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The impact that trucks have on crash severity has long been a concern in crash analysis literature. Furthermore, if a truck crash happens in a tunnel, this would result in more serious casualties due to closure and the complexity of the tunnel. However, no studies have been reported to analyze traffic crashes that happened in tunnels and develop crash databases and statistical models to explore the influence of contributing factors on tunnel truck crashes. This paper summarizes a study that aims to examine the impact of risk factors such as driver factor, environmental factor, vehicle factor, and tunnel factor on truck crashes injury propensity based on tunnel crashes data obtained from Shanghai, China. An ordered logit model was developed to analyze injury crashes and property damage only crashes. The driver factor, environmental factor, vehicle factor, and tunnel factor were explored to identify the relationship between these factors and crashes and the severity of crashes. Results show that increased injury severity is associated with driver factors, such as male drivers, older drivers, fatigue driving, drunkenness, safety belt used improperly, and unfamiliarity with vehicles. Late night (00:00&ndash, 06:59) and afternoon rushing hours (16:30&ndash, 18:59), weekdays, snow or icy road conditions, combination truck, overload, and single vehicle were also found to significantly increase the probability of injury severity. In addition, tunnel factors including two lanes, high speed limits (&ge, 80 km/h), zone 3, extra-long tunnels (over 3000 m) are also significantly associated with a higher risk of severe injury. So, the gender, age of driver, mid-night to dawn and afternoon peak hours, weekdays, snowy or icy road conditions, the interior zone of a tunnel, the combination truck, overloaded trucks, and extra-long tunnels are associated with higher crash severity. Identification of these contributing factors for tunnel truck crashes can provide valuable information to help with new and improved tunnel safety control measures.

The present study has investigated the relationship between traffic volume and crash numbers by means of meta-analysis, based on 521 crash prediction models from 118 studies. The weighted pooled volume coefficient for all crashes and all levels of crash severity (excluding fatal crashes) is 0.875. The most important moderator variable is crash type. Pooled volume coefficients are systematically greater for multi vehicle crashes (1.210) than for single vehicle crashes (0.552). Regarding crash severity, the results indicate that volume coefficients are smaller for more fatal crashes (0.777 for all fatal crashes) than for injury crashes but no systematic differences were found between volume coefficients for injury and property-damage-only crashes. At higher levels of volume and on divided roads, volume coefficients tend to be greater than at lower levels of volume and on undivided roads. This is consistent with the finding that freeways on average have greater volume coefficients than other types of road and that two-lane roads are the road type with the smallest average volume coefficients. The results indicate that results from crash prediction models are likely to be more precise when crashes are disaggregated by crash type, crash severity, and road type. Disaggregating models by volume level and distinguishing between divided and undivided roads may also improve the precision of the results. The results indicate further that crash prediction models may be misleading if they are used to predict crash numbers on roads that differ from those that were used for model development with respect to composition of crash types, share of fatal or serious injury crashes, road types, and volume levels.

The Pickup and Delivery problem (PDP) is an optimization problem used in logistics, where goods must be transported in a certain order. This paper proposes the Set of Single-Vehicle Dynamic Pickup and Delivery Problem (SVPDP), which extends PDP to a set of vehicles that are already on the road when a new pickup and delivery order arrives. A ranking is created to determine, which vehicles are best suited to fulfill this order with the smallest detour. A modified Ant Colony Optimization algorithm (ACO) dynamically defines for each vehicle new routes while minimizing the overall costs when integrating the additional locations. The problem is modeled, different sizes are examined and suitable parameter sets for the ACO are proposed to solve this particular SVPDP.

As motor vehicles are increasing, the demand for gas stations is rising. Because of the rising profits of gas stations, many traders have built illegal gas stations. The dangers of illegal gas stations are enormous. The government has always used traditional manual methods for screening illegal gas stations. How to quickly and effectively mine illegal gas stations in the trajectory data becomes a problem. This paper proposes an illegal gas station clustering discovery algorithm for unmarked trajectory data. The algorithm mines the suspected fueling point set and frequent staying point set of a single vehicle. Through the difference between the two, the suspected points of the illegal gas stations in the single vehicle trajectory are obtained, and finally all the illegal gas station suspicious points of the same type of vehicles are clustered to find the illegal gas station.

Current mobility requirements exceed by far simple needs for a single vehicle and therefore put a strain on incumbent mobility providers. The changing needs are further impacted by the digital age and the needs for organisations to adapt to stay in the game. This is particularly challenging for product focused companies (such as OEMs) to transform into customer centric organisations.

Diagnostic Trouble Codes (DTCs) allow monitoring a wide range of fault conditions in heavy trucks. Ideally, a perfectly healthy vehicle should run without any active DTCs; in practice, vehicles often run with some active DTCs even though this does not pose a threat to their normal operation. When a DTC becomes active, it is therefore unclear whether it should be ignored or considered as a serious issue. Recent approaches in machine learning, such as training Variational Autoencoders (VAEs) for anomaly detection, do not help in this respect, for a number of reasons that we discuss based on actual experiments. In particular, a VAE tends to learn that a frequently active DTC is of no importance, when in fact it should not be dismissed completely; instead, such DTC should be assigned a relative weight that is smaller but still non-negligible when compared to other, more serious DTCs. In this work, we present an approach to measure the relative weights of active DTCs in a way that allows the analyst to prioritize them and focus on the most important ones. The approach is based on the concept of binary cross-entropy, and finds application not only in the analysis of DTCs from a single vehicle, but also in monitoring active DTCs across an entire fleet.

