Vehicular Flow Research Articles

Identification of key determinants of personal safety perception at bus stops using proportional odds logistic regression

Complex vehicle-pedestrian interaction near the bus stop affects the safety perception of users, but the subjective nature of perceived safety and the lack of specific measurement techniques makes its estimation further laborious. This paper identifies factors influencing safety perceptions of bus users by employing Ordered Logistic Regression analysis. The study focussed on five dimensions; bus stops' design and surrounding facilities, traffic characteristics, and travellers' individual, travel and accident characteristics. The results demonstrated that increased vehicular flow, absence of footpath, crossing facility and safety barrier would scale down the perceived safety. Furthermore, the respondent's age, education, frequency of travelling by bus, familiarity with the bus stop, and previous accident experience are significant predictors of perceived safety. Results concluded that females perceived less safe, and no effects can be attributed to the household vehicles and income. Regarding road shoulder width, 1-2 meters is the most preferred width from the travellers' safety perspective.

Spatial Analysis with Weighted Kernel Groupings to Determine Risk Sectors Due to Traffic Accidents in Urban Area. Tunja Analysis, Colombia

A method is presented to identify and determine groups with risk sectors due to the greater occurrence of traffic accidents in urban areas as an integral component in road safety management. The methodology was framed in Spatial Analysis with geographic statistics based on Exploratory Data Analysis (AED), Kernel Density Estimation (KDE), and the application of correlation and geoprocessing techniques. The accident data collected between 2015 and 2018 from the urban area of ​​Tunja, Boyacá, Colombia, were the basis for the study of the distribution of events, characterization of clusters, occurrence dynamics and pattern modeling. The definition and delimitation of risks depended on the dispersion or grouping (Hotspots) found with weighted Kernel together with the socio-spatial interrelation of underlying processes due to the territorial dynamics of the sector. The results reveal patterns of events in concentration foci with different levels of risk, in which land uses of opposite characteristics coexist according to their activities [commercial and residential], socioeconomic sectors of low strata with a mixture of arterial road network that by its functionality mobilizes high vehicular and pedestrian flows. Although the analysis is limited to a case study, the findings show a promising perspective in road safety by delimiting risk sites for traffic accidents through the incidence of territorial variables.

Operational Assessment of Speed Control Measures on Capacity of Urban Roads in Metropolitan Area of Barranquilla, Colombia

With the aim to reduce accident rates and assist in pedestrian traffic, in the city of Barranquilla (Colombia), electronic devices for speed control (speed cameras) have been installed on roads of high vehicular flow with difficulty in pedestrian transit. Traffic Calming Measures are described in the literature as a set of measures to regulate traffic on roads, ensure mobility, and reduce accidents. This article focuses its study on the impact of Traffic Calming Measures through electronic devices on urban or inner cities roads (capacity and operating speed on them). This study centers in the evaluation of the operational impact of speed cameras and the data of vehicular speed and flow collected through them in four main roads of the city, with the purpose of estimating models that establish relationships of speed-flow, and analyzing the impact of these Traffic Calming Measures on the vehicular capacity of urban roads. In the estimation of road capacity, a Greenshields model was applied, with which via speed–density and flow-density relationships, we aim to determine how operational transit is affected by the use of speed cameras. Conclusions show that operational transit is affected by diminishing road capacity between 7 to 41 percent and these Traffic Calming measures are ineffective to ease pedestrian traffic as is expected.

Control and allocation at an intersection with traffic lights

Managing road infrastructure in highly urbanized areas during the Industry 4.0 era poses a significant technological challenge for traffic engineers. Steadily growing traffic volume, both of motor vehicles and pedestrians, cyclists or scooters, necessitates the development of advanced traffic control algorithms and systems. Improvement of the efficiency and capacity of intersections without any intervention into the physical structure of roadways is one of the two aspects of today's traffic engineering. In this paper, however, emphasis is placed on the aspect of coordination of conflicting flows of motorized and pedestrian traffic. Consideration is given to ensuring that each traffic light phase at an intersection is maximally utilized while maintaining the required safety factor. The empirical part of the study consists in identifying inefficiencies in the traffic light cycle. The analysis of traffic phases has revealed that there were certain periods in the cycle during which pedestrians were given the right of way while, in fact, it was not necessary. The study proposes a solution to optimize the green signal timing for conflicting vehicular and pedestrian flows in real-time. By eliminating delays in traffic signal phases as a result of not having to give a green signal for pedestrians, the proposed solution will improve the efficiency of urban networks with respect to an aspect whose potential has not been exploited so far. Coordination and adaptation of each light phase to the most effective extent is a feasible answer to the needs and requirements of modern urban areas.

