Vehicle Obstructions Research Articles

Design of Space Efficient Electric Vehicle Charging Infrastructure Integration Impact on Power Grid Network

With an ever-increasing number of electric vehicles (EVs) on the roads, there is a high demand for EV charging infrastructure. The present charging infrastructure in the market requires a lot of space and sometimes leads to traffic congestion, increasing the risk of accidents and obstruction of emergency vehicles. As the current infrastructure requires ample space, the cost of setting up this charging infrastructure becomes very high in metropolitan cities. In addition, there are a lot of adverse effects on the power grid due to the integration of EVs. This paper discusses a space-efficient charging infrastructure and multi-agent system-based power grid balance to overcome these issues. The proposed multi-level EV charging station can save a lot of space and reduce traffic congestion as more vehicles can be accommodated in the space. Depending on the size, capacity, and type of multi-level vehicle charging system, it can serve as a reliable charging solution at sites with medium and high daily footfall. We integrated the EV charging station with IEEE 33 bus test system and analyzed the grid and charging stations. The proposed scheme is exhaustively tested by simulation in a discrete-time event simulator in MATLAB and analyzed with varying EV arrival rates, time periods, etc.

Occluded Vehicle Detection via Multi-Scale Hybrid Attention Mechanism in the Road Scene

The obstruction of vehicles by surrounding vehicles, obstacles, etc. is a common phenomenon in the practical application of automatic driving. In view of the problem that the vehicle’s vision is affected by the occlusion, the vehicle feature information is incomplete, resulting in the low detection accuracy of the occlusion vehicle, and the occlusion vehicle detection method based on the multi-scale hybrid attention mechanism is proposed. The paper aims to fully excavate the advantages of multi-scale feature extraction, channel/space attention and other modules, and to design a multi-scale hybrid attention module suitable for occlusion vehicle detection to improve the detection accuracy of occlusion vehicles. Multi-scale features are enriched by the grouping convolution of different sizes of multi-scale feature extraction networks, and the parallel connection channels and spatial attention modules form different scale hybrid domain attention modules, which enhance the local feature information of the occluded vehicles and realize the reinforcement learning of multi-scale features and the suppression of occlusion interference information. Experimental results show that in the self-made occlusion vehicle dataset and the BDD100K occlusion vehicle dataset, the average mean accuracy of this method is 95.2% and 59.3%, respectively, which is 1.5% and 2.9% higher than that of the baseline network YOLOv5, respectively.

Measurements and Cluster-Based Modeling of Vehicle-to-Vehicle Channels With Large Vehicle Obstructions

A reliable vehicle-to-vehicle (V2V) channel model is necessary for intelligent transportation systems (ITSs) design. Due to the high mobility of vehicles and the low heights of antennas, the line-of-sight (LOS) propagation paths in V2V communications are more likely to be obstructed by large vehicles such as buses. Therefore, it is worthwhile to conduct in-depth investigations on obstructed line-of sight (OLOS) propagation channels caused by vehicle obstructions. In this paper, actual V2V channel measurements with large vehicle obstructions at 5.9 GHz band are conducted. Based on the measured data, it can be found that the obstructions of large vehicles not only cause additional attenuation, but also significantly affect the angular distribution of multipath components (MPCs). In addition, a cluster-based dynamic V2V channel model is proposed for OLOS scenarios. In the proposed model, the influences of vehicle obstructions on path loss, delay and angle dispersion are intuitively embodied as changes in the statistical distribution of MPCs clusters. Finally, the rationality and accuracy of the proposed model is validated by comparing the measured and simulated channels. The results in the paper are useful for enriching the understanding of V2V channels and provide supports for vehicular communication systems design and performance evaluation.

Machine-Learning-Based Scenario Identification Using Channel Characteristics in Intelligent Vehicular Communications

Scenario identification plays an important role in improving communication system performance. Considering that the scenarios of vehicle communications are dynamic due to movements of vehicles, and there are obvious differences in channel characteristics, vehicle speeds, traffic densities between various scenarios, the requirement for real-time scenario identification of vehicular communications is increasingly urgent. Vehicular communication systems can select appropriate channel models and transmission mode by correctly identifying the current scenarios to maintain an effective and reliable operating state. This paper presents a machine-learning-based scenario identification model for intelligent vehicular communications. Channel characteristics extracted from channel measurements in different scenarios form the datasets used to training, then a back-propagation neural network (BPNN) is trained, and a scenario identification model is obtained. Furthermore, the model configuration scheme is explored and presented which can make the proposed identification model achieves optimal performance. Subsequently, identification accuracy is verified by using validation data of the corresponding scenarios. The results show that the identification accuracies are all above 98 % in four typical scenarios of urban areas, highways, tunnels, and vehicle obstructions, which indicates that the model proposed in this paper shows good performance in scenario identification for intelligent vehicular communications.

