Intelligent Transportation Systems

This research explores technical innovation and the impact of resistance to innovation in the implementation of an active traffic management system. Technology-driven change initiatives are often difficult to implement and failure rates are high. Lack of success is often linked to failures in understanding the change environment or failure to account for human factors in the implementation of a new technology. This study explores stakeholder perceptions in the implementation of a variable speed limit (VSL) system in St. Louis, Missouri. Survey data from the driving public and law enforcement officials were analyzed during the first 2 years the VSL system was operational. High levels of dissatisfaction were present in survey results and indicated significant levels of resistance to innovation. Change management theory was used to link sources of dissatisfaction to common resistance factors. This provides an opportunity to develop strategies for the successful implementation of innovative traffic management systems. Decision makers involved with active traffic management will benefit from an understanding of the pervasive nature of resistance to innovation and an awareness of strategies for designing change management processes in innovative traffic systems.

The observation, analysis and construction of cities and forms of mobility are not always in step with the complexity of urban systems and changes in contemporary societies. It is possible to use time as a key to reading the functioning and dysfunctions of cities and as a springboard for new mobilitiesand sustainable urban development policies. This "chronotopic" perspective makes it possible to approach the complexity of urban systems and reflect on ways of "indwelling" times and mobilities. The researcher, the urban planner, the builder and the citizen are invited to change their outlooks, to think, design and manage the city by simultaneously taking into account urban physicality, flows and timetables in order to imagine, together a "malleable city", a more human, accessible and hospitable one.

Purpose-The purpose of this paper is to find a real-time parking location for a four-wheeler. Design/methodology/approach-Real-time parking availability using specific infrastructure requires a high cost of installation and maintenance cost, which is not affordable to all urban cities. The authors present statistical block matching algorithm (SBMA) for real-time parking management in small-town cities such as Bhavnagar using an in-built surveillance CCTV system, which is not installed for parking application. In particular, data from a camera situated in a mall was used to detect the parking status of some specific parking places using a region of interest (ROI). The method proposed computes the mean value of the pixels inside the ROI using blocks of different sizes (8 Â 10 and 20 Â 35), and the values were compared among different frames. When the difference between frames is more significant than a threshold, the process generates "no parking space for that place." Otherwise, the method yields "parking place available." Then, this information is used to print a bounding box on the parking places with the color green/red to show the availability of the parking place. Findings-The real-time feedback loop (car parking positions) helps the presented model and dynamically refines the parking strategy and parking position to the users. A whole-day experiment/validation is shown in this paper, where the evaluation of the method is performed using pattern recognition metrics for classification: precision, recall and F1 score. Originality/value-The authors found real-time parking availability for Himalaya Mall situated in Bhavnagar, Gujarat, for 18th June 2018 video using the SBMA method with accountable computational time for finding parking slots. The limitations of the presented method with future implementation are discussed at the end of this paper.

Cooperative approaches are becoming of great interest in automotive research. One of the most important ITS applications is cooperative localization. In this paper, the concept of a dynamic base station DGPS (DDGPS) and its application in the vehicular cooperative localization is introduced and discussed. The DDGPS is a decentralized cooperative method which aims to improve the GPS positioning by estimating and compensating the common error in GPS pseudorange measurements. It can be seen as an extension of DGPS where the base stations are not necessarily static with an exact known position. In the DDGPS method, the pseudorange corrections are estimated, based on the receiver’s belief on its positioning and its uncertainty, and then broadcasted to other GPS receivers. A new method for fusing all the received corrections from different sources is proposed and the data dependency problem is also discussed.

There has been an increasing role played by Global Navigation Satellite Systems (GNSS) in Intelligent Transportation System (ITS) applications in recent decades. In particular, cen-timeter/decimetre positioning accuracy is required for some safety related applications, such as lane control, collision avoidance, and intelligent speed assistance. Lane-level Anomalous driving detection underpins these safety-related ITS applications. The two major issues associated with such detection are (1) accessing high accuracy vehicle positioning and dynamic parameters; and (2) extraction of irregular driving patterns from such information. This paper introduces a new integrated framework for detecting lane-level anomalous driving, by combining Global Positioning Systems (GPS), BeiDou, and Inertial Measurement Unit (IMU) with advanced algorithms. Specifically, we use Unscented Particle Filter (UPF) to perform data fusion with different positioning sources. The detection of different types of Anomalous driving is achieved based on the application of a Fuzzy Inference System (FIS) with a newly introduced velocity-based indicator. The framework proposed in this paper yield significantly improved accuracy in terms of positioning and Anomalous driving detection compared to state-of-the-art, while offering an economically viable solution for performing these tasks.