Deep Reinforcement Learning for the Co-Optimization of Vehicular Flow Direction Design and Signal Control Policy for a Road Network

Reinforcement Learning (RL) is a popular approach for deciding on an optimum traffic signal control policy to alleviate congestion in a road network. However, the traffic signal control policy can also be optimized in conjunction with the design of vehicular flow directions to further improve traffic performance. The design of vehicular flow directions refers to the right of way or directional restriction imposed in a road network. Here, a new RL-based technique is presented for co-optimization of the design of vehicular flow directions and control policy for traffic signals. This technique consists of a two-step iterative process, wherein a set of vehicular flow directions for a road network is generated, then a RL-based approach is used to train the traffic signal control policy over the given set of vehicular flow directions. Following the proposed technique, the vehicular flow directions with poor traffic performance are iteratively eliminated, while new vehicular flow directions are generated to achieve better traffic performance and realize convergence to a maximum possible expected traffic performance. The proposed RL-based technique is evaluated by using two examples under rush hour and non-rush hour traffic conditions. It is found that, compared to a RL-based approach in which only traffic signal control policy is considered, the proposed approach can be used to obtain a better traffic performance in terms of vehicular queue length and throughput.

Impacts of Down-Up Hill Segment on the Threshold of Shock Formation of Ring Road Vehicular Flow

Impacts of Down-Up Hill Segment on the Threshold of Shock Formation of Ring Road Vehicular Flow

Multisource–Multidestination Optimal Energy Routing in Static and Time-Varying Vehicular Energy Network

A vehicular energy network (VEN) uses electric vehicles (EVs) to transport energy across a wide geographical area. EVs can charge and discharge wirelessly at road junctions while moving and, thus, transfer energy between junctions. In this article, we propose a method to optimally route energy from multiple energy-supplying junctions to multiple energy-demanding junctions while minimizing energy loss in four different VEN scenarios: 1) a time-invariant VEN; 2) a VEN with time-varying vehicular flows and energy demands; 3) a VEN with time-varying vehicular flows and time-averaged demands; and 4) a VEN with significant storage capacities at junctions. The method employed to solve these scenarios is to model the VEN as a graph specific to each scenario, and then solve the generalized flow problem on the graph. Simulations are performed on all four scenarios and show that transmission efficiency improves when a small number of long vehicular routes are introduced, and when storage capacities at junctions increase. The error in approximating a time-varying VEN as a static VEN is also investigated.

Analyzing roadway work zone effects on vehicular flow in a freeway ring

Roadway work zone forms as a result of traffic accidents or road maintenance. In this paper, to analyze roadway work zone effects on vehicular flow in a freeway ring, a macroscopic multi-lane traffic model is proposed, the model describes the mandatory net lane-changing rate just upstream the roadway work zone with a random number model based on golden section analysis, and the net-changing rate in normal road segment with a lane-changing time model. Assuming that the free flow speeds on lanes I–III are 120, 100 and 90[Formula: see text]km/h, respectively, with a numerical method of third-order accuracy, the model equations are solved numerically to simulate vehicular flows in a three-lane freeway ring with a roadway work zone with a total length of 160[Formula: see text]m and lane III completely banned. Numerical results show that the roadway work zone generates traffic shock when initial density normalized by jam density is around 0.18. While the ramp flows have little effect on mean travel time through the freeway ring road with a total length of 100[Formula: see text]km, but can cause observable deviation of the root mean square value of travel time.

Dynamic grouping of vehicle trajectories

Vehicular traffic volume in large cities has increased in recent years, causing mobility problems; therefore,the analysis of vehicle flow data becomes a relevant research topic. Intelligent Transportation Systems monitor and control vehicular movements by collecting GPS trajectories, which provides the geographic location of vehicles in real time. Thus information is processed using clustering techniques to identify vehicular flow patterns. This work presents a methodologycapable of analyzing the vehicular flow in a given area, identifying speed ranges and keeping an interactivemap updated that facilitates the identification of possible traffic jam areas. The results obtained on threedata sets from the cities of Guayaquil-Ecuador, RomeItaly and Beijing-China are satisfactory and clearlyrepresent the speed of movement of the vehicles, automatically identifying the most representative ranges inreal time.