Making intersections safer with I2V communication

Intersections are hazardous places. Threats arise from interactions among pedestrians, bicycles and vehicles, more complicated vehicle trajectories in the absence of lane markings, phases that prevent determining who has the right of way, invisible vehicle approaches, vehicle obstructions, and illegal movements. These challenges are not fully addressed by the “road diet” and road redesign prescribed in Vision Zero plans, nor will they be completely overcome by autonomous vehicles with their many sensors and tireless attention to surroundings. Accidents can also occur because drivers, cyclists and pedestrians do not have the information they need to avoid wrong decisions. In these cases, the missing information can be computed and broadcast by an intelligent intersection. The information gives the current full signal phase, an estimate of the time when the phase will change, and the occupancy of the blind spots of the driver or autonomous vehicle. The paper develops a design of the intelligent intersection, motivated by the analysis of an accident at an intersection in Tempe, AZ, between an automated Uber Volvo and a manual Honda CRV and culminates in a proposal for an intelligent intersection infrastructure. The intelligent intersection also serves as a software-enabled version of the ‘protected intersection’ design to improve the passage of cyclists and pedestrians through an intersection.

A Simulation-based Study on the Environment-Specific Propagation Model for Vehicular Communications

Vehicle-to-Vehicle (V2V) communication environment vary significantly in radio channel characteristics. Therefore, simulation-based studies on V2V propagation models that consider random and time-varying characteristics of surrounding environment are highly sought-after. This paper includes a detailed overview of the existing V2V channel modeling techniques. Followed by the details on what information is required to perform large-scale simulations of the environment-specific vehicular channel model. Next, the authors propose a simulation model which combines data from several sources such as 2.5D building geometry data and vehicular mobility traces to create a realistic simulation environment. Finally, the given reference scenario has been assessed regarding several performance metrics and parameter settings using a publicly available geometry-based V2V propagation model. The simulation results show that building and vehicle obstructions significantly attenuate the signal thus resulting in lower received signal strength, lower packet delivery ratio, and shorter effective transmission range.

CFD analysis of smoke backlayering dispersion in tunnel fires with longitudinal ventilation

SummaryIn a longitudinally ventilated tunnel fire, the backlayering flow propagated in the opposite direction to the air current is the most fatal contaminations to users which are blocked upstream of the fire. In the present paper, numerical simulations were conducted using Fire Dynamic Simulator, which is based on large eddy simulations to estimate the backlayering arrival time in a longitudinally ventilated tunnel fire. The effect of a vehicle obstruction on the backlayering arrival time will be also investigated. For this, a vehicle model occupying about 31% of the tunnel cross section is simulated upstream of the fire source with its location relative to the tunnel floor is varied. The numerical investigation shows that the inertia and the buoyancy forces produced by ventilation and fire, respectively, affect the backlayering spread. The backlayering arrival time increases with the longitudinal ventilation velocity while it decreases with the fire heat release rate. When a vehicle obstruction existed within the tunnel, the numerical results show an increase of backlayering arrival time. This increase is significantly more important with the fire distance when the vehicle obstruction approaches the tunnel floor. Two correlations are developed, with and without obstruction in the tunnel, to predict the backlayering arrival time against the distance to fire. Copyright © 2016 John Wiley & Sons, Ltd.

Oxymatrine inhibits renal fibrosis of obstructive nephropathy by downregulating the TGF-β1-Smad3 pathway

This study investigated whether oxymatrine (OMT) treatment can ameliorate renal interstitial fibrosis in unilateral ureteral obstruction (UUO) mice model. Moreover, the potential mechanisms of such treatment were analyzed. Twenty-four C57/BL6 mice were randomly divided into three groups, namely sham group, vehicle plus unilateral ureteral obstruction (UUO)-treated group, and 100 mg/kg/d OMT plus UUO-treated group. All mice were euthanized seven days after surgery, and their kidneys were harvested. Renal injury, fibrosis, expression of proinflammatory cytokines, and the transforming growth factor-β1/Smads (TGF-β/Smads) and nuclear factor-kappa B (NF-κB)-signaling pathways were assessed. The results showed OMT significantly prevented kidney injury and fibrosis, as evidenced by decreased expression of collagen-1 and fibronectin. Furthermore, OMT administration inhibited the release of inflammatory factors including tumor necrosis factor-α, (TNF-α) interleukin-1β (IL-1β), and interleukin-6 (IL-6), as well as phosphorylated NF-κB p65. In addition, OMT blocked the activation of myofibroblasts by inhibiting the TGF-β/Smad3-signaling pathway. The findings indicate that OMT-attenuated renal fibrosis and inflammation, and this renoprotective effect may be ascribed to the inactivation of the TGF-β/Smad3 and NF-κB p65 pathways.