Autonomous vehicle platoon is a promising paradigm towards traffic congestion problems in the intelligent transportation system. However, under certain circumstances, the advantage of the platoon cannot be fully developed. In this paper, we focus on the highway Electronic Toll Collection (ETC) charging problem. We try to let the opportunistic platoon pass the ETC as a whole. There are three main issues in this scenario. Firstly, the opportunistic platoon is temporarily composed; vehicles do not trust each other. Secondly, single vehicle may try to escape from the ETC charging by following the platoon. Finally, platoon members may collude with each other and try to underreport the number of vehicles in the platoon so as to evade payment. To solve these challenges, we propose a blockchain-based efficient highway toll paradigm for the opportunistic platoon. The driving history, credential information of every registered vehicle, is recorded and verified from the blockchain. A roadside unit (RSU) is adopted to distinguish the single vehicle from the platoon and in charge of lane allocation. Additionally, an aggregate signature is introduced to accelerate the authentication procedure in the RSU. We analyse the potential security threats in this scenario. The experimental result indicates that our scheme is efficient and practical. Agency for Science, Technology and Research (A*STAR) Published version This work is supported by the IAF-PP WP5 : Design of Security Functionality for V2X Networks Grant for the project of A19D6a0053 by the Agency for Science, Technology and Research, Singapore.

Road traffic has a significant influence on the environmental noise pollution, producing harmful effects on human health and collective well-being. Since noise measurements cannot be performed everywhere, or even in a large number of sites, because of high costs and time consumption, traffic noise predictions are necessary for noise abatement and control. Consequently, many scientific models have been developed in recent years focusing on this aspect with the definition of source emission and sound propagation empirical formulations exclusively. This paper focuses on some Emission Models, describing the comparison of the results, in terms of sound power level emitted by a single vehicle, obtained with their application to different simulations of driving conditions and to two real study cases. After a preliminary comparison between the models, the evaluation of two indicators, namely the average and total source power level, will be discussed in relation to different conditions of the vehicle kinematics. The application of these two indicators to real study cases will demonstrate their validity. It will be shown that this procedure can become a tool for supporting people route choices according to a less impact of environmental noise. This will open the way to new scenarios of eco-routing, by means of implementation of models prediction in dedicated software platforms and/or in car navigation systems.

Autonomous vehicles (AVs) promise to bring many benefits to society, such as safety, an increase of accessibility and life quality, among others. Unlike humans, they do not get tired and, supposedly, do not fail. However, there might be cases where, due to limit visibility, occlusions or even a sensor failure, the system might not be capable to detect one or more obstacles along the vehicle's path early enough to avoid a crash. Although these situations might be rare if one considers a single vehicle, if predictions are correct, these AVs are to be adopted in large quantities in the near future, making even rare situations more commonplace. AVs will have to deal with these forced-choice situations in the best possible way. This paper presents a review of the ethical discussion regarding the matter of AVs and an analysis of a questionnaire implemented by the authors. Our results show evidence for several types of contradictory choices made by the subjects, which suggest the moral choices do not necessarily follow strict logical reasoning.

This study analyzes the injury severity of commercially-licensed drivers involved in single-vehicle crashes. Considering the discrete ordinal nature of injury severity data, the ordered response modeling framework was adopted. The moderating effect of driver's age on all other factors was examined by segmenting the parameters by driver's age group. Additional effects of the different drivers' age groups are taken into consideration through interaction terms. Unobserved heterogeneity of the different covariates was investigated using the Mixed Generalized Ordered Response Probit (MGORP) model. The empirical analysis was conducted using four years of the Highway Safety Information System (HSIS) data that included 6247 commercially-licensed drivers involved in single-vehicle crashes in the state of Minnesota. The MGORP model elasticity effects indicate that key factors that increase the likelihood of severe crashes for commercially-licensed drivers across all age groups include: lack of seatbelt usage, collision with a fixed object, speeding, vehicle age of 11 years or more, wind, night time, weekday, and female drivers. Also, the effects of several covariates were found to vary across different age groups.

The efficiency of the continuously variable transmission (CVT) is within 70 ∼ 95%, so the effects on the fuel consumption cannot be ignored. In this paper, we first analyze the quantitative relationship between the running states of inertial combustion engine with CVT and the fuel consumption, and then propose a fuel-optimal driving strategy for a vehicle with CVT. In the strategy, the vehicle speed and acceleration, the engine torque and speed, and the CVT ratio in the processes of acceleration, uniform motion and deceleration are calculated. The numerical results show that when the driving distance is less than a critical value, this vehicle experiences an acceleration–deceleration process, otherwise this vehicle experiences an acceleration–constant–deceleration process. The results can provide a fuel-optimal strategy for a vehicle under different driving distance, which can be used to the human driving guidance, the driving assistance system and the autonomous vehicles.

Lane change is one of the most common maneuvers in traffic and at least 60,000 people are injured from them. This problem is usually addressed from the perspective of automation and for a single vehicle using path planning and control approaches. However, traffic is a multi-agent system which can use communication technologies to perform coordinated maneuvers in a decentralized manner. This paper aims to present a Decentralized Bargaining Negotiation Process allowing that two conflicting agents negotiate. During the negotiation, agents calculate velocity change proposals and communicate with each other in order to solve the conflict at the lowest cost. This enables that agents open safe distance gaps and make the maneuvers. We also proposed a cost function attenuation so that the agents can continue to negotiate while the agreement was not reached, but with less impact on the cost. We simulated lane merge task on SUMO with a two-lane highway with speed limit of 30 m/s. We initially simulated 2 agents and we were increasing the number of agents up to 26. We recorded the total average time for the platoon to perform the lane merge task, the platoon average velocity and the average of the speed limit exceeded in each simulation. By increasing the number of agents the total average time stabilized approximately 25 seconds. Which represents an expressive result because the time for one vehicle to complete the maneuver is 4.6 seconds. The average speed was also approximately constant around 22 m/s, which represents a good result for the traffic flow. The highest speed exceeded 9 % which represents 2.70 m/s with the attenuation cost function. We can observe that the approach proved to be scalable since the analyzed data show stability by increasing the number of vehicles.