Scientists and policymakers intend worldwide emissions reduction of up to 80 percent of carbon dioxide (CO2) and other greenhouse gases (GHGs) in the next four decades to stabilize atmospheric concentrations (TRB 2011). Henceforth, an immediate response from the transportation sector, one of the largest producers of GHGs (up to 30 percent in the U.S.), is critical for GHGs reduction. Possible long-term solutions towards cutting back on emissions from transportation are increasing supply-of/demand-for more energy/fuel efficient vehicles and to substantially improve the transit system (high-speed rail, passenger rail, metro) to reduce reliance on private vehicles and air travel for short trips. However, the markets are still struggling to produce supply-of/demand-for energy efficient vehicles and public debate on potential ridership of high speed rail is ongoing in the U.S. Another feasible strategy that can prove to be effective is emission pricing. Recent advancement in Intelligent ...

El término “movilidad urbana” hace referencia al conjunto de desplazamientos que realizan los ciudadanos dentro de un entorno urbano para satisfacer sus necesidades diarias. Si se combina con la idea de sostenibilidad, entendida como aquel sistema que consume recursos por debajo del nivel de renovación de los mismos, resulta la movilidad urbana sostenible, que serán aquellos desplazamientos que se realizan dentro de la ciudad de forma sostenible.

Son varios los recursos que consume la movilidad: recursos energéticos, tiempo, espacio e incluso al propio ciudadano a través de su salud. Además existen diferentes modos que tienen opción de escoger los ciudadanos para realizar sus desplazamientos.

Un plan de fomento de la movilidad sostenible pasará por potenciar aquellos modos de transporte identificados como más sostenibles en detrimento de aquellos que consumen una mayor cantidad de recursos.

En el presente documento, primero se realiza una reflexión sobre qué es la movilidad sostenible y que modos de transportes son los que se adaptan mejor a este concepto, para después plantear herramientas TIC que fomenten estos modos.

El estudio de las herramientas a aplicar se hace según el modelo de Lean Canvas, que en un primer momento humaniza tanto al cliente como al usuario de cada modo de transporte, buscando entender sus motivaciones y frustraciones hacia el uso de los diferentes modos de transporte, para después plantear propuestas de valor que potencien las motivaciones o reduzca las frustraciones para fomentar los modos de transportes clasificados como sostenibles en una ciudad.

Current approaches for development of collaborative business process
automation,  when  requiring  the  participation  of  multiple  stakeholders,  lack proper  formalization  in  terms  of  the  required  informatics  systems  landscape.
Existing solutions depend on specific technology strategies and do not offer a suitable  model  for  the  fast-growing  collaborative  services.  In  this  paper,  we present the concept of an open informatics system of systems (ISoS), as a holistic framework  that  can  be  applied  to  a  European  wide  payment  system  for collaborative  multimodal  mobility  services.  To  illustrate  how  the  ISoS framework  could  be  applied  in  practice,  we  consider  the  payment  service  to
support public transports, motorway and bridges tolling, payment in parking lots, bicycle renting and payment in a fueling station, all under a single contract. While each participating organization (any infrastructure operator) is free to adopt any applicable  technology,  the  proposed  ECoNet  collaboration  infrastructure  is aimed  to  support  a  multi-supplier  (open)  informatics  system  technology landscape.  Based  on  results  from  previous  research,  the  paper  introduces  a
strategy to allow effective and reliable EU wide collaborative mobility services.

Countries around the world, with the glaring exception of the US under President Donald Trump, are increasingly acknowledging the shift that’s needed from a fossil fuel-driven economy to one that is sustainable, green and attempts to mitigate climate change.