Analyzing work zone effects on vehicular flow on an annular freeway with a tunnel

This paper develops a three lane continuum model to analyze the effects of a work zone on vehicular flow on an annular freeway with a tunnel. The model expresses the mandatory lane changing rate just upstream of the work zone in an explicit algebraic form with the relevant random parameter generated from golden section analysis, and describes the discretionary lane changing rate between adjacent lanes with a lane changing time depending on local traffic flow density and relaxation time. It is assumed that the annular freeway has three lanes, a work zone with a length of 0.2 km and lane II completely blocked, an upstream tunnel of 1.5km long, and an initial jam between the tunnel and work zone. The three lane continuum model is applied in vehicular flow simulation with a 3rd order accuracy numerical scheme. Numerical results also indicate that golden section application in the analysis of work zone effects is helpful in obtaining density thresholds of traffic jam formation, the time averaged traffic speed through the tunnel, dependencies of mean travel time, and vehicle fuel consumption on the initial density normalized by jam density. Numerical results reveal that there are two density thresholds of traffic jam formation, if both density thresholds are normalized by traffic jam density, the first threshold relating to the work zone is 0.14, while the second depending on the tunnel is 0.21. In the absence of a work zone, the mean travel time through lane I is slightly longer than that estimated for cases with a work zone. As soon as initial density is above the second threshold, the time averaged speed through the tunnel is 31.91 km/h, which agrees well with published data.

Ambulance detection for smart traffic light applications with fuzzy controller

<p>In the development of intelligent cities, the automation of vehicular mobility is one of the strong points of research, where intelligent traffic lights stand out. It is essential in this field to prioritize emergency vehicles that can help save lives, where every second counts in favor of the transfer of a patient or injured person. This paper presents an artificial intelligence algorithm based on two stages, one is the recognition of emergency vehicles through a ResNet-50 and the other is a fuzzy inference system for timing control of a traffic light, both lead to an intelligent traffic light. An application of traffic light vehicular flow control for automatic preemption when detecting emergency vehicles, specifically ambulances, is oriented. The training parameters of the network, which achieves 100% accuracy with confidence levels between 65% with vehicle occlusion and 99% in direct view, are presented. The traffic light cycles are able to extend the green time of the traffic light with almost 50% in favor of the road that must yield the priority, in relation to not using the fuzzy inference system.</p>

Noise mapping and variance of road traffic noise: Identification of most noise impacting vehicular type in an urban region

Urban road traffic noise is a major concern in developing as well as developed countries. Often it is difficult to identify the most noise impacting vehicular type especially in urban region with mixed vehicular flow. Herein, we analysed in a systematic way to identify the most noise impacting vehicular type at Hyderabad city of India. The road traffic noise across the corridor-3 metro line known as the blue line metro was chosen in the present study because, it stretches from north to south connecting 23 stations comprising major residential and commercial locations of the city. The noise levels were analysed as per CPCB guidelines. The noise pollution quantifying parameters such as Noise Climate (NC), Noise Pollution Level (LNP), and Traffic Noise Index (TNI) were analysed across the lane. A systematic analysis revealed that, the twowheelers are the most noise impacting vehicles in the daytime whereas four-wheelers in the nighttime. Noise map generated using the IDW spatial interpolation method shows the noise impacted regions across the metro lane stretching ~27 km of the city. The methodological pattern in the present investigation can be useful tool in identifying the most noise impacting vehicular type in any region with a mixed vehicular flow.

Analyses of lattice hydrodynamic area occupancy model for heterogeneous disorder traffic

In developing countries, traffic not only consists of a wide range of vehicles, including automobiles, trucks, buses, motorbikes, etc. but is also disordered. Controlling and managing increasingly complex transport networks depend heavily on modeling the mechanics of mixed (heterogeneous) traffic. In heterogeneous disordered traffic, every vehicle has its size and speed, and even they are different from each other in the case of occupying the area on the road, so these can affect the overall movement of vehicular flow. Therefore, a new lattice model is designed by considering the area occupancy of different vehicles in a heterogeneous disorder traffic system with a variable proportion of slow-moving to fast-moving automobiles. In addition, stability analysis is done to investigate the ability of a heterogeneous traffic model. The mixed traffic phase diagrams show a link between traffic stability and the fraction of vehicles. Moreover, a reduction perturbation approach is used to explore the behavior of the disordered traffic, and the mKdV equation is achieved near the critical point. Furthermore, numerical simulations are performed to verify the consistency of theoretical analysis. Results portray that a higher fraction of small vehicles is beneficial for stabilizing the traffic flow.

