Highway Vehicle Research Articles

Vehicle License Plate Recognition Based on Wavelet Transform and Vertical Edge Matching

With the improvement of our country’s economic level and quality of life, the numbers and scales of highway networks and motor vehicles are constantly expanding, which makes the current road traffic burden more and more serious. As an important means of traffic automation management, license plate recognition (LPR) technology plays an important role in traffic surveillance and control. However, the recognition rate and accuracy of the traditional license plate recognition methods still need to be improved. In the case of poor surrounding environment, it is prone to localization failure, vehicle license plate recognition errors or unrecognizable phenomena. Wavelet transform, as another landmark signal processing method after Fourier transform, has been widely used in the field of image processing. In China, the number of horizontal lines is usually larger than that of vertical lines. If the two vertical boundaries of the license plate can be detected successfully, the four angles of the license plate can be determined efficiently to complete the license plate positioning. In view of the advantages of wavelet transform technology and the characteristics of vehicle license plate, in this paper, a vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching is proposed. The edge of the license plate is detected by wavelet transform technology, and then the license plate is located by vertical edge matching technology. After the location is realized, the characters are segmented by vertical projection method and the characters are recognized by improved BP neural network algorithm. The experimental results show that the proposed vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching performs well in algorithm performance, which provides a good reference for the development of vehicle license plate recognition system.

“That crosscountry 1969 vw squareback and holiday inn affair”: lesbian mobility

This article argues that lesbian mobility contributed to the development of lesbian identity in North America in the 1960s and 1970s. Drawing primarily on published accounts, it explores the ways in which women achieved and sustained their lesbian identity in part through their access to what cultural geographers term a transportation assemblage or constellation of mobility. This was constituted through the symbolic meaning of mobility for predominantly white women, the existence of new highway networks and Volkswagen vehicles, which were popularized through countercultural branding, and lesbians’ embodied experiences of fear and desire.

Sleepiness and Driving: The Role of Official Regulation.

Sleepiness accounts for approximately 20% of major highway motor vehicle accidents (MVAs) and the most common medical disorder associated with sleepiness is obstructive sleep apnea (OSA). OSA patients are 2 to 3 times more likely to have an MVA than the general population, although continuous positive airway pressure therapy can remove this excess risk. Several jurisdictions have introduced regulations to limit driving in patients with moderate or severe OSA associated with sleepiness until the disorder is effectively treated. Successful implementation of such regulations requires education regarding risk-benefit relationships of relevant stakeholders, including patients, clinicians, and employers in the transportation industry.

Rigid–flexible coupled dynamic response of steel–concrete bridges on expressways considering vehicle–road–bridge interaction

Steel–concrete bridges on highways are now widely used, and their dynamic coupling effect is more prominent under heavy vehicles. At present, for the study of vehicle–bridge coupling, it is difficult to reflect the mechanical response characteristics of the bridge pavement because the bridge pavement (road) is often considered as a load. In order to get closer to reality, we use the whole vehicle model and the bridge model to realize the dynamic coupling of highway vehicle–bridge. Moreover, the vehicle model can take into account tire characteristics, such as various linear and nonlinear suspension characteristics, and tire–ground contact characteristics. So, a new vehicle–road–bridge interaction method with higher computational efficiency is proposed. This method can be used not only to analyze the overall mechanical response of bridge structure such as deflection and stress but also to analyze the dynamic characteristics of driving vehicles and the coupling force between tires and pavement and then to analyze the dynamic deformation and stress of asphalt pavement layers on the bridge. First, according to the construction drawings of a steel–concrete bridge on a highway and a Dongfeng brand three-axle vehicle, a vehicle–road–bridge interaction rigid–flexible coupling model was established. Second, the correctness and effectiveness of the vehicle–road–bridge interaction model were verified by field testing. Finally, the dynamic response of the vehicle–road–bridge interaction rigid–flexible coupling model was analyzed.

