the calibration and validation efforts associated with an analytical platform, SIDRA 9, and a microsimulation model, TransModeler 5, conducted under sight-restricted conditions. Video captured from a drone, followed by trajectory extraction using video processing software, was used to analyze operations on two approaches at a single-lane roundabout. In the process, the team employed a specialized demand estimation method, and developed a novel data collection scheme for estimating the critical headway distribution in TransModeler 5. Because of sight distance constraints, the model validation was limited to the use of the observable system travel time and associated travel speed within the field of view. The comparison results, for both platforms, have confirmed the value of model calibration in more accurately describing field performance. The calibrated models performed differently between the two approaches, with the approach having a larger presence of buses and heavy vehicles yielding slightly poorer results.
This paper compares two analytical approaches for modelling signalised intersection networks in relation to the assessment of signal coordination quality as a fundamental element of network ...performance analysis. These are (i) the traditional model based on using “lane groups” or “links” through aggregation of individual lane conditions, and (ii) a new “lane-based” model of upstream departure and downstream arrival patterns as well as midblock lane changes between upstream and downstream intersections, and the resulting proportions of traffic arriving during the green period at an individual lane level. The latter is part of a lane-based network model that involves blockage of upstream intersection lanes by downstream queues (queue spillback) and capacity constraint applied to oversaturated upstream intersections. The differences between the two models are expected to be particularly important in evaluating closely-spaced intersections with high demand flows where vehicles have limited opportunities for lane changes between intersections. The lane-based model can make use of “special movement classes” (e.g. through movements at external approaches which become turning movements at downstream internal approaches, and the dogleg movements at staggered T intersections) to enhance the modelling of signal platoon patterns. This allows assignment of specific movements to separate lanes and separate signal phases, and tracking of their second-by-second platoon patterns through the network separately. The method also allows better estimation of unequal lane use cases at closely-spaced (paired) intersection systems, a factor which also affects signal platoon patterns. The paper presents a staggered T network example to demonstrate important aspects of modelling signal platoon patterns by approach lane use and movement class, and to compare the resulting traffic performance measures (delay, back of queue, level of service) with those estimated using the traditional method based on lane groups or links.
This paper proposes a delay model for signalized intersections that is suitable for variable demand conditions. The model is applicable to the entire range of expected operations, including highly ...oversaturated conditions with initial queues at the start of the analysis period. The proposed model clarifies several issues related to the determination of the peak flow period, as well as the periods immediately preceding and following the peak. Separate formulas are provided for estimating delay in each of the designated flow periods as well as in the total flow period. Formulas are also provided to estimate the duration of the oversaturation period where applicable. The strength of the model lies in the use of simple rules for determining flow rates within and outside the peak, using the peak flow factor, a generalization of the well-known peak hour factor parameter. Simple rules are also provided for the identification of the location and duration of the peak flow period from observations of the demand profile. Such information is considered vital from an intersection design and evaluation viewpoint. Application of the model to a variety of operating conditions indicates that the estimated delay for vehicles arriving in the peak flow period is an acceptable predictor of the average delay incurred during the total flow period, even when oversaturation persists beyond the total flow period. On the other hand, the use of the average degree of saturation with no consideration of peaking can lead to significant underestimation of delay, particularly when operating at or near capacity conditions. These findings were confirmed by comparing the model results with other models found in the literature. The significant contribution of this work is not simply in the development of improved delay estimates, but, more important, in providing an integrated framework for an estimation process that incorporates (a) the peaking characteristics in the demand flow pattern, (b) the designation of flow-specific periods within the total flow period in accordance with the observed peaking and (c) the estimation of performance parameters associated within each flow period and in combination with other periods. A revised delay formula for the U.S. Highway Capacity Manual (HCM) is proposed. The revised formula has no constraints on the peak flow period degree of saturation, unlike the current HCM formula. It is also recommended that a simple formula for estimating the duration of oversaturation be used in conjunction with the revised delay formula.