Injury pattern of road traffic accident cases in a rural hospital of central Uttar Pradesh

Background: Accident is a multifactorial event and can be studied in terms of agent, host, and environment. The WHO has defined road traffic accident (RTA) as when a vehicle collides with another vehicle, pedestrian, animal, road debris, or other stationary obstruction. Objective: To study demographic profile and injury pattern among RTA victims. Materials and Methods: This cross sectional study was conducted at UP Rural Institute of Medical Sciences & Research (UPRIMS & R) hospital, Saifai, Etawah, Uttar Pradesh from 1st January 2014 to 30th June 2014. The study group consisted of all the RTA victims reporting to Emergency Department of UPRIMS & R Hospital in the study period. The data were summarized using percentages. The chi-square test was applied to see if there was any association between the different variables associated with the accidents. Result: There is a high percentage of RTA among males of younger age group those were using motorized two wheelers. Fracture was the most common type of injury and lower limbs were the most common site involved. Conclusion: There is a high percentage of RTA among males of younger age group those were using motorized two wheelers. Fracture was the most common type of injury and lower limbs were the most common site involved.

Vehicle-to-Vehicle Propagation Models With Large Vehicle Obstructions

Vehicle-to-vehicle (V2V) communication is an enabler for improved traffic safety and congestion control. As for any wireless system, the ultimate performance limit is determined by the propagation channel. A particular point of interest is the shadowing effect of large vehicles such as trucks and buses, as this might affect the communication range significantly. In this paper we present measurement results and model the propagation channel, in which a bus acts either as a shadowing object or as a relay between two passenger cars. The measurement setup is based on a Wireless Open-Access Research Platform (WARP) Field-Programmable Gate Array (FPGA) software radio as transmitter and a Tektronix RSA5106A real-time complex spectrum analyzer as receiver. We analyze the influence of the bus location and car separation distance on the path loss, shadowing, small-scale fading, delay spread, and cross correlation. The main effect of the bus is that it is acting as an obstruction creating an additional 15- to 20-dB attenuation and an increase in the root-mean-square delay spread by roughly 100 ns. A Nakagami distribution is found to well describe the statistics of the small-scale fading, by using Akaike's Information Criterion and the Kolmogorov-Smirnov test. The distance dependence of the path loss is analyzed and a stochastic model is developed.

A State-of-the-Art Modeling Framework to Improve Congestion by Changing the Configuration/Enforcement of Urban Logistics Loading/Unloading Bays

Systematic ways to perform ex-ante analysis of urban freight good practices are still missing, deeming transferability efforts prone to failure. We critically analyze state-of-the-art freight modeling methodologies to optimize the configuration of loading/unloading bays, and the associated enforcement measures, quantifying congestion reductions. Existing models can poorly handle some crucial elements for this analysis. An alternative modeling framework is proposed, integrating simulation models and optimization strategies that take into account double-parking derived vehicle obstruction. The framework should lead to deeper insights, even in a low-data availability perspective, between what is regarded as good practices and a quantification of their potential; thus becoming a useful tool in the design and analysis of policies.

Numerical Simulation of Critical Velocity in Obstructed Tunnel

When highway tunnel is on fire, obstruction of vehicles in the tunnel have certain effects on the spread of fire smoke and critical velocity. This paper made CFD studies on the critical velocities when the blockage is located in the upstream flow of the fire smoke. The effect of the distance between fire source and blockage as well as the dimension ratio was analyzed. The numerical simulation results show that the critical velocity in upstream obstructed tunnel is smaller than that in empty tunnel and the critical velocity increases with the distance between the blockage and the fire source. The critical velocity increases with the heat release rate and decreases with the dimension ratio. The calculating model for critical velocity of empty tunnel was modified to adapt to obstructed tunnel.