Infrastructure and traffic management technologies can have substantial impact on fuel use and emissions. This paper explores a way to generate information about emissions and other route characteristics for drivers faced with a choice of routes. GPS equippedvehicles were used to traverse various paths between origins and destinations to collect second-by-second trajectory data required for microscale emission analysis. A methodology based on the Vehicle Specific Power (VSP) concept was used to estimate the emissions impact. On-board video footage recorded route features, traffic incidents, and congestion levels. Two different vehicles and drivers traversed several urban and intercity routes to enable the consideration of the influence of driver behaviour and vehicle dynamics. It was found that the choice of a route can substantially affect emission rates of the analysed pollutants and that smoother driving styles can also result in considerable emissions reduction. A trade-off between reducing CO 2 /fuel consumption and local pollutants has been identified. Specifically, faster intercity routes are more desirable in terms of fuel use and CO 2 emissions. However, these same routes yielded carbon monoxide, nitrous oxides, and hydrocarbons emission increases of up to 150%. These findings have implications for future investment and policy decisions regarding eco routing strategies.

Intelligent Vehicles, as a main part of Intelligent Transportation Systems (ITS), will have great impact on transportation in near future. They would be able to understand their immediate environment and also communicate with other traffic participants such as other vehicles, infrastructures and traffic management centres. Intelligent vehicles could navigate autonomously in highway and urban scenarios using maps, GPS, video sensors and so on. To navigate autonomously or follow a road, intelligent vehicles need to detect lanes. It seems that the best cue for lane detection is to use the lane markings painted on roads and it should be noticed that among passive and active sensors, the video sensors are the best candidate for finding lane markings. In this paper we present a method for lane detection in image sequences of a camera mounted behind the windshield of a vehicle. The main idea is to find the features of the lane in consecutive frames which match a particular geometric model. The geometric model is a parabola, an approximation of a circular curve. By mapping this model in image space and calculation of gradient image using Sobel operator, the parameters of the lane can be calculated using a randomized Hough transform and a genetic algorithm. The proposed method is tested on different road images taken by a video camera from Ghazvin-Rasht road in Iran. Experimental results on different road scenes indicate the good performance of the proposed method.

The Internet has become the preferred resource to announce, search and comment about social events such as concerts, sports games, parades, demonstrations, sales or any other public event that potentially gathers a large group of people. These planned special events often carry a potential disruptive impact to the transportation system, because they correspond to nonhabitual behavior patterns that are hard to predict and plan for.

This paper presents a novel automatic and dynamic camera calibration algorithm based on traffic visual surveillance. The algorithm can automatically calibrate the intrinsic and extrinsic parameters of camera, and offer enough guarantee to extract traffic real-time parameters. This paper firstly indicates the significance of applying automatic and dynamic calibration algorithm to intelligent transportation system, then establishes a mathematical model of calibration parameters between camera image and actual road. The algorithm is established from three view points, which are description, flow chart and algorithm description. Afterward this paper describes the experimental method and result based on this novel algorithm. Finally this paper indicates wide application foreground of this algorithm in intelligent transportation system.

As transportation engineers and practitioners continue to advance the scope and breadth of intelligent transportation systems (ITS) applications, privacy is a primary concern of transportation agencies in the United States (US) when tracking people, vehicles and goods within the nation's transportation grid. As a number of technologies have rapidly advanced, including photo enforcement, electronic tolling, vehicle-mile taxing, weigh-in-motion, and Connected Vehicle technologies, research examining the privacy implications of system applications has lagged. In a recent national survey to determine how state departments of transportation (DOTs) are meeting the privacy needs of the traveling public, it was determined that DOTs favor aggregating and masking data for protecting privacy of motorists while collecting travel times and speeds. For capturing video surveillance, abiding by legislation or agency policies was the preferred method of protecting privacy. Unfortunately, there are no national standards in the US for the privacy protection of travelers as most privacy information merely takes the form of poorly defined precepts. With the increasing use of ITS applications, which are becoming more interwoven into the US transportation grid, there is a need to develop a national policy and related standards to ensure the privacy protection of the traveling public to ensure broader acceptance of ITS applications. The findings presented in this paper aim to provide direction on how to address the current and future privacy challenges that face the transportation industry.