OPERATING SPEED PREDICTION MODEL AS A TOOL FOR CONSISTENCY BASED GEOMETRIC DESIGN OF FOUR-LANE DIVIDED HIGHWAYS

Researchers have studied two-lane rural highways to predict the operating speed on horizontal curves and correlated it with safety. However, the driving characteristics of four-lane-divided highways are different. Weak lane discipline is observed in these facilities, which influences vehicle speed in adjacent lane or space. So, irrespective of its lane or lateral position, vehicles in four-lane divided highways are considered free flowing only when it maintains the minimum threshold headway from any lead vehicle. Examination of two conditions is proposed to ensure the free flow. Vehicles meeting both conditions, when tracked from the preceding tangent section till the centre of the horizontal curve, are considered as free flowing. The speed data of such free flowing passenger cars at the centre of eighteen horizontal curves on four-lane divided highways is analysed to develop a linear operating speed prediction model. The developed model depends on curve radius and preceding tangent length. The operating speed of passenger car in four-lane divided highways is influenced by horizontal curve of radius 360 m or less. Further, longer tangent would yield higher operating speed at the centre of the curve. Finally, two nomograms are suggested for conventional design, consistency based design and geometric design consistency evaluation of four-lane divided horizontal curves.

Techniques for Assessing and Mitigating Longwall Subsidence Effects on Interstate Highways

Surface subsidence induced by underground coal mining activities, especially longwall mining operations, can cause various problems to interstate highways ranging from structural integrity, drivability to safety. Accurate subsidence prediction, correct influence assessments, and effective mitigation measures are the keys to ensure the safety of highway traffic. The surface subsidence prediction program, called comprehensive and integrated subsidence prediction model (CISPM), was developed based on the principle of influence function method and has been validated with a large number of subsidence measurements. In this paper, the techniques to use the predicted final surface movements and deformations for assessing their influence on the integrity and functionality of highway structures (e.g., road surface pavements, concrete slabs, transverse joints, etc.), vehicle dynamics, comfort level, and drivability are presented. A number of mitigation measures to protect the highway structures and to ensure traffic safety are proposed along with an application case.

Effect of Vibration from Highway Vehicle Load on adjacent Buildings and Its Assessment

This paper studies the influence of highway vehicle loads on the vibration of nearby buildings, and both the vehicle induced vibration of ground and adjacent residential are analyzed. Firstly, testing points are arranged on both sides of a highway named Xiongchu Avenue to measure the ground vibration caused by vehicle loads. Secondly, the corresponding vibration response of a nearby residential building is measured. The natural frequency of this building is identified by NexT/ERA method. The results show that the influence of the traffic load on the frequency of the building is mainly between 8Hz to 20Hz. The acceleration level of each storey and influence of vibration on human comfort are calculated, and it is concluded that all the degree of vertical vibration are belong to the requirements in the Chinese code. This paper provides corresponding technical support for solving the problem of such traffic system.

Analysis of the influence of geometric design consistency on vehicle CO2 emissions

Highway vehicles driving on rural roads account for more than 50% of all CO2 emissions produced by the transportation sector in Europe. Although the policy measures to mitigate Greenhouse Gas emissions are increasing, these do not include policies aimed at reducing emissions by means of highway geometric design, which significantly influences drivers’ speeds and accelerations and, consequently, plays a major role on fuel consumption and emissions.Therefore, the main objective of this research is to study the influence of the geometric design consistency on vehicle CO2 emissions. To do this, continuous speed data were collected on 47 homogeneous road segments by means of Global Positioning System devices. Vehicle CO2 emissions were estimated by applying the VT-micro model, whereas geometric design consistency was assessed considering different global consistency models.As a conclusion, vehicle CO2 emissions decreases as the consistency level of a homogeneous road segment increases. Specifically, a good consistency road segment has been found to present an emission rate 20–30% lower than a poor-consistent one. Therefore, the design of consistent roads allows, in addition to maximize road safety, to help to achieve more environmentally sustainable highways, reducing CO2 emission production.