ObjectiveTo examine the characteristics of seizure-related vehicle crashes (SRC).MethodUsing a nested case-control design, we identified and compared cases of SRC involving confirmed epilepsy patients with 137,126 non-seizure-related crash controls (NSRC) in the Australian state of Victoria. SRC were identified from approximately 20,000 epileptologist medical records by cross-referencing this source with the Victorian Police Traffic Incident database and the Road Crash Information System Database (RCISD).ResultsSeventy-one SRC involving 62 patients with epilepsy were identified. Thirty-seven SRC resulted in injury and could be identified in the RCISD and compared to NSRC. Seizure-related crashes typically involved a single vehicle (57% vs 29%,p< 0.001) carrying a sole occupant (95% vs 48%,p= 0.001). Most SRC began with an “out of control movement” (51% vs 10%,p< 0.001) and the subsequent collision type differed significantly between the groups (p< 0.001). The majority of SRC were a “collision with a fixed object” (54% vs 17%,p< 0.001) involving an “off path on straight” mechanism (48% vs 10%,p< 0.001). Regarding all 71 SRC, generalized as compared with focal epilepsy crashes involved younger drivers (p< 0.001), seizure-provoking factors (p= 0.033), and occurred earlier in the day (p= 0.004).ConclusionsGiven the distinct SRC features, we propose that clinicians, crash investigators, and driver licensing authorities incorporate collision characteristics into the overall assessment of suspected SRC. Further research should examine restricting driving immediately after risk periods as a harm-minimization strategy.

For any country’s growth is depend on their people’s growth, whenever we talk about the growth of any country then it shows the achievements done by their peoples. Day by day population are increasing and peoples are enjoying their luxurious life with big bungalows, and big luxurious cars but not a single vehicle it could be per person average of two-three vehicles results to noise, air pollutions and important factor is the increment of traffic of the city. In this paper we are not praising for the growth of the country, no doubt for the growth but we want to focus on the traffic system control. Day to day traffic is increasing in which the big problem is faced for the safe passage for the ambulance vehicle’s escape or some other person who is in need of urgent work anywhere apart from medical facilities. We heard many patients leads to death in the ambulance and doctor says ‘‘it’s too late, if you could reach at least 10minutes before then the patient could have been saved his/her life’’. So here we focused in paper to facilitate the emergency services (only concerned to patient’s ambulance) signal free. This will be possible by using the telecom technologies along with city traffic control stations to implement the things made easier for the signal free passage to escape of ambulance from the traffic lights or streets means the ambulance would not stop in the traffic jams. This can be made possible using VANET-LTE advanced technology.

In the context of rail vehicle collision tests, which incur high costs and consume substantial time and energy, the equivalence between a single vehicle crashing into a rigid wall and two identical vehicles colliding with each other was studied. Taking the car body as a rigid body, a three-dimensional multi-body dynamic model was built to simulate a single-vehicle impact and a collision between two identical vehicles; the results showed that the condition of a single vehicle crashing into a rigid wall at a speed of [Formula: see text] can be used to replace the condition of one vehicle moving at a speed of v and crashing into an identical vehicle that is stationary. However, the actual collision is a strong nonlinear process, and it is necessary to conduct the equivalent test of the condition of collision. Based on the similarity theory, the scaled equivalent vehicle model is established. Through a series of scaled model tests, the following conclusion is drawn: if one vehicle moving at a speed of vcrashes into another identical vehicle that is stationary, one can equivalently use a single vehicle with a speed of [Formula: see text] (units: m/s) that crashes into a rigid wall. This study provides practical support for the equivalence of vehicle collision test conditions and holds great value for engineering applications.

VCC leverages the underutilized storage and computing resources of vehicles to collaboratively provide traffic management, road safety, and infotainment services to end users, such as drivers and passengers. It is a hybrid technology that improves the resource utilization on vehicles and is able to perform complex computing tasks that cannot be handled by a single vehicle. Despite the appealing advantages, security and privacy threats are severe in VCC due to the sharing of resources among unfamiliar vehicles. In this article, we identify security goals for the interoperability with VCC and provide an AKA framework for VCC. Specifically, we first present the research challenges and open problems for designing a reliable AKA with strong security guarantees for VCC. Then we propose an integrated AKA framework that integrates the single-server 3-factor AKA protocol and the non-interactive identity-based key establishment protocol, and evaluate its performance based on a simulated experimental platform. Finally, several interesting issues are discussed to light up the further research directions on AKA for VCC.

Time for single vehicle combat preparation (TSVCP) is an important characteristic parameter for the operational support feature of armored vehicle. During the development phase, how to validate the TSVCP of armored vehicle through analytic method is a difficult issue in analysis and validation of vehicle supportability. This paper uses Monte Carlo approach and builds a working model for single vehicle combat preparation (SVCP) of armored vehicle, thus realizes the prediction and analysis of the TSVCP of armored vehicle, and finally validates the effectiveness of the approach by example.