This paper provides an agent technology for a decision support system. This system is designed to detect and regulate the traffic of multimodal public transport when many disturbances come simultaneously. The objective of this system is to optimize the regulation action by learning technique of regulator. The goal of this research is to improve the quality of public transport service provided to users and respect the use rules (safety rules, business rules, commercial rules, etc.). So, to improve the quality service of the user, we have to optimize simultaneously several criteria like punctuality, regularity and correspondence in disturbance case. In this paper, we focus primarily on a multi agent system for optimizing and learning of Regulation Support System of a Multimodal Public Transport (RSSPT). We have validated our strategy by simulating situation related to existing transportation system.

The optimal routing problem has always been the main event of city emergency rescue. Its research object has developed from searching for "the shortest route" to searching "the optimal route". The related algorithms and techniques differ in different situations. In addition to distance problem, the influence of various parameters factors should also be analyzed under the complicated conditions. The amount of the accidents in the world is terrifying and it is viewed as the highest in the world. So in this situation, we need an efficient method for fast intervention that will respond in such situations. Therefore, it is important to encourage the study in ambulance management and routing by introducing a new strategy for guiding ambulance toward the position of the accident in an efficient way. A distributed solution is proposed based on the ant colony system algorithm model. The improved method is based on a distributed architecture to compute and find the optimal path for a set of emergency vehicles. Based on the defect of the ambulance route planning, this paper puts forward a new distributed model to find the best way that minimizes the time while taking into consideration the cases of problems that can appear each time such as traffics, speed limit, number of available ambulances, the position of the hospitals.

Abstract: Highway engineers face complicated problems that are influenced by various conditions during the construction of flexible highway pavements. Identifying such problems and recommending effective solutions demand considerable engineering expertise, which is difficult to obtain at all construction sites. Thus, the development of an expert system can effectively help engineers control and analyze such problems. In addition, an expert system can effectively archive the storage and distribution of expertise among pavement ...

The Congress’s principal theme “Experience future mobility now” was chosen to illustrate the radical role Intelligent Transport Systems, digitalisation, and cooperative, connected and automated mobility can play in addressing the key challenges in the mobility and transport sectors. Deployment of ITS can take us further down the road to a mobility world that is accessible, equitable, affordable, has zero fatalities, has zero emissions, is resilient when stressed, and is seamless
across Continents. How to achieve these benefits was presented in policy discussions, technical and research paper sessions, demonstrations, technical tours and the Congress Exhibition. The headline theme was addressed by a wide range of different types of sessions, over 250 in total – Plenary, Executive, Special Interest, Technical, Scientific and a range of Forums.

Part 1 of this Report summarises the Congress proceedings. The second part paints a picture of proceedings at the Plenary and Executive Sessions. The third part focuses mostly on the Technical & Scientific papers and the Special Interest Sessions. The final part summarises the proceedings at the ITS Summit.

New approach to manage congestion using vehicular communication is presented in this work. The research work using MATLAB simulation, tracked communicating vehicles travelling on roads with constant registration of changes in routes, number of hops, and energy consumed as a function of travelled distances. The area of travel and simulation is divided into blocks or zones to enable sufficient allocation and distribution of Road Side Units (RSUs) that are used to relay communication signals and transmission of Basic Safety Messages (BSMs). The successfully concluded simulation is based on the assumption that as congestion occurs, the number of hops per route and associated energy consumption per transmitted packets will change patterns in terms of hops, routes and consumed energy as traffic passes from low to smooth (optimal) to high density (congestion) states, where at the start of congestion, vehicles start to slow down and become closer to each other in a two dimensional space. The output is used as input to traffic status pattern characterization algorithm (management system) that uses the data to indicate the start of traffic accumulation, thus pre-emptive measures can be taken to avoid congestion and reduction in mobility. The presented analysis proved that it is possible to predict congestion as a function of both hops sequences and consumed energy, depending on the hops pattern which is shown to be symmetric in the case of optimum traffic that flows smoothly. The analysis also showed that when congestion starts to occur, asymmetric hops pattern occurs with hops sequences elements switch and swap places within the identified pattern. Further analysis and polynomial curve fitting proved that congestion control and smooth traffic management using the proposed approach is achievable.

