High Traffic Flow Research Articles

THREE ARM UNSIGNALIZED INTERSECTION ON JALAN PERJUANGAN – JALAN KALIABANG BABELAN, NORTH BEKASI

The intersection of Jalan Perjuangan - Jalan Kaliabang Babelan, North Bekasi is experiencing high traffic flow. It is because the intersection area is a shopping area and a residential area so that traffic jams often occur during busy traffic jams. This research aims to see the degree of saturation and delay at the research location. This research was conducted using a method based on MKJI 1997. The results of the analysis in the morning, the maximum flow that occurs on weekdays is 5533.7 pcu / hour, the minimum flow on holidays is 3982.2 pcu / hour with the degree of saturation on working day in the morning is equal to 1.18, and the degree of saturation in morning on holidays is 1.30 with a delay in morning in holidays is 36.1 sec / pcu, the delay in morning on working day is 5.7 sec / pcu. The results of the analysis during the day that the maximum flow occurs on holidays is 3905.6 pcu / hour, the minimum flow on working day is 3551.9 pcu / hour with the degree of saturation on holiday is 1.11, the degree of saturation on weekdays in the afternoon is 0.83 with a delay on holiday is 26.97 sec / pcu, a delay on working day is 13.48 sec / pcu. The results of the analysis in the afternoon the maximum flow occurs on weekdays of 6304.8 pcu / hour, the minimum flow on holidays is 5869.1 pcu / hour with the degree of saturation on working day is 1.84, the degree of saturation on holidays is 1.55 with a delay on working day is 0.74 sec / pcu, and delay on holidays is 1.08 sec / pcu

A predictive analytics method for maritime traffic flow complexity estimation in inland waterways

Maritime traffic flow complexity is the factor that presents in most existing maritime safety analysis methods. It is considered as one of the main influencing factors affecting maritime safety. It can be estimated quantitatively through the analysis of traffic data. To explore maritime ship traffic in more detail, a predictive analytics method utilizing the Lempel-Ziv algorithm and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) for traffic safety management is proposed. The Lempel-Ziv algorithm quantifies the entropy for the evaluation of the irregularity and unpredictability of ship travel time sequences, and TOPSIS ranks complexity. The results presented utilize Automatic Identification System (AIS) data corresponding to complex inland waterway traffic scenarios encountered in the Yangtze River. They show that high complexity implies ship travel time sequences are neither periodic nor stochastic, but dependent on the evolution patterns of traffic encounters. A correlation analysis of traffic flow complexity with the number of maritime accidents is carried out, showing that higher traffic flow complexity may result in more unwanted events. It is therefore concluded that the proposed method may help to (1) differentiate traffic flow complexity accurately, indicating that the higher the complexity value is, the higher the irregularity and unpredictability of maritime traffic flow are, (2) provide helpful reference for optimizing traffic management over the life cycle of fleet operations as well as maritime safety management of high traffic flow complexity areas.

Analysis of Wildlife Roadkill in a Road Circuit. Case study of a Colombian road in the Department of Huila: Neiva - Rivera - Campoalegre

This research contributes information related to records of wildlife roadkill in the different roads of the department of Huila. The results come from samplings carried out during the rainy season from October to December of 2017 on the Neiva - Rivera - Campoalegre road circuit. The highest roadkill rate was recorded in section 1, Neiva - Rivera (Los Cauchos tollbooth); which had high traffic flow during the day (5045 vehicles/month), high speed limit (90 km / h), and an arboreal coverage that forms a green tunnel due to the lack of lighting on this road.
 A total of 102 dead specimens were registered in this case study; predominantly mammals (53 specimens, 51.96%) and the species Didelphis marsupialis (48, 47.06%), followed by reptiles (34, 33.33%) whose most affected species were the Boa constrictor (9, 8.82%) and the Iguana iguana (7, 6.86%). Additionally, birds were the third most affected group (12, 11.76%) classified in 8 species, such as the Megascops choliba which was the most affected (4, 3.92%). Amphibians were the least affected group (3, 2.94%), mainly the Rhinella horribilis species (2, 1.96%).