This study examined the effects of distance from alcohol outlets to motor vehicle crashes across the Perth metropolitan area. A retrospective population-based study was undertaken using measures of alcohol- and non-alcohol-related crashes, and their proximity to alcohol outlets, using a geographic information system. Two logistic regression models were developed with the following outcomes: i) crashes including drivers with BAC ≥ 0.05%, and ii) weekend single vehicle night-time crashes, a surrogate measure of alcohol-related crashes. The surrogate measures of non-alcohol-related crashes for these models were all day-time and single vehicle day-time crashes respectively. The major predictors of alcohol-related crashes were number of on-premise outlets and bottleshops in buffer zones up to 2 km, 2 km–5 km, 5 km–10 km and 10 km-20 km from crashes. The distance from the central business district (CBD) and sociodemographic factors were controlled for. The study included 341,467 crashes that occurred between 2005 and 2015. The highest crash incidence rates occurred in the CBD. The statistical models indicated that crashes with a higher number of on-premise outlets in adjacent buffer zones were more likely to be alcohol-related than non-alcohol-related crashes. Crashes with a higher number of on-premise outlets less than 2 km, 2 km–5 km, 5 km–10 km, and 10 km–20 km from the crashes were significantly more likely to be weekend single vehicle night-time crashes than day-time crashes (OR = 1.014; 95% CI:1.002-1.027, OR = 1.022; 95% CI:1.014-1.029, OR = 1.019; 95% CI:1.014-1.024, and OR = 1.017; 95% CI:1.014-1.020 respectively). There was some evidence that crashes with lower number of bottleshops in adjacent buffer zones were more likely to be alcohol-related crashes, although this was not consistent across both models and all buffer zones. When other predictors were controlled for, alcohol-related crashes were more likely to occur further from the CBD, than in the CBD. Recommendations about the timing and location of roadside alcohol testing are made.

In this paper, a Markov inequality based switching rule is proposed to switch among numerically computed, time optimal controllers in a multiple vehicle intercept problem. Each controller is optimal for the intercept of a single vehicle, i.e., for the segment of the complete time varying multiple vehicle target set. The switching rule guarantees that after every switch the time to the target set is shorter with a certain predefined probability. Furthermore, the rule guarantees that the target set is reached after a finite number of switches and the rule scales well with the number of vehicles, i.e., the segments covering the target set. The problem and results are illustrated by a numerical example.

Atualmente a mobilidade urbana e um dos assuntos de maior preocupacao na cidade. Ela diz respeito a forma como os deslocamentos de pessoas e cargas acontecem na malha urbana, e e considerada por diversos autores como um importante atributo das mesmas. O objetivo do trabalho e analisar a mobilidade urbana por meio do transporte coletivo urbano na cidade de Sao Miguel do Oeste – SC. O transporte coletivo tem como funcao permitir o deslocamento de um numero maior de usuarios em um unico veiculo, otimizando o deslocamento e reduzindo o grande numero de automoveis que circulam pelo municipio. O foco no usuario do transporte coletivo e importante, pois abrange o publico enquanto usuario e enquanto pedestre. Para essa compreensao, elaborou-se um questionario do tipo survey, que foi aplicado em uma amostra de 100 pessoas, usuarias do transporte coletivo da cidade, nos meses de setembro e outubro. Conclui-se que o transporte coletivo em Sao Miguel do Oeste e utilizado principalmente por jovens mulheres e o principal motivo do deslocamento acontece para fins de estudo. Ele nao atende a malha urbana como um todo, considerando um raio de abrangencia de 300 metros a partir dos pontos e paradas de onibus. E necessario repensar na infraestrutura dos pontos e paradas de onibus, na quantidade de onibus que percorrem a linha e ainda, repensa-lo a partir de politicas publicas que possam incentivar o uso do transporte coletivo, como uma alternativa positiva a mobilidade urbana do municipio. A B S T R A C T Currently, urban mobility is a matter of major preoccupation in a city. It concerns about how the displacements of people and cargo take place in the urban mesh, which is considered by multiple authors as an important attribute of it. The intention of the study is to analyze urban mobility through collective transportation, in the city of Sao Miguel do Oeste - SC. Public transportation has the purpose to allow a great number of users in a single vehicle, optimizing displacement and reducing a large number of automobiles that circulate through the city. Focusing on the user of collective transportation is important, since it embraces the public as users and as pedestrians. For this understanding, a questionnaire of the type survey was elaborated and applied in a sample of a hundred people, all users of the collective transportation of the city, in the months of September and October. Sao Miguel do Oeste’s collective transportation is mainly used by young women, and for studying purposes. Considering a radius of 300 meters from one bus stop to another, it doesn’t attend the urban mesh as a whole. It is necessary to rethink the infrastructure of the bus stops, the number of buses that travel a bus’ route and also, rethink public policies that are able to encourage the use of public transport as a positive alternative to the urban mobility of the municipality. Keywords: Urban mobility. Collective transportation.Sao Miguel do Oeste. Road system. Mobility Program.

The task of simulation of urban processes often concerns city traffic and road dynamics. Many assumptions in an urban science may be made by analysing traffic flows and vehicle behaviour on city streets. Since road traffic is a dynamic and possibly spatially large system that depends on many external conditions, approaches like visual analysis and computational steering may be used. There are many traffic modelling frameworks presented in the field, but there are also several drawbacks most of them have: they are limited to a specific model or case; have abstracted logic which disregards some factors affecting vehicle movement; they ignore possible physical interactions which are not described in a model or use too many simplifications in vehicle interaction simulations. In this paper, a novel agent-based traffic modelling framework is presented, combining different classes of traffic models into a single vehicle agent and allowing the user to set a specific model for each supported class. The framework was made using a game engine, Unreal Engine 4, which allows users to model realistic interaction between vehicles and make realistic visualisations for purposes of visual analysis and computational steering.

