Van Aerde Research Articles

Analysis of congestion key parameters, dynamic discharge process, and capacity estimation at urban freeway bottlenecks: a case study in Beijing, China

ABSTRACT Recurring bottlenecks significantly contribute to urban freeway congestion, making their analysis essential. This study examines six bottlenecks on Beijing’s Ring Road using multi-day data, identifying them via Dynamic Time Warping and Fuzzy C-Means Clustering (DTW+FCM). Key parameters—free-flow speed, critical speed, critical density, and jam density—are calibrated using fundamental diagram models. The Weibull distribution analyzes flow and speed patterns during congestion phases. The DTW+FCM method effectively identified bottlenecks and congestion levels. Severe congestion lasting over 10 hours on the West Second and Third Ring Roads averaged speeds of 15 km/h. The S3 model best fits data for the West Ring Roads, while the Van Aerde model suits the North Ring Roads. Different methods yield varying traffic capacity estimates, highlighting the need for nuanced approaches in urban expressway planning to maintain traffic quality and comfort. These findings offer valuable guidance for research and practical traffic management solutions.

Impact of High Resolution Radar-Obtained Weather Data on Spatio-Temporal Prediction of Freeway Speed

Inclement weather and environmental factors impact traffic operations resulting in travel delays and a reduction in travel time reliability. Precipitation is an example of an environmental factor that affects travel conditions, including traffic speed. While Intelligent Transportation Systems services aim to proactively mitigate congestion on roadways, these services are often not sensitive to weather conditions. This paper investigates the application of high-resolution weather data in improving the performance of proactive transportation management models and proposes short-term speed prediction models that fuse real-time high-resolution weather surveillance radar data with traffic stream data to conduct spatial and temporal prediction of the speed of roadway segments. Extreme gradient boosting weather-aware speed prediction models were developed for a 7-km segment of Interstate 270 in St. Louis, MO, USA. The performance of the weather-aware models was compared with the performance of weather-insensitive speed prediction models that did not take precipitation into account. The results indicated that in the majority of instances, the weather-aware models outperformed the weather-insensitive models. The extreme gradient boosting models were compared with the K-nearest neighbors algorithm and feed-forward neural network models. The extreme gradient boosting model consistently outperformed the other two methods. In addition to speed prediction models, van Aerde speed-flow traffic stream models were developed for rain and no-rain conditions to study the impact of precipitation on the traffic stream across the corridor. Results indicated that the impact of precipitation is not identical across the corridor, which was mirrored in the results obtained from weather-aware speed prediction models.

Research on Characteristics of Hefei Road Traffic Flow Based on GIS

Taking the whole road network traffic system in Hefei as the research object, based on GIS (Geographic Information System) traffic flow big data, this paper analyzes and compares the van aerde traffic flow model. The characteristics of urban road traffic flow are compared and analyzed according to road grades, working days, holidays and seasonality, which lays a foundation for further research on driving conditions and travel rules of automobile users in Hefei.

Calibration of the empirical fundamental relationship using very large databases

This paper describes a procedure for fitting traffic stream models using very large traffic databases. The proposed approach consists of four steps: (1) an initial treatment to eliminate noisy, inaccurate data and to homogenize the information over the density range; (2) a first fitting of the model, based on the sum of squared orthogonal errors; (3) a second filter, to eliminate outliers that survived the initial data treatment; and (4) a second fitting of the model. The proposed approach was tested by fitting the Van Aerde traffic stream model to 104 thousand observations collected by a permanent traffic monitoring station on a freeway in the metropolitan region of São Paulo, Brazil. The model fitting used a genetic algorithm to search for the best values of the model parameters. The results demonstrate the effectiveness of the proposed approach.