Effect of vehicular blockage on critical ventilation velocity and tunnel fire behavior in longitudinally ventilated tunnels

Most studies have investigated tunnel fires in tunnels without vehicles, even though vehicles can obstruct ventilation flows and alter tunnel fire behavior. This study conducted small-scale experiments and numerical simulations to investigate the effects of vehicular blockage on tunnel fire behavior and critical ventilation velocity, ucr, in longitudinally ventilated tunnels. The 7m-long tunnels had cross sections of 0.6m(H)×0.6m(W) or 0.4m(H)×0.6m(W). Three vehicles types in two or three arrays, occupying 5–31% of the tunnel cross section, were positioned upstream of fires. Fires were located on the tunnel center line or downstream of vehicles on the vehicle center line. Fuel was gasoline in square pans with dimensions of 6.3×6.3cm2 or 9.0×9.0cm2. Experimental data indicate that ucr decreased due to vehicular obstruction when ventilation flow reached the fires; the reduction ratio approximately equals the vehicle blockage ratio by the continuity equation. Non-uniform distribution of flow velocity caused by the relative positions of fires and vehicles when ventilation flow passed fires and vehicles played a secondary role. However, ucr increased when the vehicle obstructions existed and ventilation flow did not reach the fires since the heat release rate increased due to heat feedback from vehicle obstructions. The mechanism of vehicle blockage is discussed.

Predicting Small Target Detection Performance of Low-SNR Airborne Lidar

Recent technological advances in the performance of small micro-lasers and multi-channel multi-event photo-detectors have enabled the development of experimental airborne lidar (light detection and ranging) systems based on a low-SNR (LSNR) paradigm. Due to dense point spacing (tens of points per square meter) and sub-decimeter range resolution, LSNR lidar can likely enable detection of meter-scale targets that would go unnoticed by traditional lidar technology. Small vehicle obstructions and other similar targets in the beach and littoral zones are of particular interest, because of LSNR lidar's applicability to the near-shore environment and the general desire to improve detection of antivehicle and antipersonnel obstacles in the coastal zone. A target detection procedure is presented that exploits the detailed information available from LSNR lidar data while diminishing the effect of spurious noise events. Consideration is given to detection in both topographic and bathymetric scenarios. Data sets for target detection analysis are supplied by a numerical sensor simulator developed at the University of Florida. Target detection performance is evaluated as a function of environmental characteristics, such as water clarity and depth, and system parameters, specifically transmitted pulse energy and laser pulse repetition frequency. Analysis of results with regards to consideration for future system design is discussed.

Measurement of UHF Signal Strength Propagating from Road Surface with Vehicle Obstruction

Measurement of UHF Signal Strength Propagating from Road Surface with Vehicle Obstruction

Study of critical velocity and backlayering length in longitudinally ventilated tunnel fires

Experimental tests and theoretical analyses were conducted to investigate the critical velocity together with the backlayering length in tunnel fires. The experiments were performed in two longitudinally ventilated model tunnels. The proposed correlations for critical velocity are found to comply well with experimental data in both tunnels. The critical Froude number and the critical Richardson number were analyzed using the experimental data. The backlayering length was related to the ratio of longitudinal ventilation velocity to critical velocity. Experimental data show that the relation between the ratio of ventilation velocity to critical velocity and the dimensionless backlayering length follows an exponential relation. A correlation based on experimental data to predict the backlayering length is proposed. Further, comparison of experimental data of critical velocity and backlayering length with results from large-scale tests shows that there is a good agreement in both scales. The effect of accident vehicle obstruction on critical velocity and backlayering length was also analyzed. Experimental data show that the decrease in rate of critical velocity due to obstruction is slightly greater than the ratio of cross-sectional area of the model vehicle to tunnel cross-sectional area, and the backlayering length with an accident vehicle set inside the tunnel gets smaller.

Effects of loading behaviour and road transport stress on traumatic injuries in cattle transported by road during the hot-dry season

The welfare of cattle during loading and unloading, and injuries sustained during road transportation of 150 indigenous West African cattle breeds belonging to the Bos indicus breeds of White Fulani (WF), Red Bororo (RB) and Sokoto Gudale (SG) were investigated. The injuries were determined using standard clinical examination methods. The result showed that cattle with higher points of behavioural activities and loading time had higher ( P < 0.01) number of injuries. The highest percentages of injuries were inflicted by their horns, stockholders and vehicle obstructions. Wound contusions and lacerations were the most frequent types of injuries sustained in all the breeds. The thoracic and abdominal walls were the areas of the body most affected by the injuries. Severe injuries and the number of internal muscular hemorrhage sustained at slaughter were significantly ( P < 0.05) higher in breeds with massive long horns (RB and WF). The longer the duration of the journey, the higher the incidence of injuries sustained. In conclusion, the transported cattle were exposed to serious stress factors adversely affecting their health, productivity and market value.