Undoubtedly, single-vehicle crashes remain a major concern for roadway users and highway administrators, especially in low- and middle-income developing countries, where accident death rates remain extremely high. This study investigates the temporal instability of contributing factors of driver-injury severities in single-vehicle crashes using data in Thailand, a developing country, from 2011 to 2017. Uncorrelated and correlated random parameters models with possible heterogeneity in means and variances were estimated for individual year model using two levels of driver-injury severities, namely, no/minor injury and severe/fatal injury. The models considered a wide range of factors, such as driver, roadway, vehicle, crash, environmental and temporal, and spatial characteristics. A series of likelihood ratio test and the marginal effect of significant factors were computed to explore the temporal stability of the year models and to investigate the temporal instability of the effect of each parameter estimate on the probability of driver-injury severities within given time periods. The result indicates that a substantial temporal instability exists in the model specifications and estimated parameters (temporally unstable factor included male driver, driving using exceeding speed limit, crashes on asphalt pavement, crashes on weekends, and crashes on weekend during nighttime with present of road lighting) across the time periods under study (despite being insignificant in particular year models, some factors were stable but marginal effects varied across time). The findings may be used to assist and guide decision makers in policy generation for plans to mitigate driver-injury severities. Despite the unclear source of temporal instability, the findings emphasize the importance of the temporal instability of the factors that influence the outcomes of driver-injury severities. Alternatively, ignoring temporal instability in studies on crash severity may lead to high levels of bias and inaccurate conclusions. With regard to methodologies, both random parameters with heterogeneity in means and variances and correlated random parameters with heterogeneity in means approaches are promising methods with ability to offer another layer of insight into unobserved heterogeneity in injury severity research.

En la ciudad de Tunja no se cuenta con fuentes de información e indicadores exactos que establezcan la cantidad de llantas usadas y desechadas en tiraderos clandestinos, patios de casas y centros de acopio, las cuales generan impacto negativo en el medio ambiente y la salud de los habitantes, evidenciando la necesidad de generar una solución logística. Se presenta una investigación de enfoque cuantitativo de tipo estudio de caso; en esta se utilizó el método CVRP, que consiste en el diseño de un conjunto de rutas de menor coste, donde cada cliente se visite una única vez por un único vehículo y todas las rutas comienzan y finalizan en un centro de gravedad. Como resultados se logró la caracterización y diseño de un modelo logístico, que integró la ubicación de punto de acopio, demanda, rutas de recolección, capacidades, como herramienta sólida y actualizada que generara alternativas ambientales para la ciudad.

This article presents a method of calculation that allows us to separate the contribution of a specific vehicle to the overall noise pollution in an urban environment. This method will provide local authorities with new operating models so that the cost of noise can be allocated to a vehicle according to factors such as the number of people it affects, the distance traveled and journey time, the driving style and the type of vehicle and tires. The proposed methodology can be adapted to different noise emission and propagation models, and we select as a basis the CNOSSOS-EU framework for compatibility with the European noise mapping strategy. This method will make it possible to reduce road traffic noise using two long-term strategies: (a) separate distributions of the costs of noise among the vehicles that generate it, with the aim of achieving (b) an increase in pro-environmental behavior with regard to this pollutant.

A vehicle detection method is developed based on three-axis anisotropic magneto resistive (AMR) sensors along travel lane markings. The method integrates multiple algorithms and uses different geomagnetic waveforms which are disturbed by vehicles passing a single AMR sensor. This method comprehensively analyses X-, Y-, and Z-axis information and applies a double-window algorithm to extract a single vehicle waveform. The vehicle mixed algorithm (VMA) is developed to differentiate vehicles driving by the AMR sensor simultaneously and determine vehicle flow rates. In addition, the vehicle motion-state discrimination algorithm (VMSDA) is developed to distinguish the vehicle operating status (i.e. driving on the left lane, the lane line, or the right lane). The field experimental tests verified the effectiveness of the both algorithms. Results indicate that the average accuracy rates of VMA and VMSDA can, respectively, be up to 98.0 and 96.4%.

We consider the problem of finding the optimal routing of a single vehicle that starts its route from a depot and delivers a product to N customers that are served according to a particular order. ...

In single vehicle probe data measured on German freeways the authors have revealed free flow→synchronised flow→free flow transitions that occur before traffic breakdown at a bottleneck occurs. Thus resulting in the formation of a congested pattern. The empirical findings of these phase transitions confirm a recent microscopic stochastic theory of traffic breakdown developed by Kerner. Only because of the recently introduced possibility of gathering larger amounts of anonymised vehicle data – including a sequence of positions of each car – the authors are able to show the phenomenon of these phase transitions in measured floating car data. This contribution reveals empirical findings in microscopic data which support and prove some of the recent theoretical findings of the nature of traffic breakdown.

The number of arc routing publications has increased significantly in the last decade. Such an increase justifies a second annotated bibliography, a sequel to Corberan and Prins Networks 56 2010, 50-69, discussing arc routing studies from 2010 onwards. These studies are grouped into three main sections: single vehicle problems, multiple vehicle problems and applications. Each main section catalogs problems according to their specifics. Section 2 is therefore composed of four subsections, namely: the Chinese Postman Problem, the Rural Postman Problem, the General Routing Problem GRP and Arc Routing Problems ARPs with profits. Section 3, devoted to the multiple vehicle case, begins with three subsections on the Capacitated Arc Routing Problem CARP and then delves into several variants of multiple ARPs, ending with GRPs and problems with profits. Section 4 is devoted to applications, including distribution and collection routes, outdoor activities, post-disaster operations, road cleaning and marking. As new applications emerge and existing applications continue to be used and adapted, the future of arc routing research looks promising. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 703, 144-194 2017

This article investigates the temporal stability of the factors that increase the risk of rollover in single-vehicle collisions by utilizing logistic regression modeling to analyze annual records of all single-vehicle collisions that occurred in North Carolina from January 1, 2004 to December 31, 2013. A separate model was developed for each analysis year, and all the models were compared together to identify the most temporally stable factors. The factors that were found to consistently increase the risk of rollover are vehicle age, exceeding the speed limit, rural highways, curved highways, drivers younger than the age of 21 years, drivers influenced by alcohol, illicit drugs, fatigue, or other medical conditions, and when the light-duty vehicle involved in the collision is not a passenger car. Conversely, three factors were found to have no temporally stable effect on the risk of rollover in single-vehicle collisions. Those three factors are undivided highways, driver gender, and adverse enviro...