Calibration of traffic stream models on high-speed urban roads with heterogeneous traffic

The basic objective of this work was to identify best-fitting traffic stream models for the varying traffic flows on high-speed urban roads under heterogeneous traffic in India. To this end, traffic data on ten-lane, eight-lane and six-lane divided roadways were collected. An iterative process was developed to fit traffic stream models by optimising constant parameters using optimisation techniques. Different single-regime models, multi-regime models and models based on the car-following approach were fitted to the field-observed data set. Among the single-regime models, the Northwestern model fitted the data set with the highest level of accuracy. The three-regime model was found to be more accurate than the other multi-regime models. Various multi-variate car-following models were also applied and found to fit uncongested and congested data with higher accuracy than the use of a single equation. Among all the models examined, the model proposed by Van Aerde and Rakha provided the highest accuracy. This observation was also validated for roadway sections with varying carriageway widths. The outcome of this research may be useful for the development of correct trends of speed–flow relationships for similar kinds of roadway facilities in the Asia-Pacific nations. Using the most suitable trend, level-of-service boundaries can be delineated more effectively.

Comparison of Highway Capacity Estimation Methods

The capacity of a freeway segment is a critical factor for planning, design, and operational analysis of freeway facilities. This research aimed to perform a comparison among well-known freeway capacity estimation methods in order to investigate their application, as well as their advantages and disadvantages. Single estimate capacity methods such as the Van Aerde method, and breakdown probability methods, such as the product limit method (PLM), the Highway Capacity Manual (HCM) method, and the sustainable flow index (SFI) method, were applied at six merge bottleneck locations in the Kansas City area. The results from all methods were compared and the advantages and the disadvantages of each method were discussed. The HCM results showed a significant variability in the estimated breakdown probability function and the resulting capacities. The HCM method was also found to be sensitive to the breakdown probability ratios as a single breakdown observation can significantly shift the fitted distribution and the corresponding capacity estimate. The PLM model provided the highest capacity estimates, followed by the Van Aerde model capacities. The Van Aerde capacities were also found to be closer to the average pre-breakdown flow rates. Finally, the PLM and the SFI method showed consistent performance in comparison to the remaining methods, and flexibility in being applied on different sites with various characteristics.

Traffic Flow Modeling of Diverse Work Zone Activities

What effect does work activity type have on traffic conditions in a work zone? This question has still not been answered satisfactorily in practice. Without knowing the true effect a work activity has on traffic, practitioners are forced to make assumptions while scheduling work. This paper attempts to answer this question by studying the traffic flow characteristics, that is, traffic speed versus flow curves, capacity reduction factors, and free-flow speed reduction factors, for various activities related to construction and maintenance. The importance of the speed–flow curves and reduction factors for work zone planning is also stressed in the latest edition of the Transportation Research Board’s Highway Capacity Manual. This manual recommends capacity and speed reduction factors for work zones, yet does not include specific guidance for including the impact of work activities. Thre e traffic stream models, Gipps, Newell–Franklin, and Van Aerde, were calibrated using field data from St. Louis, Missouri. The Van Aerde model fitted the field data the best as compared to the other two models. Using the Van Aerde model-generated speed–flow curves, it was found that the capacity for bridge-related activities varied from 1,416 vehicles per hour per lane (vphpl) to 1,656 vphpl and for pavement-related activities from 1,120 vphpl to 1,728 vphpl. The capacity reduction factor for different work activities was found to be in the range 0.68 to 0.95, whereas the free-flow speed reduction factor was found to be in the range 0.78 to 1.0. The methodology proposed in this paper contributes toward the development of practitioner guidance and incorporation of work activity effects into traffic impact assessment tools.

