Analysis of Freeway Secondary Crashes With a Two-Step Method by Loop Detector Data

Real-time estimation of secondary crash likelihood on freeways using high-resolution loop detector data

Automatic traffic incident detection based on nFOIL

Dynamic merge control (DMC) can be used in freeway merge areas to change lane allocation dynamically at interchanges. DMC generally prioritizes the facility having higher volume and closes a lane on the lesser-volume roadway. DMC has been implemented in the Netherlands and Germany, where it was reported that the application of DMC significantly improved traffic operations. However the DMC strategy has rarely been studied and has not been implemented in the United States. This research used microsimulation studies with VISSIM to investigate the efficiency of the DMC strategy. Optimum traffic demand thresholds were sought specifically for the geometric case in which a two-lane freeway merged with a three-lane freeway and tapered into four lanes. Major-road traffic demands between 2,500 and 4,600 vehicles per hour were compared against minor-road demands between 3,000 and 4,600 vehicles per hour. The DMC strategy was applied by closing the right lane of the major road, ahead of the merging gore area. The results indicate that (a) the DMC strategy is beneficial for all the previously mentioned traffic demand combinations in regard to average vehicle delay and average vehicle speed; (b) when traffic demand on the minor road exceeds 1,900 vehicles per hour per lane, these benefits become statistically and practically significant; and (c) DMC can greatly alleviate the capacity reductions caused by lane changing in the merge area.

A detailed study has been made of the conditions under which the average vehicle is driven in the Tehran area. This study was needed to assist the Iranian Department of Environment in developing a driving cycle and test procedures for motor vehicle exhaust emissions. A preliminary traffic survey was made in which average vehicle speed and traffic densities were measured for different streets at various hours of the day. As a result of this survey, representative routes were selected. A large number of runs were made in Tehran Traffic using cars instrumented to continuously record engine speed, manifold vacuum pressure, and other pertinent data. The measurements indicate that the average driver in Tehran spends 38% of his driving time idling. He moves at constant speed cruise 21% of his time at an average speed of 22.4 kilometer per hour. The average driver accelerates 22% of the time. He decelerates 14% of the total time.

The article presents a method of determining the characteristics of exhaust emissions and fuel mass consumption in real driving conditions based on a single test using the Monte Carlo method. The exhaust emission characteristics used are the relations between the emissions and the average vehicle speed, and the characteristic of the fuel mass consumption is the dependence of the fuel mass consumption at the average vehicle speed. The results of empirical research of a passenger car with a spark-ignition engine in the RDE test were used. The use of the Monte Carlo method made it possible to select the initial and final moments of averaging the process values, thanks to which it was possible to determine the discrete values of the characteristics for various values of average vehicle speeds. The determined discrete characteristics of the particulate mass and number emissions and fuel mass consumption relative to the average vehicle speed were approximated by polynomial functions of the second and third degree. The determined discrete characteristics, presented as sets of points, were characterized by a relatively small dis-persion in relation to their polynomial approximations. The average relative deviation of the points of discrete characteristics from the value of the polynomial was in most cases small less than 4%, only in the case of the number of particles emitted deviated from this, as the average relative deviation of the measured points from the determined polynomial was nearly 14%. Combined with the results of RDE empirical studies, the Monte Carlo method proved to be an effective method for determining the characteristics of exhaust emissions, measured in real vehicle operating conditions. The main advantage of the proposed method was a significant reduction in the actual workload necessary to carry out the empirical research where it became possible to determine the charac-teristics in a large range of vehicle average speed values with just one drive test. Using standard methods of meas-uring this type of data, it would be necessary to conduct multiple tests, driving at different average vehicle speeds.