Voxel-RCNN-Complex: An Effective 3-D Point Cloud Object Detector for Complex Traffic Conditions

The complex traffic conditions and high traffic flow are big challenges to the perception of autonomous vehicles. As the basis of environmental perception technology, object detection based on point cloud is of great significance for the normal operations of autonomous vehicles. Considering the complex traffic conditions, in this work, we use the One millioN sCenEs (ONCE) dataset to train an effective 3-D object detector, namely Voxel-region convolution neural network (RCNN)-Complex. This is accomplished by modifying the Voxel RCNN to make it suitable for complex traffic conditions. We add the residual structures in the 3-D backbone and design a heavy 3-D feature extractor, which is conducive to extracting high-dimensional information. We also design a 2-D backbone composed of residual structures, self-calibration convolution, and spatial attention and channel attention mechanism; this expands the receptive field and captures more context information. As compared with the Voxel RCNN, the proposed Voxel-RCNN-Complex significantly improves the detection performance for long-distance and small objects. In order to further increase the robustness of the proposed model and alleviate category imbalance, we use a class-balanced sampling strategy (CBSS). We evaluate the proposed model using the ONCE dataset. The results show that the proposed model achieves an mAP of 65.34% and an inference speed of 13.8 FPS. The experiments show that the proposed model performs better than other methods on the ONCE dataset. This demonstrates the effectiveness of the proposed Voxel-RCNN-Complex. Moreover, we also test the proposed model in an intelligent vehicle platform on real roads.

Robustness Analysis of Discrete State-Based Reinforcement Learning Models in Traffic Signal Control

With the growing traffic congestion problem, more and more deep reinforcement learning (DRL) methods have been applied in traffic signals control(TSC). But researches show that DRL is very fragile with abnormal data. In this paper, special traffic state abnormal data (TSAD) are simulated, based on which the robustness of DRL is analyzed and improved for traffic signals control. Firstly, the perturbation noise is generated based on the Discrete Carlin&Wagner attack, which is then added to the normal data to simulate the TSAD. Secondly, under different type of TSAD, the robustness of DRL models for traffic signals control is explored, which are demonstrated to have certain vulnerability, especially with high traffic flows. Finally, induction model based on reward detection(IMR) and mask the activation values of decision neurons (MVN) are proposed to effectively improve the robustness of DRL models for traffic signals control.

A Comparison of Approaches for the Time Series Forecasting of Motorway Traffic Flow Rate at Hourly and Daily Aggregation Levels

Congestion forms a large problem in many major metropolitan regions around the world, leading to delays and societal costs. Congestion is generally associated with reduced average speed at a high traffic flow rate. This traffic flow rate is defined as the number of vehicles that pass a certain location at a given time. The modelling and prediction of this traffic flow rate may lead to valuable insights that may be used to reduce congestion and societal costs. This study aims to predict the traffic flow rate for 41 different locations in and around Amsterdam, The Netherlands. Using TBATS, SARIMAX and LSTM models, among others, the traffic flow rate of these locations has successfully been modelled. These models may provide accurate predictions for the future flow rate, which may be useful for the identification of infrastructure bottlenecks and the scheduling of maintenance. Considering the dramatic effects of the COVID-19 pandemic on the traffic flow rate, the inclusion of 2020 data with a number of external factors, could lead to an improvement of the results and the ability to model the future effects of the pandemic.

Analysis of Bus Passenger Demand and Supply: Case Study on Western Province, Sri Lanka

Buses carried about 47% of passengers crossing the Colombo Municipal Council (CMC) boundary in 2013. The Sri Lanka Transport Board (SLTB) and private bus companies operates roughly 680 intra-provincial bus routes and 400 inter-provincial bus routes in the Western Province according to the bus route information from the National Transport Commission (NTC, 2012) . The number of buses on the seven (7) major radial corridors carries more bus passengers than other roads in the Western Province. Kandy, Galle and Malabe Road corridors are the highest followed by High Level, Negombo, Horana and Low Level Road corridors. This research paper is an attempt to analyse the bus passenger demand and supply on seven major corridors connecting Western Province boundaries. The impact of the passenger demands and volumes from the seven major corridors and the traffic speed are the main outcome of this analysis. The present bus traffic information and the impact of the traffic congestion due to the high traffic flow on major corridors are discussed in the analysis. The research will also focus on alternative solutions and the importance of integrating other public transport modes to cater the demand from the major seven corridors for the better utilisation of public transport inside the Western Province boundaries.