Practical approach to determining traffic congestion propagation boundary due to traffic incidents

A practical approach for predicting the congestion boundary due to traffic incidents was proposed. Based on the kinematic wave theory and Van Aerde single-regime flow model, a model for estimating the congestion propagation speed for the basic road segment was developed. Historical traffic flow data were used to analyze the time variant characteristics of the urban traffic flow for each road type. Then, the saturation flow rate was used for analyzing the impact of the traffic incident on the traversing traffic flow at the congestion area. The base congestion propagation speed for each road type was calculated based on field data, which were provided by the remote traffic microwave sensors (RTMS), floating car data (FCD) system and screen line survey. According to a comparative analysis of the congestion propagation speed, it is found that the expressway, major arterial, minor arterial and collector are decreasingly influenced by the traffic incident. Subsequently, the impact of turning movements at intersections on the congestion propagation was considered. The turning ratio was adopted to represent the impact of turning movements, and afterward the corresponding propagation pattern at intersections was analyzed. Finally, an implementation system was designed on a geographic information system (GIS) platform to display the characteristics of the congestion propagation over the network. The validation results show that the proposed approach is able to capture the congestion propagation properties in the actual road network.

Analysis of Speed Differences in Data from Remote Traffic Microwave Sensors and Floating Car Data Systems on Expressways

The remote traffic microwave sensor (RTMS) and the floating car data (FCD) system are two important sources of traffic data; both provide key speed information. However, these two data processes gather data differently. The RTMS detects spot speeds at specific cross sections. The FCD system collects travel speed along a segment of a road link. Although the difference between time mean speed (TMS) and space mean speed (SMS) has been discussed for decades, the speed differences between RTMS and FCD have been underestimated in many engineering applications. This study examined the speed differences between the RTMS and FCD data on expressways in Beijing. First, the differences between the two data collections over 5 days were analyzed. The correlation between the difference and the value of the speeds was investigated. The relationships between TMS and SMS in existing studies were then compared with the relationship derived from the field data. It was found that the existing relationships between TMS and SMS were not valid for representing the relationship between the RTMS and FCD speeds. The flow–speed relationship from each data group was then investigated by using the Van Aerde traffic flow model; it was found that free-flow speed and speed at capacity determined on the basis of the RTMS data were significantly overestimated. It was inaccurate to apply the RTMS speed to the analysis of fundamental traffic flow diagrams. Finally, the repeatability and stability of the relationship between these two data groups were validated.

Derivation of Van Aerde Traffic Stream Model and Studying the Effect of Ramp Metering

With increase in population, demand for traffic is increasing tremendously. As a consequence congestion on urban freeways or highways during the morning and evening peak hours is always increasing. This research examines the traffic condition on Highway 2(i.e Deerfoot Trail), Calgary,Canada by providing ramp metering (funded by Government of Canada in Collaboration with MITACS Globalink Program). In order to accommodate increasing traffic demand, constructing new highways and adding lanes is not always the best option. Instead proper management of transportation system can help in increasing its efficiency. It is therefore important to increase our understanding of traffic flow models to help estimating the efficiency of different road facilities and therefore prepare us to make enlightened decisions in the design process of new road facilities or improving older ones.

An analysis of four methodologies for estimating highway capacity from ITS data

With the recent advent of Intelligent Transportation Systems (ITS), and their associated data collection and archiving capabilities, there is now a rich data source for transportation professionals to develop capacity values for their own jurisdictions. Unfortunately, there is no consensus on the best approach for estimating capacity from ITS data. The motivation of this paper is to compare and contrast four of the most popular capacity estimation techniques in terms of (1) data requirements, (2) modeling effort required, (3) estimated parameter values, (4) theoretical background, and (5) statistical differences across time and over geographically dispersed locations. Specifically, the first method is the maximum observed value, the second is a standard fundamental diagram curve fitting approach using the popular Van Aerde model, the third method uses the breakdown identification approach, and the fourth method is the survival probability based on product limit method. These four approaches were tested on two test beds: one is located in San Diego, California, U.S., and has data from 112 work days; the other is located in Shanghai, China, and consists of 81 work days. It was found that, irrespective of the estimation methodology and the definition of capacity, the estimated capacity can vary considerably over time. The second finding was that, as expected, the different approaches yielded different capacity results. These estimated capacities varied by as much as 26 % at the San Diego test site and by 34 % at the Shanghai test site. It was also found that each of the methodologies has advantages and disadvantages, and the best method will be the function of the available data, the application, and the goals of the modeler. Consequently, it is critical for users of automatic capacity estimation techniques, which utilize ITS data, to understand the underlying assumptions of each of the different approaches.