Roadside trees can help calm traffic, define roadways and reduce drivers’ stress. However, roadside trees are also one of the most common components of urban infrastructure involved in single-vehicle crashes. The aim of this review is to identify and summarise research findings on risk assessment for tree crashes and the effect of roadside vegetation on drivers’ psychology and behaviour. The literature was obtained by entering keywords into multiple search engines and tracking down references that were cited in articles that were on-point. This literature review summarises findings from road safety research, identifying trends in tree and site factors that have been used to model single car crash frequency and severity. In looking at 10 similar studies, 8 found that the location of a tree (i.e. distance from the roadway) was a significant predictor of crash likelihood or severity. Other recurring predictors of tree-related car crashes include time of day and roadway geometry (e.g. the presence of ...

This paper addresses the longitudinal vehicle behavior before and during lane changes. Hereby, it is desired that the lane-changing vehicle simultaneously follows its predecessors on the lanes before and after the lane change. Specifically, the lane changing vehicle should keep a safe distance to the rearmost predecessor vehicle, while maintaining a small inter-vehicle spacing and supporting driving comfort. To this end, the paper develops an extension of cooperative adaptive cruise control (CACC). Instead of following a single vehicle as in the classical realization of CACC, it is proposed to follow a virtual vehicle that is evaluated based on distance measurements and communicated state information from the predecessor vehicles. A simulation study demonstrates the practicability of the proposed method.

This paper seeks to investigate the effects of passengers on driver-injury severities. Using single-vehicle crashes, a random parameters logit model with heterogeneity in parameter means is estimated to explore the differences in driver-injury severities in three distinct subgroups; vehicles with one occupant (driver-only), vehicles with two occupants (driver and a passenger), and vehicles with three occupants (driver and two passengers). In addition to considering age, gender and the presence of the passenger(s), a wide range of variables that potentially affect driver-injury severity were considered, including weather conditions, roadway characteristics, vehicle characteristics and driver attributes. Estimation results show that both the age and the gender of the passenger(s) significantly affected driver-injury severities. The findings of this research point toward the need to further study the potentially complex interactions between drivers and passengers.

Despite the vast body of literature on vehicle routing problems, little attention has been paid to multi-compartment vehicle routing problems that investigate transportation of different commodities on the same vehicle, but in different compartments. In this project, we present two strategically different versions of the MCVRP in general settings. In the first version, different commodities may be delivered to the customer by different vehicles, but the full amount of each product must be delivered by a single vehicle. In the second version, each customer may only be serviced by a single vehicle, which must deliver the full amount of all commodities demanded by that customer. We present a Branch-and-Price algorithm for solving the two versions of the problem to optimality and we analyze the effect of the strategic decision of whether or not to allow multiple visits to the same customer by comparing the optimal costs of the two versions. Computational results are presented for instances with up to 100 customers and the algorithm can solve instances with up to 50 customers and 4 commodities to optimality.

Motorcycles represent an increasing proportion of traffic fatalities in the United States, accounting for more than 12.7% of the total traffic casualties within 2005–2014. Specifically, in North Carolina, motorcycles comprise less than 1% of vehicles involved in crashes but account for more than 7% of total fatalities, representing a top state in the United States. This study tries to investigate the motorcycle crashes in North Carolina more in depth. In doing so, five years’ (2009–2013) worth of crash data was obtained from the Federal Highway Administration’s Highway Safety Information System database. A partial proportional odds (PPO) logistic regression model was developed to examine the influence of the explanatory variable on the ordered dependent variable, that is, injury severity. Moreover, two other popular ordered-response models, that is, proportional odds and non-proportional odds models, as well as one similar unordered-response model, that is, multinomial logit model, were also deve...

Background Previous studies have shown increased precipitation to be associated with higher frequency of traffic collisions. However, data regarding how extreme weather events, projected to grow in frequency, intensity, and duration in response to a changing climate, might affect the risk of motor vehicle collisions is particularly limited. We investigated the association between frequency of extreme heat and precipitation events and risk of motor vehicle collision in Maryland between 2000 and 2012. Methods Motor vehicle collision data was obtained from the Maryland Automated Accident Reporting System. Each observation in the data set corresponded to a unique collision event. This data was linked to extreme heat and precipitation events that were calculated using location and calendar day specific thresholds. A time-stratified case-crossover analysis was utilized to assess the association between exposure to extreme heat and precipitation events and risk of motor vehicle collision. Additional stratified analyses examined risk by road condition, season, and collisions involving only one vehicle. Results Overall, there were over 1.28 million motor vehicle collisions recorded in Maryland between 2000 and 2012, of which 461,009 involved injuries or death. There was a 23% increase in risk of collision for every 1-day increase in extreme precipitation event (Odds Ratios (OR) 1.23, 95% Confidence Interval (CI): 1.22, 1.27). This risk was considerably higher for collisions on roads with a defect or obstruction (OR: 1.46, 95% CI: 1.40, 1.52) and those involving a single vehicle (OR: 1.41, 95% CI: 1.39, 1.43). Change in risk associated with extreme heat events was marginal at best. Conclusion Extreme precipitation events are associated with an increased risk of motor vehicle collisions in Maryland.