Congestion Attack Detection in Intelligent Traffic Signal System: Combining Empirical and Analytical Methods

The intelligent traffic signal (I-SIG) system aims to perform automatic and optimal signal control based on traffic situation awareness by leveraging connected vehicle (CV) technology. However, the current signal control algorithm is highly vulnerable to CV data spoofing attacks. These vulnerabilities can be exploited to create congestion in an intersection and even trigger a cascade failure in the traffic network. To avoid this issue, timely and accurate congestion attack detection and identification are essential. This work proposes a congestion attack detection approach by combining empirical prediction and analytical verification. First, we collect a range of traffic images that correspond to specific traffic snapshots which are vulnerable to potential data spoofing attacks. Based on these traffic images, an improved generative adversarial network is trained to predict whether a forthcoming attack will cause congestion with a high probability. Meanwhile, we define a group of traffic flow features. After exploring features and conducting a thorough analysis, a TGRU (tree-regularized gated recurrent unit)-based approach is proposed to verify whether congestion occurs. When we find a possible attack that can cause congestion with high probability and subsequent traffic flows also prove congestion, we can say there is a congestion attack. Thus, we can realize timely and accurate congestion attack detection by integrating empirical prediction and analytical verification. Extensive experiments demonstrate that our approach performs well in congestion attack detection accuracy and timeliness.

Effectiveness of driver's bounded rationality and speed guidance on fuel-saving and emissions-reducing at a signalized intersection

To reduce the fuel consumption and emissions of drivers passing through signalized intersections, this research proposes a fuel-saving and emissions-reducing strategy at a signalized intersection which takes into account driver's bounded rationality and speed guidance, including the theoretical basis of strategy, the scenario division of vehicle speed guidance, and the solution of vehicle optimal trajectory. Drivers are divided into three types: aggressive, normal, and conservative. Bounded rationality is divided into three levels: low, medium, and high. And the 3 × 3 × 3 numerical simulation experiments are carried out under low, medium, and high traffic flow. The results show that when the speed guidance is received, aggressive drivers have the greatest fuel-saving and emissions-reducing benefits, followed by conservative drivers. When the bounded rationality level changes under high traffic flow or the level of traffic flow and bounded rationality change concurrently, the benefits will be greatly affected. The driver's bounded rationality harms fuel consumption and emissions, and this negative effect increases with the increase of traffic flow. Providing corrected speed guidance can effectively reduce the negative effect. This study can provide more effective guidance information for drivers in a manual driving environment.

Analysis and prediction of intersection traffic violations using automated enforcement system data

The automated enforcement system (AES) is an effective way of supplementing traditional traffic enforcement, and the traffic violation data from AES can also be effectively used for safety research. In this study, traffic violation data were used to analyze the influencing factors associated with traffic violations and to predict the probability of violations at intersections. The potential factors influencing violations include 24 independent factors related to time, space, traffic and weather. Results from a logistic model showed that the midday period, weekends, residential districts, collector roads, congested traffic conditions, high traffic flow, lower wind speed and low temperature would increase the probability of traffic violations. The probability of violations was predicted by the random forest algorithm, which was proven to be the best traffic violation prediction model among logistic regression, Gaussian naive Bayes, and support vector machine. Moreover, the proximity weighted synthetic oversampling technique (ProWSyn) method was applied to reduce the impact of the imbalance ratio (IR) and improve the model’s prediction performance. The receiver operating characteristics (ROC) curves and Precision-Recall (PR) curves illustrated that the random forest algorithm using oversampling data had the best classifier prediction performance than undersampling data. The area under curve (AUC) and out-of-bag (OOB) error with IR = 1 reached 0.914 and 0.0787, which showed the better performance of the random forest algorithm using ProWSyn in dealing with imbalanced traffic violation data.