The traditional two‐term analytical model for predicting delays, queues and stops with random arrivals as found at isolated signalized intersections is extended to the case of platooned arrivals. The ...work was carried out in the context of modeling traffic performance at signalized paired intersections. A cycle‐by‐cycle macroscopic simulation model was used to calibrate the overflow terms of the performance formulae for a single stream of platooned arrivals at the downstream approach of a paired intersection system. The steady‐state form of the analytical model was used for calibration. The parameters derived for the steady‐state model are then used in the time‐dependent form of the model. Descriptions of the general analytical model, the cycle‐by‐cycle simulation model, its validation against several well‐known models are presented, and the new models derived from this study are described. Extension of the model to multistream, multiphase applications are discussed and areas of further study are identified.
The efficiency and drag parameters in the instantaneous fuel consumption model are explained by comparing the model with the original power-based model developed at Sydney University, and relating ...the two models to a conceptual model. Various efficiency factors internal to the vehicle system can be modelled as contributing to the efficiency parameter, or explicitly as power components. The single efficiency parameter in the original power model includes engine drag and all other internal inefficiency components of the vehicle system. On the other hand, the two efficiency parameters in the Australian Road Research Board (ARRB) model have been derived in such a way that they do not include the engine/internal drag in the steady-state driving mode. A fuel consumption model that uses a drag force component measured by coast-down (in neutral) should employ a nonconstant efficiency factor (i.e. a factor dependent on speed and acceleration rates). Otherwise, a satisfactory level of accuracy cannot be achieved, particularly if the prediction of fuel consumption during different modes of driving is required. If all power terms are modelled explicitly, then a basic (constant) engine efficiency parameter can be employed. The basic efficiency factors found from engine maps are of the order of 0.06 to 0.08, which are very close to the values obtained for the ARRB model. This confirms the accuracy of the calibration method used for the ARRB model.
Bu çalışmada, L. lactis subsp. lactis LL52, L. lactis subsp. cremoris LC79 ve L. lactis subsp. lactis biovar. diacetylactis LD62 suçlarında dört farklı stres koşuluna karşı hücresel dirençlilik ...gelişimi araştırıldı. Stres koşulu olarak yüksek ve düşük sıcaklık, düşük asitlik ve ozmotik basıncın kullanıldığı denemelerde, LL52 diğer suçlardan daha duyarlı bulundu. Stres koşullarına dirençlilik ya indüksiyona bağlı ya da sürekli bir karakter gösterdi. Stres dirençlilik indüksiyonu, bakteri tipine ve stres faktörlerine bağlı olarak hücre üremesinin 40 ve 90 dakikaları arasında meydana geldi.
Özet: İki Lactococcus lactis susu olan L lactis subsp. lactis LL52 ve L. lactis subsp. cremoris LC79'un yüksek ve düşük sıcaklık,
ozmotik şok ve düşük pH stresleri altında protein profilleri ve ...plazmid içeriklerindeki değişimler belirlendi. LL52 susunda yüksek
sıcaklık stresine yanıt olarak 1.6,0, 29,4 ve 45,0 kDa moleküler ağırlıkta üç farklı spesifik protein tespit edildi. LC79 susunda yüksek
sıcaklık stresi protein içeriğinde herhangi bir değişime neden olmadı. Her iki susta tuz ve düşük pH stres yanıtlarına spesifik
proteinler, sırasıyla. 16,0-40,5 kDa ve 24,8-107,5 kDa aralığında değişim gösterdi. Düşük sıcaklık stresiyle ilişkili olarak LL52 ve
LC79 suşlarında hiçbir protein bulunamadı. Plazmid analizleri, stres yanıtları ile bakterilerideki plazmidler arasında bir bağlantının
bulunmadığını gösterdi.
Abstract: Differences in the protein and plasmid content of 2 Lactococcus lactis strains, L. lactis subsp. lactis LL52 and L. lactis subsp.
cremoris LC79, under the stresses of high and low temperature, osmotic shock, and low pH were determined. We identified 3 new
proteins with molecular masses of 16.0, 29.4, and 45.0 kDa as high temperature stress response specific in strain LL52. High
temperature stress did not cause any changes in the protein content of strain LC79. Proteins that were specific for salt stress and
low pH stress responses ranged between 16.0 and 40.5 kDa, and 24.8 and 107.5 kDa, respectively, in both strains. No proteins
were related to low temperature stress in LL52 and LC79 strains. Plasmid analysis indicated that there was no relationship between
stress responses and plasmids in these bacteria.
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