Design and Implementation of Intelligent Traffic Control System using Programmable Logic Controller

Generally, traffic light systems are regarded as open loop control systems, that is, they are in continuous operation without any form of feedback that can help the system take a decision based on certain conditions. And so, this is specifically part of the reason why there exist high vehicular densities at roundabouts. Having considered in providing a solution to this problem, this project integrated a 4I/O Programmable Logic Controller (PLC) into the traffic light system circuitry which provided feedback based on signals received from the input sensors connected to the PLC. When these sensors get energized due to the presence of a vehicle, it sends an ON-bit signal to the PLC through the input port terminating the sensor and the PLC. This signal in turn triggers the output port mapped in the microprocessor so that it energizes the Light Emitting Diodes (LEDs). During simulation, two forms of control were used: Primary (default) and Secondary control systems. On the secondary control, the PLC receives signal from the ultrasonic sensor on road tracks A and B then allows long queued vehicles to pass while it stops vehicular movement on road track C and D and vice versa. It is identified that this method of traffic light control has helped to ensure orderliness and evenly distributed vehicular flow at case study roundabout.

Vehicular Traffic Flow Characterization: An Edge Computing Perspective

With rapid urbanization, road network inefficiencies have become a primary impediment for developing sustainable smart cities. Associated challenges range from traffic congestion, ambient pollution, accidents, and lost productivity. In this regard, intelligent transportation system (ITS) based solutions are being proposed to design and develop smart urban mobility. However, real-world traffic flow parameters (such as vehicular count, flow, classification, speed, road capacity, time/distance headway, temporal/spatial densities, heatmaps, and trajectories) are fundamental building blocks for designing and developing ITS solutions. In existing literature, varying solutions have been proposed for traffic flow characterization. These can be categorized as either intrusive or non-intrusive sensors. However, these solutions have serious limitations, especially under heterogeneous traffic flow behavior. To overcome these limitations, compute vision-based solutions have emerged as optimum traffic flow characterization solutions. In this work, all compute vision-based edge computing solutions in existing literature have been reported and analyzed. Through comparative analysis, it is concluded that edge computing solutions are the optimum choice as compared to Internet-of-Video-Things based solutions. However, edge computing solutions are seriously constrained because of the compute resources of single board computers. To overcome this limitation, mathematical traffic flow characterization equations have been reported for calculating eight additional traffic flow parameters. These mathematical equations can optimize the already proposed edge computing solution’s performance by 400%.

A new at-grade transportation network without conflict movement at intersections

This research aims to propose a new form of transportation network, the Chet network, to facilitate vehicular flow within a new area of built environment. One- and two-way links are uniquely arranged to form hexagonal blocks, such that vehicles can move from one place to another without facing any conflict in movement at intersections. The proposed network maintains a low-cost at-grade infrastructure, but does not require stop signs or traffic signals, which can delay traffic. Hence, the mobility performance of the proposed network is expected to be better than that of a traditional grid network. A proof-of-concept is conducted through microscopic traffic simulation, in order to take into account individual driving behaviors. The numerical results are very impressive. Discussions regarding practical issues are also provided. Nevertheless, the Chet network is original. It can be considered as an innovative design that could change the way of how people live and travel.

Anthropogenic Vehicular Heat and Its Influence on Urban Planning

Anthropogenic heat (QF) is one of the parameters that contributes to the urban heat island (UHI) phenomenon. Usually, this variable is studied holistically, among other anthropogenic flux such as industrial, vehicular, buildings, and human metabolism, due to the complexity of data collection through field measurements. The aim of this paper was to weigh vehicular anthropogenic heat and its impact on the thermal profile of an urban canyon. A total of 108 simulations were carried out, using the ANSYS Fluent® software, incorporating variables such as the number of vehicles, wind speed, urban canyon orientation, and urban canyon aspect ratio. The results were compared with a database of 61 American cities in 2015 and showed that orientation is the main factor of alteration in vehicular heat flow, increasing it in a range of 2 °C to 6.5 °C, followed by the wind speed (1.2 to 2.2 m/s), which allows for decreases of 1 to 3.8 °C. The exploration of these variables and their weighing in the definition of urban street canyon temperature profiles at the canopy level of urban structures provides valuable information on the hygrothermal comfort of its inhabitants; its appropriate quantification can be an example of many urban energy balances altering processes.