Evaluation of transportation network in AL- Fallujah city

The city of Fallujah suffers from bad design in their network and it still dominated by the same pattern of the road and street network system that was produced by the previous stages of the development of the city, which is awaiting the necessary and appropriate solutions, which calls for planning to modernize the road network and streets in it that can accommodate the reality of the city’s condition and the proposed expansions for its subsequent urban growth. The transportation network in Fallujah city was chosen as a case study, the network was divided into roads and intersections, the evaluation included two main roads and eleven sectoral roads, eleven arterial roads, and twenty-five intersections. The network was evaluated in three stages, the first stage was traffic flow and service level, the second stage was evaluating the network in terms of road and intersections marking, while the third stage concerned with evaluating the network in terms of sustainability. The HCS 2010 program was applied to evaluate the first stage, while the second and third stages were evaluated based on the field survey. The results of the first stage showed that most parts of the network in the northern zone suffer from traffic problems and have a low level of service, while most parts of the network in the southern zone have a high service level and enjoy high traffic flow. Most parts of the network were suffered from bad marking, which causes many problems for the users of this network. Related to sustainability, we note a lack of interest on the part of designers or decision-makers. It was concluded that traffic solutions should be economically feasible for some parts of the network, which would lead to improving the network’s performance at the level of the three stages.

ROTATING SPEED BREAKER SURFACE AERATOR SEWAGE SYSTEM

In this project we are trying to utilize one transport medium that is road speed breaker. Aeration of sewage in sewer pipeline's/ channel’s carried out by replacing the traditional speed breakers with some simple mechanism. The present invention relates generally to mechanisms for infusing air from the atmosphere into Sewage network pipelines. In this project we are trying to utilize friction between tires and road pavement. As vehicles pass over the speed breakers, they rotates the rollers/rotar (hump of speed breaker) which are connected to a gear mechanism which further connected into sewer pipeline ,In this unit the paddles are connected which drains out the sewage. This method is an effective way to drained out the sewage in very less time as the numbers of vehicles on the road are ever increasing. Also the cost of fabrication of the model is low. It can be effectively placed near high volume traffic flow. This method provides an efficient way to clean the sewage by aeration process from the channel in very less time and having large discharge as compare to existing one from the kinetic energy of moving vehicles on roads.

Exploring the effects of connected and automated vehicles at fixed and actuated signalized intersections with different market penetration rates

ABSTRACT To investigate the effects of different market penetration rates (MPRs) of intelligent vehicles – Intelligent Driving Model (IDM) for autonomous vehicles (AVs), Adaptive Cruise Control (ACC) for AVs, and Cooperative Adaptive Cruise Control (CACC) for connected and automated vehicles (CAVs) – in mixed traffic flows with human driving vehicles (HDVs) at intersections, three signalized intersections (fixed signal, gap-based actuated signal, and delay-based actuated signal-controlled intersections) with low, medium, and high traffic demands are investigated. The simulation results indicate that CAVs with the CACC system outperform AVs with ACC or IDM systems and could reduce the average delay under low and high demand scenarios by 49% to 96%. CAVs with the CACC system could also significantly reduce average delay with a 20% MPR, while significant drops could only be observed after 60% and 80% MPRs for AVs with the ACC/IDM system. Gap-based and delay-based actuated signal control schemes are preferred under medium traffic flow demand, and CACC/ACC systems could significantly improve the performance of actuated signal-controlled intersections under high traffic flow demand.

Pollution and health risk assessment of arsenic in street dust and soil from an industrial zone

Taking an industrial area in Wuhan as the research object, single factor index, Geoaccumulation index and EPA health risk model are utilized to evaluate the pollution pattern and health risk of arsenic (As) in street dust with different particle fractions and soil. The results showed that the content of As in street dust increased with the decrease of particle size. The average content of As in street dust with fine particle fraction and soil exceeded the soil background value of Hubei Province, but did not exceed the screening value of “Soil Environmental Quality Construction Site Soil Pollution Risk Control Standards (Trial)”. The content of As in soil had a high correlation with that of dust with < 63 particle fraction at the corresponding point, with high fit degree (R2=0.6012). There was moderate to heavy pollution of As in areas surrounding industrial enterprises like Wuhan Iron and Steel, cement plants, and areas with high traffic flow and construction sites. The As of street dust and soil at some points posed a non-carcinogenic risk to children, but no carcinogenic risk. The ingestion pathway was the largest non-carcinogenic exposure route of As in street dust and soil from the research area.