Waste collection is one of the most critical logistics activities in modern cities with considerable impact on the quality of life, urban environment, city attractiveness, traffic flows and municipal budgets. Despite the problem’s relevance, most existing work addresses simplified versions where container loads are considered to be known in advance and served by a single vehicle depot. Waste levels, however, cannot be estimated with complete certainty as they are only revealed at collection. Furthermore, in large cities and clustered urban areas, multiple depots from which collection routes originate are common, although cooperation among vehicles from different depots is rarely considered. This paper analyses a rich version of the waste collection problem with multiple depots and stochastic demands by proposing a hybrid algorithm combining metaheuristics with simulation. Our ‘simheuristic’ approach allows for studying the effects of cooperation among different depots, thus quantifying the potential savings this cooperation could provide to city governments and waste collection companies.

Roundabouts reduce fatal and injury crashes at intersections when converted from other intersection control types. In Wisconsin, roundabouts have been linked to a 38% decrease in fatal and injury crashes. Part of this reduction can be attributed to crash types that result in the mitigation of more serious injuries. However, the reduction comes at a cost because other crash types, such as single-vehicle collisions, may increase. Six years of crash data on 53 roundabouts in Wisconsin were examined for crash causes and geometric characteristics that affected single-vehicle crashes. Weather and impaired driving, particularly by younger drivers, were primary causes for more than half of all single-vehicle crashes at the study roundabouts. Younger drivers (18 to 24 years of age) were involved in a significantly higher proportion of single-vehicle crashes than the total proportion of licensed drivers in that age group. Younger drivers were involved in approximately one-third of all crashes that involved impaired driving and in two-thirds of all speed-related single-vehicle crashes. A negative binomial model was constructed to estimate run-off-road crashes at approaches. It was found that roundabouts with higher approach speeds and higher traffic volumes experienced more run-off-road crashes. Landscaped central islands experienced significantly lower frequencies of run-off-road crashes.

The objective of this research is to identify the factors differentiating between single heavy vehicle collisions at intersections and midblocks by using a binary logit model. Our results show that single vehicle crashes involving heavy vehicle at intersections are more likely to occur on main roads and highways, whereas crashes at midblocks are more likely to occur on divided two-way roads, roads with special facilities or features (e.g. bridge) and roads with a higher percentage of heavy vehicle traffic. Intersection crashes are also more likely to involve vehicles that are turning left or right, resulting in angle crashes and vehicle overturn, whereas midblock crashes are more likely to involve vehicles on higher posted speed roads.

In the Melbourne metropolitan area in Australia, an average of 34 pedestrians were killed every year between 2004 and 2013 in traffic crashes, and vehicle–pedestrian crashes accounted for 24% of all fatal crashes. Mid-block crashes accounted for 46% of the total pedestrian crashes in the Melbourne metropolitan area and 49% of the pedestrian fatalities occurred at mid-blocks. This study developed three models using different decision trees (DTs) to identify the factors contributing to the severity of pedestrian crashes. To improve the accuracy, stability and robustness of the DTs, bagging and boosting techniques were used in this study. The results of this study showed that the boosting technique improved the accuracy of individual DT models by 46%. Moreover, the results of boosting DTs showed that neighbourhood social characteristics were as important as traffic and infrastructure variables in influencing the severity of pedestrian crashes.

There is a lack of knowledge regarding in-vehicle concentrations of nitrogen dioxide (NO2) during transit through road tunnels in urban environments. Furthermore, previous studies have tended to involve a single vehicle and the range of in-vehicle NO2 concentrations that vehicle occupants may be exposed to is not well defined. This study describes simultaneous measurements of in-vehicle and outside-vehicle NO2 concentrations on a route through Sydney, Australia that included several major tunnels, minor tunnels and busy surface roads. Tests were conducted on nine passenger vehicles to assess how vehicle characteristics and ventilation settings affected in-vehicle NO2 concentrations and the in-vehicle-to-outside vehicle (I/O) concentration ratio. NO2 was measured directly using a cavity attenuated phase shift (CAPS) technique that gave a high temporal and spatial resolution. In the major tunnels, transit-average in-vehicle NO2 concentrations were lower than outside-vehicle concentrations for all vehicles with cabin air recirculation either on or off. However, markedly lower I/O ratios were obtained with recirculation on (0.08–0.36), suggesting that vehicle occupants can significantly lower their exposure to NO2 in tunnels by switching recirculation on. The highest mean I/O ratios for NO2 were measured in older vehicles (0.35–0.36), which is attributed to older vehicles having higher air exchange rates. The results from this study can be used to inform the design and operation of future road tunnels and modelling of personal exposure to NO2.

Snowy weather is consistently considered as a hazardous factor due to its potential leading to severe fatal crashes. A seven-year crash dataset including rural highway single vehicle crashes from 2010 to 2016 in Washington State is applied in the present study. Pseudo elasticity analysis is conducted to investigate significant impact factors and the temporal stability of model specifications is tested via a likelihood ratio test. The proposed model based on the seven-year dataset is able to capture the individual-specific heterogeneity across crash records for four significant factors, i.e., surface ice, male, and airbag combine deployment for minor injury, and male for serious injury and fatality. Their estimated parameters were found to be normal distribution instead of fixed value over the observations. Other significant impact factors with fixed effects are: inroad object, animal, overturn, surface wet, surface snow, unusual horizontal design, medium and high speed limits, driver age, impaired condition, no belt usage, vehicle type, airbag deployment. Especially, when compared to significant factors for crashes under other weather conditions, male indicator and impaired condition show significant higher effects in snow-related crashes. The results of temporal stability test show that the model specification is generally not temporally stable for driver injury severity model based on the years of crash data that were used, especially for longer period (more than 3-year dataset). Models that allow the explanatory variables to track temporal heterogeneity, are of great interest and can be explored in future research.