Kinematics-enabled lossless compression of freeway and arterial vehicle trajectories

This paper shows how embedded instantaneous kinematic information from files of vehicle trajectories can be exploited to better enable data compression algorithms for typical files containing all such trajectories from a roadway segment over some period of time. Such files typically contain other relevant information, such as vehicle class, lane number, and so on, and effective ways of compressing these variables are demonstrated as well. The test files are taken from the Next Generation Simulation project, as those files are to date the de facto standard for large trajectory repositories suitable for studying traffic flow theory. The advent of connected vehicles suggests that the data collection, storage, and hence, compression needs in this arena will continue to grow. We develop compression algorithms that exploit collective vehicle kinematics of the first and second order to enable greater compression ratios. Using the context-free .zip and .7z compression routines as baselines, we compare three schemes. The first scheme treats each column independently and does not recognize any variables as kinematic and produces compression gains approaching 2:1. The second scheme also compresses each column independently, but recognizes that some of them contain kinematic variables, and hence relationships along the rows, resulting in gains of around 4:1. Finally, the scheme that uses all of this information, plus kinematic correlations across columns, produces gains on the order of 5:1.

Compressed-Domain Highway Vehicle Counting by Spatial and Temporal Regression

Counting on-road vehicles in the highway is fundamental for intelligent transportation management. This paper presents the first highway vehicle counting method in compressed domain, aiming at achieving comparable estimation performance with the pixel-domain methods. Counting in compressed domain is rather challenging due to limited information about vehicles and large variance in vehicle numbers. To address this problem, we develop new low-level features to mitigate the challenge from insufficient information in compressed videos. The new proposed features can be easily extracted from the coding-related metadata. Then, we propose a hierarchical classification-based regression (HCR) model to estimate the number of vehicles from the compressed-domain low-level features for individual frame. HCR hierarchically divides the traffic scenes into different cases according to the density of vehicles such that the large variance of traffic scenes can be effectively captured. Beside the spatial regression in each frame, we propose a locally temporal regression model to further refine the counting results, which exploits the continuous variation characteristics of the traffic flow. We extensively evaluate the proposed method on real highway surveillance videos. The experimental results consistently show that the proposed method is very competitive compared with the pixel-domain methods, which can reach similar performance with much lower computational cost.

Empirical modeling of the relationship between decision sight distance and stopping sight distance based on AASHTO

The paper introduces implementation of highways' stopping sight distance (SSD) and decision sight distance (DSD) based on AASHTO modeling assumptions. SSD characterizes the necessary distance for highway vehicles to stop safely in front from an obstacle. SSD is a function of vehicle speed, perception reaction time, deceleration rate, and grade based on AASHTO and most highway design international guidelines. The deceleration rate which is assumed constant (3.4 m/sec2) based on AASHTO 2011 is generally controlled by the friction coefficient depending on the road surface conditions. A driver's demanded deceleration rate may not exceed the range of friction coefficient according to various pavement conditions. Although SSD is generally sufficient to allow skilled and alert drivers to the stop their vehicles under regular situations, this distance is insufficient when information is difficult to comprehend. A DSD should be provided in highways geometric design when the driver is required to detect an unexpected or difficult to perceive information source. Interchanges (specifically exit ramps) and intersections, and required changing in driver direction of travel, changes in the basic cross section such as toll plaza, lane drop, are typical scenarios where driver needs DSD in the safety manner. The introduction of the two sight distance types (SSD and DSD) is a perquisite for empirical modeling of the relationship between DSD and SSD. The modeling refers to DSD for rural highways, suburban roads, and urban roads based on AASHTO models. Specifically the paper covers DSD three avoidance maneuver types of stopping (types A, A1, B) and three maneuver types of speed, path, and direction changing (types C,D, E) for the three roadway categories. The major parameters that control these avoidance types are pre-maneuver times, and pre-maneuver plus maneuver times. The empirical relationship proposed in this study simplifies the process of evaluating the decision sight distance based on stopping sight distance record, based on AASHTO models, without the need of strenuous estimation of the DSD model maneuver and deceleration parameters. Such a simplified correlation has not been found in the literature except a rough approximation documented in the British highway design guidelines.