Differences between HCM Procedures and Fundamental Diagram Calibration for Operational LOS Assessment on Italian Freeways

A not clear national framework and the uncertainty as to the transferability of the U.S. HCM require an assessment of standard methodologies more calibrated on Italian freeways. The study is aimed at testing the Levels of Service assessment for a sample freeway segment on the basis of a calibrated Fundamental Diagram, and at evaluating its consistency with respect to the most recent methodologies from HCM2010. The research shows a test calibration of the Fundamental Diagram according to the Longitudinal Control Model and Van Aerde Model. The comparative analysis shows how standard procedures and ranges could underestimate operational congestion levels on the test section. Therefore, the results suggest that operators should to use carefully HCM standard procedures and that transferability issues should be further analyzed.

Calibrating Car-Following Model Considering Measurement Errors

Car-following model has important applications in traffic and safety engineering. To enhance the accuracy of model in predicting behavior of individual driver, considerable studies strive to improve the model calibration technologies. However, microscopic car-following models are generally calibrated by using macroscopic traffic data ignoring measurement errors-in-variables that leads to unreliable and erroneous conclusions. This paper aims to develop a technology to calibrate the well-known Van Aerde model. Particularly, the effect of measurement errors-in-variables on the accuracy of estimate is considered. In order to complete calibration of the model using microscopic data, a new parameter estimate method named two-step approach is proposed. The result shows that the modified Van Aerde model to a certain extent is more reliable than the generic model.

Olfactory granule cell-specific silencing slows down odor discrimination time in mice

Olfactory granule cell-specific silencing slows down odor discrimination time in mice

Empirical Study of Impact of Icy Roadway Surface Condition on Driver Car-Following Behavior

Research was done to quantify the impact of icy roadway conditions on driver car-following behavior. The data used in the study were gathered by a group of researchers at Japan's Hokkaido University in a controlled environment under dry and icy roadway conditions. The data were used to calibrate the Van Aerde steady-state car-following model, along with vehicle acceleration and deceleration constraints. The impact of icy roadway conditions on five driver-specific car-following parameters [driver perception–reaction time (PRT), free-flow or desired speed, speed-at-capacity, capacity, and jam density] was conducted with one-way analysis of variance and Kruskal–Wallis tests. The results demonstrate that icy roadway conditions produce statistically significant differences at a 5% significance level. Specifically, icy roadway conditions reduce the mean free-flow speed, speed at capacity, and capacity by 28%, 13%, and 46%, respectively, compared with driving on dry roadways. The mean PRT for icy conditions is found to take 13% longer than driving under dry conditions. The longer PRTs can be attributed to drivers driving at lower speeds and larger spacing on icy surfaces compared with dry conditions.

Dancing neurons, complex beats

Dancing neurons, complex beats

Validation of Van Aerde's simplified steadystate car-following and traffic stream model

The research reported in this paper validates Van Aerde's simplified steady-state car-following and traffic stream motion model, identifies valid input parameter ranges, and compares the model performance to other single and multi-regime models. In addition, the paper demonstrates that the Pipes linear car-following model produces the commonly known inverted V-shaped flow-density relationship. The paper also derives the relationship between the kinematic wave speed and the facility capacity, jam density, and free-flow speed for the Pipes and Van Aerde models. The study demonstrates that the Van Aerde functional form offers a superior fit to field data when compared to Newell's nonlinear single-regime model and Pipes linear dual-regime model. Specifically, the Van Aerde model is shown to fit data from different roadway types using different data aggregation intervals with a quality of fit that is superior to multi-regime models, without the need to deal with the complexities associated with the selection of regime break points.