The notion of material stability is examined in the context of active muscle tissue modeling, where the nonlinear constitutive law is dependent both on the physiologically driven muscle contraction and finite mechanical deformation. First, the governing equations and constitutive laws for a general active-elastic material with a single preferred direction are linearized about a homogeneous underlying configuration with respect to both the active contraction and deformation gradient. In order to obtain mathematical restrictions analogous to those found in elastic materials, stability conditions are derived based on the propagation of homogeneous plane waves with real wave speeds, and the generalized acoustic tensor is obtained. Focusing on 2D motions, and considering a simplified, decoupled transversely isotropic energy function, the restriction on the active acoustic tensor is recast in terms of a generally applicable constitutive law, with specific attention paid to the fiber contribution. The implication of the material stability conditions on material parameters, active contraction, and elastic stretch is investigated for prototype material models of muscle tissue.

Wave propagation and localization in a rate-dependent cracked medium—model formulation and one-dimensional examples

During the driving process in expressway, the vehicle carrying efficiency is influenced by many factors. However, in the existing researches on microscopic traffic flow, there is a lack of evaluation index system and corresponding calculation, so it is necessary to choose appropriate indicators and evaluation methods to calculate the vehicle carrying efficiency comprehensively. Therefore, in this paper, we establish a cellular automata model of the three-lane expressway and select multiple parameters that influence the vehicle carrying efficiency, which includes three input indicators: vehicle travel time, vehicle fuel consumption, vehicle emission, and two output indicators: vehicle average speed and vehicle ridership. Meanwhile, the data envelopment analysis is used to calculate the vehicle carrying efficiency under different maximum speed limits. From the simulation results, the traffic condition of vehicles is analyzed and corresponding improvement strategies are proposed, which have certain research significance for the traffic management department to formulate reasonable management measures.

An ultrasonic Doppler blood flow measuring apparatus comprises a plurality of frame memories for storing information pieces about a blood flow speed in a unit of frame, circuits for comparing blood flow speed information pieces at corresponding addresses on the plurality of frame, memories and determining a speed difference, a circuit for comparing the speed difference with a predetermined threshold value and determining a blood flow at the corresponding address as an arterial flow when the speed difference exceeds the threshold value but as a venous flow when the speed difference is below the threshold value, and a circuit for displaying the determined arterial and venous flows in different colors.

This paper develops the fixed-smoothing asymptotics in a two-step generalized method of moments (GMM) framework. Under this type of asymptotics, the weighting matrix in the second-step GMM criterion function converges weakly to a random matrix and the two-step GMM estimator is asymptotically mixed normal. Nevertheless, the Wald statistic, the GMM criterion function statistic, and the Lagrange multiplier statistic remain asymptotically pivotal. It is shown that critical values from the fixed-smoothing asymptotic distribution are high order correct under the conventional increasing-smoothing asymptotics. When an orthonormal series covariance estimator is used, the critical values can be approximated very well by the quantiles of a noncentral F distribution. A simulation study shows that statistical tests based on the new fixed-smoothing approximation are much more accurate in size than existing tests.

The goal of this research project was to develop a method to measure the performance of a winter maintenance program with respect to the task of providing safety and mobility to the travelling public. Developing these measures required a number of steps, each of which was accomplished. First, the impact of winter weather on safety (crash rates) and mobility (average vehicle speeds) was measured by a combination of literature reviews and analysis of Iowa Department of Transportation traffic and Road Weather Information System data. Second, because not all winter storms are the same in their effects on safety and mobility, a method had to be developed to determine how much the various factors that describe a winter storm actually change safety and mobility. As part of this effort a storm severity index was developed, which ranks each winter storm on a scale between 0 (a very benign storm) and 1 (the worst imaginable storm). Additionally a number of methods of modeling the relationships between weather, winter maintenance actions and road surface conditions were developed and tested. The end result of this study was a performance measure based on average vehicle speed. For a given class of road, a maximum expected average speed reduction has been identified. For a given storm, this maximum expected average speed reduction is modified by the storm severity index to give a target average speed reduction. Thus, if for a given road the maximum expected average speed reduction is 20 mph, and the storm severity for a particular storm is 0.6, then the target average speed reduction for that road in that storm is 0.6 x 20 mph or 12 mph. If the average speed on that road during and after the storm is only 12 mph or less than the average speed on that road in good weather conditions, then the winter maintenance performance goal has been met.