Near-real-time water-quality monitoring in uncertain environments such as rivers, lakes, and water reservoirs of different variables is critical to protect the aquatic life and to prevent further propagation of the potential pollution in the water. In order to measure the physical values in a region of interest, adaptive sampling is helpful as an energy- and time-efficient technique since an exhaustive search of an area is not feasible with a single vehicle. We propose an adaptive sampling algorithm using multiple autonomous vehicles, which are well-trained, as agents, in a Multi-Agent Reinforcement Learning (MARL) framework to make efficient sequence of decisions on the adaptive sampling procedure. The proposed solution is evaluated using experimental data, which is fed into a simulation framework. Experiments were conducted in the Raritan River, Somerset and in Carnegie Lake, Princeton, NJ during July 2019.

Verification and robustness testing of machine learning algorithms for autonomous driving is crucial. Due to the increasing complexity and quantity of those systems in a single vehicle, just driving the required distance with a newly developed vehicle is not feasible anymore: billions of hours on the street without failure are necessary to qualify for industry standards like ISO 26262. That is where simulation comes into play: machine learning algorithms are trained and evaluated on well known image data sets like KITTI or Cityscapes. But today’s data sets mostly contain images taken under perfect weather conditions and therefore do not harden optical object detection algorithms against various weather conditions. This paper focuses on reusing these established and labeled data sets by augmenting them with adverse weather effects like snow and fog. Those effects are rendered physically correct and life like while being added to existing real world images. Thanks to easy parametrization the weather influences may be varied as necessary and allow for finely tuned learning and optimization processes. The weather effects are evaluated with regard to realism and impact on an established object detection algorithm. These newly created weather-influenced images may be used to validate or train new object detection algorithms.

Traffic microsimulation has been used extensively to evaluate consequences of different traffic planning and control policies in terms of travel time delays, queues, pollutant emissions and every other common measured performance while at the same time traffic safety has not been considered in common traffic microsimulation packages as a measure of performance for different traffic scenarios. The absence of safety evaluation with microscopic simulation models is due to a lack of complete and established models for the simulation of potential crashes. Commonly-used procedures for safety evaluation with microscopic simulation have been based on traffic conflict theory which until recently was not extended to single vehicle crashes and to crashes between vehicles which are moving on non-conflicting trajectories. This paper presents some applications of a new procedure based on potential crash events simulation for the evaluation of safety levels in microsimulated traffic scenarios which takes into account also potential crashes with road side objects and barriers.

Vehicles were operating as platoon is a fundamental approach to solve the problem of road traffic efficiency. When a vehicle travels in the two-lane highway, it could overtake only by using the opposing lane. The platoon makes the ego vehicle face the problem of overtaking, which not only interfering with the traffic efficiency improving but also adding the risk of collision. In order to solve this problem, a step-by-step VOPDS (vehicle overtakes the platoon based on driving style) algorithm was proposed, in which an optimal speed matching scheme by researching the relationship between the speed of vehicles before the slot, the speed of vehicles behind the slot, the speed of vehicle joining a platoon and the required safety slot was designed. Also, a Hierarchical Constrained Multi-objective Optimization Method Based on Improved Particle Swarm Optimization is proposed, which provides the optimized speed guidance strategy for the vehicle overtaking a platoon model. In order to make the speed guidance information be accepted by drivers, this paper got driver behavior characteristics statistics by using open-source driving-simulation tool CARLA, through experiments. The algorithm-simulation results imply that the improved particle swarm optimization algorithm has stronger robustness and faster convergence than the traditional algorithms, optimized results which be more in line with drivers’ driving style showed an improved both overall operating efficiency and comfortable for single vehicle overtaking a platoon scenario.

According to the Spanish General Traffic Accident Directorate, in 2017 a total of 351 pedestrians were killed, and 14,322 pedestrians were injured in motor vehicle crashes in Spain. However, very few studies have been conducted in order to analyse the main factors that contribute to pedestrian injury severity. This study analyses the accidents that involve a single vehicle and a single pedestrian on Spanish crosstown roads from 2006 to 2016 (1535 crashes). The factors that explain these accidents include infractions committed by the pedestrian and the driver, crash profiles, and infrastructure characteristics. As a preliminary tool for the segmentation of 1535 pedestrian crashes, a k-means cluster analysis was applied. In addition, multinomial logit (MNL) models were used for analysing crash data, where possible outcomes were fatalities and severe and minor injured pedestrians. According to the results of these models, the risk factors associated with pedestrian injury severity are as follows: visibility restricted by weather conditions or glare, infractions committed by the pedestrian (such as not using crossings, crossing unlawfully, or walking on the road), infractions committed by the driver (such as distracted driving and not respecting a light or a crossing), and finally, speed infractions committed by drivers (such as inadequate speed). This study proposes the specific safety countermeasures that in turn will improve overall road safety in this particular type of road.

We consider the coordination of transportation and batching scheduling with one single vehicle for minimizing total weighted completion time. The computational complexity of the problem with batch capacity of at least 2 was posed as open in the literature. For this problem, we show the unary NP-hardness for every batch capacity at least 3 and present a polynomial-time 3-approximation algorithm when the batch capacity is at least 2.