Derivation of Van Aerde Traffic Stream Model from Tandem-Queuing Theory

The relationship between the traffic stream flow, speed, and density can be described with a fundamental diagram. With a reasonable fundamental diagram, the maximum flow rate of motorways and the corresponding traffic quality can be estimated more accurately. According to different theories such as the car-following theory, queuing theory, or theory of fluid dynamics, different models for the fundamental diagram can be established. From queuing theory, several models can be found. However, the existing queuing models consider a roadway cross section as a stand-alone queuing counter, and thus the interaction between consecutive vehicles cannot be considered sufficiently. This paper presents a new model treating a road stretch as a series of many queuing counters. The new model yields a single-regime fundamental diagram that fully corresponds to the well-known Van Aerde model. In the Van Aerde model, the model parameters can be easily measured and calibrated using loop detector data. The application and calibration of the model are demonstrated with sample data sets and compared with other state-of-the-art traffic stream models. The results demonstrate the superiority of this model in capturing traffic stream behavior.

Analysis of Traffic Flow Characteristics on Ring Road Expressways in Beijing

The primary objective of this paper is to analyze traffic flow characteristics on ring road expressways in Beijing on the basis of floating car data (FCD) and remote traffic microwave sensors (RTMS) data. Traffic flow characteristics are studied in relation to lane use, the relationship between occupancy and density, relationship of flow–speed–density, and the relationship between FCD speed and RTMS speed. It is demonstrated that lane use characteristics on the basic sections of ring road expressways are similar to those of freeways, in which the average vehicle lengths in the median, center, and shoulder lanes are found to be approximately 5.78 m, 6.03 m, and 6.33 m, respectively. Further, the four essential parameters used to characterize the Van Aerde flow–speed–density relationship are calibrated and compared for the second, third, and fourth ring road expressways. Results indicate that the fourth ring road, which has the highest free-flow speed, speed-at-capacity, and capacity, has characteristics similar to those of typical freeways. Traffic flow characteristics observed on the second and third ring roads are roughly consistent with the Greenshields model. It is observed that the second ring road has the worst traffic conditions, followed by the third ring road, and that the basic sections of ring road expressways have better traffic conditions than the areas around the ramp junctions. Finally, a regression analysis is done to develop the relationship between FCD speed and RTMS speed. It is found that RTMS speed is slightly higher than FCD speed, with a difference of less than 6%.