Study on the Design of Container Highway and Railway Automatic Transfer Vehicle in Ocean Port

Abstract To realize “seamless” connection of ocean port container multimodal transport, efficiently carry out “door-to-door” transport of ocean port containers and overcome the shortcomings of existing highway and railway vehicles, this study takes the standard for heavy-duty container vehicles in TB1335-1996 Railway Vehicle Strength Design and Test Identification Code as the design basis and designs a new ocean port container transport vehicle in combination with automatic guidance technology. This study innovatively designs the automatic lifting system of the bogie and the docking part of the vehicle, introduces the automatic guidance technology and the remote-control technology to optimize the car body structure, and uses the SAP software to carry out the finite element analysis of the car body load capacity and Flexsim software to carry out the simulation analysis on the operation of vehicles. The designed transfer vehicle can improve the transfer efficiency of ocean port containers, reduce the transit time of field and station equipment and container transport links, and improve the level of multimodal transport and comprehensive economic benefits.

An algorithm for highway vehicle detection based on convolutional neural network

In this paper, we present an efficient and effective framework for vehicle detection and classification from traffic surveillance cameras. First, we cluster the vehicle scales and aspect ratio in the vehicle datasets. Then, we use convolution neural network (CNN) to detect a vehicle. We utilize feature fusion techniques to concatenate high-level features and low-level features and detect different sizes of vehicles on different features. In order to improve speed, we naturally adopt fully convolution architecture instead of fully connection (FC) layers. Furthermore, recent complementary advances such as batch-norm, hard example mining, and inception have been adopted. Extensive experiments on JiangSuHighway Dataset (JSHD) demonstrate the competitive performance of our method. Our framework obtains a significant improvement over the Faster R-CNN by 6.5% mean average precision (mAP). With 1.5G GPU memory at test phase, the speed of the network is 15 FPS, three times faster than the Faster R-CNN.

Source-Specific Contributions to Fine Particulate Matter Exposure Disparities in the United States

Efficiently addressing environmental injustice in air pollution exposure requires knowledge of the predominant sources of air pollution exposure disparities. Previous studies that have linked emissions sources to environmental injustice have used proximity to the emissions source as an exposure metric, but locations of emissions sources and the spatial patterns of the resulting concentrations are often only weakly correlated. We use the year-2014 US EPA National Emissions Inventory (NEI) and the Intervention Model for Air Pollution (InMAP) to estimate fine particulate matter (PM2.5) concentrations resulting from the more than 5,000 emissions source types included in the inventory, and we quantify associated exposure disparities by race-ethnicity. Preliminary results suggest 54% of source types, representing 62% of total PM2.5 exposure, result in higher average exposures for minorities as compared to whites. Overall, minorities are exposed to average concentrations 1.7 μg m-3 higher than whites. Significant source groups—those that contribute at least 1% of overall exposure—disproportionately impacting minorities include residential natural gas burning, commercial cooking, and highway vehicles (average exposure for minorities is 90%, 73%, and 39% higher, respectively, than whites). Significant source groups disproportionately impacting whites include coal power generation and agriculture (average exposure for whites is 26% and 15% higher, respectively, than minorities). These results can help policy-makers direct targeted efforts to mitigate inequitable exposure to air pollution.

Thermodynamic analysis and nanoparticle assessment of Japanese diesel no 2 fueled truck engine

There are two Japanese quality standards for diesel fuels. One of them is JIS K 2204 class which consists of five class diesel fuels as No. 1, No. 2, No. 3, Special No. 1 and Special No. 3 (1S, 1, 2, 3 and 3S, respectively). No. 2 diesel fuel is generally used for highway vehicles (passenger cars, buses and trucks). In this study, Japanese Industrial Standard Diesel No:2 fuel is utilized to run the truck engine under 284.39 Nm load. The thermodynamic analysis and experimental tests are performed to the engine for nano-particle, emission and efficiency assessments. In this regard, the maximum energy rate is found for the energy of fuel (145.209 kW) which is the main component to start the engine. Also, the minimum energy rate is determined for the exhaust gases which are released to the atmosphere. The power of the truck engine is calculated as 53.585 kW and the energy efficiency is found as 31.625%. Furthermore, the maximum particle concentration is determined around 106 1/cm3 which is lower than other fuels that compared in this study, and the particle size is measured between 5 nm and 15 nm by using Scanning Mobility Particle Sizer (SMPS).