With increasing urbanization, problems such as traffic congestion and environmental pollution have become more pronounced. Alternative modes of transportation such as micromobility (bicycles, e-scooters, e-bikes, segways) have the potential to reduce these problems. This study analyzes the effects of micromobility on the performance of an intersection using a simulation-based approach. A four-arm signalized intersection in Nilüfer, Bursa, is taken as a model, and the impact of micromobility on intersection performance is evaluated in terms of "average vehicle speed", "queue delay", and "vehicle travel time" performance indicators. In the study, the inclusion of micromobility at low levels (2.5% and 5%) improves intersection performance, while at higher levels (7.5% and 10%) this improvement is reversed, resulting in longer travel times and lower speeds. Signal modification has shown an improvement in the performance of the intersection. However, these results suggest the need for special signaling studies for micromobility vehicles at intersections. The study provides important findings for transportation management and policy makers in micromobility planning.

Simple SummaryThis study aimed at identifying, on the basis of objective evaluations (blood parameters): (1) the pre-slaughter treatments that result in higher stress for heavy pigs and can therefore be used as pre-slaughter stress indicators; (2) the meat quality parameters that show the largest variation as a response to the stress experienced during pre-slaughter handling. Two blood parameters (cortisol and creatine kinase) were used to categorize pigs into two groups (clusters) depending on transport conditions: “higher stress” and “lower stress”. Our results indicate that the variables/indexes which differed more widely between the two clusters (namely, average vehicle speed during transport, welfare slaughter score, overall transport and slaughter welfare index (TSWI), distance travelled, group stability, and behaviors—slips, falls, and overlaps—during unloading) might be considered as the best descriptors of the welfare conditions experienced by Italian heavy pigs during pre-slaughter handling. However, we observed no consistent effects of the stress experienced during pre-slaughter handling on meat quality, which warrants the need for further studies addressing: (1) the individual stress response and meat quality variability in pigs within the same transport; (2) the relationships between the variables examined and meat quality, with the aim to improve the TSWI.This study aimed at identifying possible pre-slaughter indicators and/or indexes to be used to predict pig stress response and meat quality variation. Data were collected on 44 shipments (loads) of Italian heavy pigs. For each shipment, several pre-slaughter parameters were recorded on farm, during transport, and at the slaughterhouse. Blood and meat samples were taken from 10 pigs from every of the 44 loads included in the study (N = 440). Blood samples were used to assess cortisol and creatine kinase levels, whereas meat samples were used to assess meat quality (pH, instrumental color, tenderness, water-holding capacity, and sensory analysis). Cluster analysis of blood parameters allowed the categorization of the shipments into two main clusters: Lower Stress (LS) and Higher Stress (HS). The variables/indexes statistically differing between the two clusters were: average vehicle speed during transport, welfare index at slaughter (i.e., “slaughter score”), overall transport and slaughter welfare index (TSWI), distance travelled, and behaviors (slips, falls, overlaps) during unloading, which appeared to be the best descriptors of the welfare conditions experienced by Italian heavy pigs during pre-slaughter handling. No consistent effects of the stress level experienced on meat quality was detected, which warrants the need for further studies conducted under more variable pre-slaughter conditions, with the aim of simplifying and improving the TSWI.

A bottleneck is defined as a point upstream of which exists a queue and downstream of which exists freely flowing traffic. Bottleneck automatic identification technology is based on loop detector data using identification algorithm to identify bottleneck locations and their activation and deactivation times. This research is an improvement to previous speed-based bottleneck recognition methods, and various parameter determinations of standards and algorithm evaluation standards were discussed. The proposed algorithm was applied to detect the bottlenecks in Shanghai inner ring viaduct Dabaishu-Guangzhong Road section, and verified by cumulative curve method. It was found out that the occupancy threshold value based algorithm had a high precision. The proposed real-time bottleneck detection method is useful for transportation authorities to identify bottlenecks as soon as possible and track their impact over time.

Large truck fatal crash severity segmentation and analysis incorporating all parties involved: A Bayesian network approach