Nitrogen Dioxide Monitoring In Urban Areas of Lahore, Pakistan

Nitrogen dioxide (NO2) plays significant role in atmospheric chemistry mainly in secondary air pollutants formation which consequently result in environmental acidification. It has adverse impact on human health and considered as the second most harmful air pollutant after PM10 in major cities of Pakistan including Lahore. In this study, 15 major urban sites of Lahore with respect to vehicular flow were focused during rush hours from 1:30 pm to 9:30 pm for the monitoring of NO2 level. Chemiluminescence technique was applied to identify NO2 concentrations by using Horiba APNA-370 monitor. For sampling, four months of winter season November 2016 to February 2017 were selected and measured monthly average mean values; associated meteorological conditions like temperature, wind speed, rainfall and relative humidity were also monitored. A spatial distribution map of different locations for NO2 concentrations was developed by using geostatistical tool ArcGIS. The highest NO2 values near the main roads were mainly due to intense traffic flow and vehicular emissions unlike residential and commercial locations. Moreover, the NO2 level exceeded the NEQS standards at most of the sampling points during study. Therefore, it is mandatory to take desired steps in order to develop effective mechanism to control air pollution before it becomes a serious hazard for human beings living in urban areas.

Multispecies and high-spatiotemporal-resolution database of vehicular emissions in Brazil

Abstract. In this article, we present the BRAzilian Vehicular Emissions inventory Software (BRAVES) database, a multispecies and high-spatiotemporal-resolution database of vehicular emissions in Brazil. We provide this database using spatial disaggregation based on road density, temporal disaggregation using vehicular flow profiles, and chemical speciation based on local studies and the SPECIATE 5.1 database from the United States Environmental Protection Agency (US EPA). Our BRAVES database provides hourly and annual emissions of 41 gaseous and particle pollutants, where users can define the spatial resolution, which ranges from a coarse to a very refined scale. Spatial correlation analysis reveals that the BRAVES database reaches better performance than the vehicular emissions inventory from the Emissions Database for Global Atmospheric Research (EDGAR). A comparison with the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) surface concentration confirms the consistency and reliability of the BRAVES database in representing the spatial pattern of vehicular emissions. Compared to EDGAR, the BRAVES database brings more spatial, temporal, and chemical details. These additional features are crucial to understanding important atmospheric chemistry processes in Brazil. All codes and inputs are freely available, and the outputs are compatible with the input requirements of sophisticated chemical transport models. We envision that our database will enable the scientific and environmental community to gain new insights into vehicular emissions and their effects in Brazil, where emissions inventories are scarce and urgently needed. The BRAVES database is freely available at https://doi.org/10.5281/zenodo.6588692 (Hoinaski et al., 2022).

Pedestrian behavior in signalized intersections: Santiago deQuerétaro

Twenty-six percent of worldwide road fatalities are pedestrians, and the state of art suggests that not following the traffic signals by pedestrians is one of the most common causes of accidents. Therefore, this research estimates on one hand, through an observational study, four models to establish the significant variables in the pedestrians' obedience of traffic signals in a signalized intersection. On the other hand, it was proven through surveys, the level of road safety knowledge and how the socioeconomic factors influence the probability that pedestrians obey traffic signals and do not engage in risky behaviors. For the observational study, the variables analyzed are the pedestrian characteristics, obedience to signs, vehicle interaction, the time of day, and the infrastructure. The existence of vehicular flow, that the pedestrian crossing is obstructed and that the pedestrian waits in a group, are the variables with the greatest influence on the probability that the pedestrian does not assume risky behaviors when crossing. The factors that influence the probability of obeying the pedestrian traffic light are the existence of vehicular flow, the user running, and the time of the day; factors for the compliance of the pedestrian crossing are that the crossing is obstructed, the number of lanes, and the presence of vehicular flow; while for the probability of running, factors for compliance are obedience to the traffic light, that the user crosses in the group, and the location of the pedestrian crossing. This study is a first approach to estimate the variables that influence the observance of traffic signals and risk behaviors.