Analysis of culturable airborne fungi in outdoor environments in Tianjin, China

BackgroundFungal spores dispersed in the atmosphere may become cause of different pathological conditions and allergies for human beings. A number of studies have been performed to analyze the diversity of airborne fungi in different environments worldwide, and in particular in many urban areas in China. We investigated, for the first time, the diversity, concentration and distribution of airborne fungi in Tianjin city. We sampled 8 outdoor environments, using open plate method, during a whole winter season. Isolated fungi were identified by morphological and molecular analysis. Environmental factors which could influence the airborne fungi concentration (temperature, humidity, wind speed, and air pressure) were monitored and analyzed. The effect of different urban site functions (busy areas with high traffic flow and commercial activities vs. green areas) on airborne fungal diversity was also analyzed.ResultsA total of 560 fungal strains, belonging to 110 species and 49 genera of Ascomycota (80 %), Basidiomycota (18 %), and Mucoromycota (2 %) were isolated in this study. The dominant fungal genus was Alternaria (22 %), followed by Cladosporium (18.4 %), Naganishia (14.1 %), Fusarium (5.9 %), Phoma (4.11 %), and Didymella (4.8 %). A fungal concentration ranging from 0 to 3224.13 CFU m− 3 was recorded during the whole study. Permutational multivariate analysis showed that the month was the most influential factor for airborne fungal community structure, probably because it can be regarded as a proxy of environmental variables, followed by wind speed. The two analyzed environments (busy vs. green) had no detectable effect on the air fungal community, which could be related to the relatively small size of parks in Tianjin and/or to the study season.ConclusionsOur study shed light on the highly diverse community of airborne fungi characterizing the outdoor environments of Tianjin, and clarified the role that different environmental factors played in shaping the analyzed fungal community. The dominant presence of fungi with potential hazardous effect on human health, such as Alternaria, Cladosporium and Naganishia, deserves further attention. Our results may represent a valuable source of information for air quality monitoring, microbial pollution control, and airborne diseases prevention.

Assessing the effects of link-repair sequences on road network resilience

Disruptions to transport networks are inevitable and detrimental to the functioning of society. Improving the resilience of transport networks to disruptive events has, therefore, a significant impact on society. Although the resilience of a transport system depends on the ability of the network to sustain the consequences of initial disruption (i.e. robustness) and quickly recover its performance (i.e. rapidity), the latter attracted less attention than robustness. The present paper focuses on quantifying the impacts of recovery processes and, more specifically, link-repair strategies on resilience. Several link-repair strategies are compared across a multitude of perturbation scenarios in the well-known Sioux Falls network. The strategies considered include: (i) the optimal (minimising the disruption consequences over the recovery process), (ii) average (representing a recovery process where the disrupted links are repaired in random order), (iii) flow-based (where the links with the highest traffic flow in the undisrupted network are repaired first), and (iv) criticality-based (where the links whose individual failure result in the highest impacts on the system performance are repaired first) recovery. The results of this comparison are subsequently used to evaluate the correlation between robustness and resilience, and characterise the optimal repair strategy.

Traffic management at landslide disaster in West Sumatera and its impact to passenger and drivers

West Sumatra is one of Indonesia province that always experiences landslides during the rainy season. Based on data from BNPB, in the last 10 years, 166 landslides have occurred in West Sumatra. The landslide materials covers partially and even the entire road wide, so it interferes the traffic flow activities in the lane. This study aims to identify traffic management that is carried out in the landslide disaster zone, the impacts arising from landslides are identified. The study was conducted by exploring the experiences of drivers and passengers when using vehicles in the West Sumatra. Structured questionnaires were created and distributed online and directly to respondents. From the results of data analysis, it was obtained that landslide most often occurred in the Padang-Solok road at Sitinjau Lauik region and in Padang-Padang Pariaman road at Silaiang region. These two routes have high traffic flow. Majority of landslide materials are soil, it causes traffic congestion. Traffic management by opening and closing oneway roads is a type that is mostly conducted to reduce traffic congestion, this activity is carried out by the police and the people around the location. The most impact that experienced by driver and passenger during waiting for cleaning the landslide material were tired and loss ot time.