Characterization of municipalities with high road traffic fatality rates using macro level data and the CART algorithm

Road traffic accidents occur daily caused by different factors leading to varying degrees of injury severity. Considering this, many studies have been developed to identify and understand these factors to implement preventive actions. A Decision Tree (DT) is one of the techniques that can generate classifications and predictions by detecting a priori unknown patterns. This study aims to identify the characteristics of municipalities with high and very high fatality rates caused by traffic accidents, using a macro level dataset and a DT algorithm (CART - Classification And Regression Tree). Therefore, macro level data from the municipalities of São Paulo state (Brazil) were used, such as demographic and socioeconomic data, fatality rates and other variables related to traffic. The results indicated the Gross Domestic Product (GDP) as the most important variable, and the municipalities were characterized mainly considering the size of the highway network and vehicle fleet (trucks, minibuses, cars, motorcycles). These characteristics could provide support to the government to plan mitigating actions in municipalities with the highest tendency to high traffic fatality rates.

Lane Marking Detection and Reconstruction with Line-Scan Imaging Data.

Lane marking detection and localization are crucial for autonomous driving and lane-based pavement surveys. Numerous studies have been done to detect and locate lane markings with the purpose of advanced driver assistance systems, in which image data are usually captured by vision-based cameras. However, a limited number of studies have been done to identify lane markings using high-resolution laser images for road condition evaluation. In this study, the laser images are acquired with a digital highway data vehicle (DHDV). Subsequently, a novel methodology is presented for the automated lane marking identification and reconstruction, and is implemented in four phases: (1) binarization of the laser images with a new threshold method (multi-box segmentation based threshold method); (2) determination of candidate lane markings with closing operations and a marching square algorithm; (3) identification of true lane marking by eliminating false positives (FPs) using a linear support vector machine method; and (4) reconstruction of the damaged and dash lane marking segments to form a continuous lane marking based on the geometry features such as adjacent lane marking location and lane width. Finally, a case study is given to validate effects of the novel methodology. The findings indicate the new strategy is robust in image binarization and lane marking localization. This study would be beneficial in road lane-based pavement condition evaluation such as lane-based rutting measurement and crack classification.

Spotting of over Speeding Vehicles and Controlling the Speed in Highways using MEMS Sensor

This Paper describes about the spotting of an over speed of a vehicle in highway and controlling the speed of a vehicle whenever there is an uneven Condition Occurred. And alert the speed offence to control room and toll gate, the devices like Controller, RFID reader, MEMS sensor, GSM&LCD are used. The System are controlled by a microcontroller, The Micro-Controller plays an important role to do a desired task. The controller obtains the MEMS sensor, which is used to sense speed of the vehicle, Vehicle has RFID tag when speed violation take place where RFID reader reads the tag and identify the vehicle and send the information through GSM module. We design a project in such a manner that it gives an alert signal to the driver if he does not react to that, than two condition occurred first speed is been controlled and other speed offence fine is send control room and toll gate whenever vehicle crossing its maximum speed limit.

Design of Highway Intelligent Vehicle Guidance System

Now the highway’s traffic accidents are often taken place because of the influence of fog and other inclement weather. The accidents cause a very big loss to people's life and property. Therefore, it plays an important part in all-weather real-time monitoring, analyzing and early warning effectively. In this paper, a highway intelligent vehicle guidance system is developed to avoid traffic accidents occurring in highway. The system can greatly reduce the traffic accidents caused by mass of fog. The result shows that the system has high precision and reliability.

Bunker diesel viscosity is dramatically reduced by electrorheological treatment

Bunker diesel is an important fuel for heavy duty engines, such as navy ships. It is different from the Ultra Low Sulfur Diesel which is used for highway system vehicles, which has high level sulfur. The Department of Defense (DOD) testified in September 2006 that its energy use represents about 1.2% of total U.S. energy use, of which marine diesel fuel accounts for 13%, that is, 16 million barrels of oil. The Navy spent $900 million for fuel for its ships and aircraft. For fossil-fueled Navy ships, reducing energy use can reduce fuel costs, increase cruising range, increasing its survivability by reducing emissions of hot exhaust gasses. If applied to a significant number of ships, an increase in cruising range might permit a reduction in Navy costs for fuel-related force structure and infrastructure. The flow rate of bunker diesel can be increased 30% by electric field treatment, that is, by reducing the viscosity at least 50%. This could lead to significant cost savings and increase cruising range.