Varenicline and Adult ADHD

Back to table of contents Previous article Next article LETTERFull AccessVarenicline and Adult ADHDJames A. Cocores M.D.,Mark S. Gold M.D.,James A. Cocores M.D.Search for more papers by this author,Mark S. Gold M.D.Search for more papers by this author,Published Online:1 Oct 2008AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail To the Editor: Nicotine dependence is perpetuated by biobehavioral rewards generated as the result of nicotine’s interaction with the brain’s neurochemical systems. 1 Nicotine’s memory-enhancing reward is believed to result from its effects on specific nicotinic acetylcholine receptors. 2 Nicotine’s attentional, antidepressant, and antianxiety rewards are thought to be due to pathways between nicotinic acetylcholine receptors and noncholinergic neuronal subtypes that selectively traffic dopamine, norepinephrine, 5-hydroxytryptamine, and gamma-aminobutyric acid. 3 Varenicline is a new treatment for nicotine dependence and a member of the selective alpha4beta2 nicotinic acetylcholine receptor partial agonist class. 4 Central nicotinic acetylcholine receptors have been implicated in attention deficit hyperactivity disorder (ADHD), 5 and an alpha4beta2 antagonist counteracted nicotine-induced improvement in an animal model of ADHD. 6The first case of adult ADHD that responded to the addition of varenicline is reported here.Case ReportMs. A, a 26-year-old white woman, was self-referred in 2007 for difficulties staying focused, staying on task, and with reading comprehension. She fulfilled DSM-IV-TR criteria for ADHD, but was against the initial recommendation to begin taking a prescription stimulant. The administration of the antidepressants bupropion (150 mg) and venlafaxine (up to 150 mg), each alone or in combination with valproic acid, was met with either side effects or undesirable results. The medicine selected was based on office sample availability at Ms. A’s request because of financial problems. A wealthier patient had previously donated a barely used varenicline prescription that she had abandoned due to nausea. Ms. A agreed to undergo a trial of varenicline taking 0.5 mg in the morning, after eating a low-acid breakfast, with an 8-oz glass of water. Her reading comprehension and ability to focus improved substantially after reaching 1 mg b.i.d. Her mild hyperactivity improved marginally. She complained of no side effects as she completed 6 weeks, including weekends, of the clinic’s subsidized varenicline treatment trial. Her problematic ADHD symptoms fully resurfaced about 2 days after she ran out of varenicline. Ms. A agreed to continue medicine trials using affordable antidepressant, dopamine agonist, or nicotine replacement generics.CommentAlthough this report does not rule out the placebo effect, and a therapeutic connection between varenicline and ADHD cannot be established with certainty, this case does suggest that the new selective alpha4beta2 nicotinic acetylcholine receptor partial agonist class of medicines is useful in the management of adult ADHD. In particular, the varenicline-ADHD interface warrants further investigation using larger groups of subjects, more sophisticated study designs, and a variety of memory deficits such as depression and mild cognitive impairment.Nutritional Neuropsychiatry, Southcoast Psychotherapy and Education Associates, Boca Raton, Florida; Visiting Clinical Assistant Professor, University of Florida College of Medicine and McKnight Brain Institute, Gainesville, FloridaEminent Scholar, Distinguished Professor and Chairman, Department of Psychiatry, McKnight Brain Institute; College of Medicine, University of Florida, Gainesville, FloridaReferences1 . Rosecrans JA: The biobehavioral effects of nicotine: interaction with brain neurochemical systems, in The Clinical Management of Nicotine Dependence. Edited by Cocores JA. New York, Springer-Verlag, 1991, pp 53–65Google Scholar2 . Mansvelder HD, van Aerde KI, Couey JJ, et al: Nicotinic modulation of neuronal networks: from receptors to cognition. Psychopharmacology (Berl) 2006; 184:292–305Google Scholar3 . Rosecrans JA, Krynock GM, Newlon PG, et al: Central mechanisms of drugs as discriminative stimuli: involvement of serotonin pathways, in Stimulus Properties: Ten Years of Progress. Edited by Colapaert FC, Rosecrans JA. Amsterdam, Elsevier/North-Holland Press, 1978, pp 83–98Google Scholar4 . Lam S, Patel PN: Varenicline: a selective alpha4beta2 nicotinic acetylcholine receptor partial agonist approved for cessation. Cardiol Rev 2007; 15:154–161Google Scholar5 . Potter AS, Newhouse PA, Bucci DJ: Central nicotinic cholinergic systems: a role in the cognitive dysfunction in attention-deficit/hyperactivity disorder? Behav Brain Res 2006; 175:201–211Google Scholar6 . Ueno K, Togashi H, Matsumoto M: Alpha4beta2 nicotinic acetylcholine receptor activation ameliorates impairment of spontaneous alternation behavior in stroke-prone spontaneously hypertensive rats, an animal model of attention deficit hyperactivity disorder. J Pharmacol Exp Ther 2002; 302:95–100Google Scholar FiguresReferencesCited byDetailsCited ByNeuropsychopharmacology, Vol. 38, No. 3Expert Opinion on Drug Safety, Vol. 9, No. 3 Volume 20Issue 4 Fall, 2008Pages 494-495 Metrics PDF download History Published online 1 October 2008 Published in print 1 October 2008