Atmospheric pollutants sources, health risk assessment study at a commercial, urban and traffic site

Ambient air pollutants have detrimental effects on human health and ambient air quality in central Taiwan is worsening. The aims of this study are as follows: (1) Measure the ambient air concentrations and dry deposition fluxes of particulates at a mixed commercial, urban and traffic sampling site in Luliao. (2) Identify the metallic elements that are attached to the particulates at this mixed sampling site. (3) Discuss the effects of ambient air pollutants (metallic elements that are attached to the particulates) on the health of local people using contamination factors and degrees of contamination [Ghosh et al. (2018). Source and chemical species characterization of PM10 and human health risk assessment of semi-urban, urban and industrial areas of West Bengal, India. Chemosphere 207:626–636]. The mean total suspended particulate concentrations were highest in the winter and lowest in the summer. The deposition fluxes were highest in the autumn and lowest in the summer. ANOVA results revealed no significant seasonal variation in the concentrations or dry depositions of particulates and metallic elements (Al, Cd, Cr, Mn, Ni, Pb and Zn) at the sampling site. Cu was the only exception, as its concentration varied seasonally. Degrees of contamination and contamination factor values for metallic elements Cd, Cr, Cu, Mn, Ni, Pb and Zn were low. Most of the metallic elements – Zn, Cr, Ni, Cd, Pb and Al – were locally emitted. Local residents close to the site faced no immediate carcinogenic or other health-related risk. Taichung World Flora Exposition was held in Taichung city and lasted as long as six months, and traffic flow increased significantly during this period. Hence, high density traffic flow during the Taichung World Flora Exposition might have been responsible for the high concentration and seasonal variations concentrations of metallic elements Cu and Mn at this time.

Management of Compound Depressed Fractures Over Major Cranial Venous Sinuses

Background: Incidence of trauma increased both in developing and developed countries especially in congested cities because of high traffic flow. This makes it a worldwide health and social issue. Furthermore, depressed skull fractures occur over venous sinuses in 11% –18% of cases, representing a fairly large proportion of these cases. Objective: To characterize the demographic, clinical and radiological findings of patients with depressed fractures overlying cranial dural sinuses that we have faced in our institute at Sohag University Hospital. Patients and Methods: This retrospective and prospective study was conducted on 50 patients with compound depressed fracture over venous sinuses, which were treated either surgically or conservative at Sohag University Hospitals. Results: Despite surgical group included patients with neurological deficit and impaired level of consciousness compared to conservative group; surgical group had the same outcome as the conservative group. CNS infection was not recorded in both groups and the superficial infection was significantly higher in the conservative group. Mortality related to the treatment modality was not recorded in our study. Conclusion: Both surgical and conservative treatment of compound depressed fracture over major cranial venous sinuses had a good outcome as regards morbidity and mortality. Risk of CNS infection is not high but surgical treatment can significantly decrease the risk of infection compared to the conservative treatment.

The Effect Of Road Narrowing On The Traffic Characteristics

A problem found in transportation is road narrowing. Road narrowing refers to a condition in which its downstream is smaller than the upstream. This research took place on Ahmad Yani Street at the front of Royal Plaza, Surabaya. The location of this research had a sufficiently high traffic flow. Thus, the road should be able to operate optimally. In fact, there is still a density caused by road narrowing. This research was intended to determine how much the maximum flow, maximum density and free speed on the road before, during and after the narrowing. Besides, this research was carried out to find out the relation of the flow, the traffic density and speed, determine the value of the shock waves during the road narrowing. This research was done on Wednesday and Saturday morning, at 06:00-08:00 and in the afternoon at 16:00-18:00. The calculation performed was based on Greenshield method. The analysis revealed that the largest maximum flow was on the fragment of road before narrowing, which was 2376.30 pcu/hour. The maximum density found on the fragment of road during narrowing was 322.33 pcu/hour, and the highest free speed regarding to the road condition before the narrowing was 57.21 km/hour. The relation between flow, speed and density showed a significant result (R2&gt; 0.5). Shock waves obtained were in the mornings and afternoons on Wednesday and Saturday,