The concept of the “smart mobility” has become something of a buzz phrase in the planning and transport
fields in the last decade. After a fervent first phase in which information technology and digital data were
considered the answer for making mobility more efficient, more attractive and for increasing the quality of
travel, some disappointing has grown around this concept: the distance between the
visionarypotentialthatsmartness is providingis too far from the reality of urban mobility in cities. We argue in
particular that two main aspects of smart mobility should be eluded: the first refers to the merely application
to technology on mobility system, what we called the techo-centric aspect; the second feature is the
consumer-centric aspect of smart mobility, that consider transport users only as potential consumers of a
service.
Starting from this, the study critics the smart mobility approach and applications and argues on a“smarter
mobility” approach, in which technologies are only oneaspects of a more complex system. With a view on
the urgency of looking beyond technology and beyond consumer-oriented solutions, the study arguments the
need for a cross-disciplinary and a more collaborative approach that could supports transition towards
a“smarter mobility” for enhancing the quality of life and the development ofvibrant cities. The article does
not intend to produce a radical critique of the smart mobility concept,denying a priori its utility. Our
perspectiveisthat the smart mobility is sometimes used as an evocativeslogan lacking some fundamental
connection with other central aspect of mobility planning and governance.
Main research questions are: what is missing in the technology-oriented or in the consumers-oriented smart
mobility approach? What are the main risks behind these approaches? To answer this questions the paper
provides in Section 2 the rationale behind the paper;Section 3 provides a literature review that explores the
evolution on smart mobility paradigm in the last decades analysing in details the “techno-centric”and the
“consumer-centric” aspects. Section 4proposes an integrated innovative approach for smart mobility,
providing examples and some innovative best practices in Belgium. Some conclusions are finally drawn in
Section 5, based on the role of smart mobility to create not only virtual platforms but high quality urban
places.

Public transportation fleets operate fundamental processes such as toll collection, fleet management, vehicle tracking, passenger information and collection of vehicle information from in-vehicle networks. However, these processes mostly communicate with each other over non-standard communication protocols. Often these functions are provided by different manufacturers, which causes delay during the construction of the required information technologies. Even if the systems and devices of different manufacturers are compatible with each other, their installation processes are challenging. The international Information Technology for Public Transport (ITxPT) standards have recently been defined in order to ensure that companies, providing intelligent transportation technologies to the fleets, are able to properly manage the complex infrastructure in question and to eliminate the problems of compliance. However, since the ITxPT standards are new, there are few studies on the implementation of onboard ITxPT services for public transport systems. In order to contribute these efforts, a system architecture for the implementation of ITxPT services is introduced in this study and the design and implementation of important ITxPT services, called Module inventory, GNSS location and VEHICLEtoIP for a public transportation vehicle has been realized. ITxPT services, designed according to the proposed architecture, have been observed to work successfully on the units of a company producing public transport information systems. The implementation which is based on Avahi System, UDP Multicast and HTTP REST services architecture, allows ITxPT services to be installed, run and monitored more easily and quickly on these Linux-powered units.

Intelligent Vehicles, as a main part of Intelligent Transportation Systems (ITS), will have great impact on transportation in near future. They would be able to understand their immediate environment and also communicate with other traffic participants such as other vehicles, infrastructures and traffic management centres. Intelligent vehicles could navigate autonomously in highway and urban scenarios using maps, GPS, video sensors and so on. To navigate autonomously or follow a road, intelligent vehicles need to detect lanes. It seems that the best cue for lane detection is to use the lane markings painted on roads and it should be noticed that among passive and active sensors, the video sensors are the best candidate for finding lane markings. In this paper we present a method for lane detection in image sequences of a camera mounted behind the windshield of a vehicle. The main idea is to find the features of the lane in consecutive frames which match a particular geometric model....

In this paper, we propose a camera based novel, real-time framework for detection and tracking of vulnerable road users, such as pedestrians and cyclists. Our framework also gives a measure of the degree of vulnerability based on the direction of movement and distance from the vulnerable region. Pedestrians and cyclists are the most vulnerable road users and it is necessary to develop automated systems that can detect them and ensure their safety by alerting the driver. In our framework, we apply deep learning based method for 2D pose detection for detecting the pedestrians and cyclists in the view of the outside looking camera mounted on the dashboard of a vehicle. As the vehicle moves, the pedestrians and cyclists are detected and tracked across frames, their degree of vulnerability is measured and the driver is alerted in case of high vulnerability score. Experimental results show that the our framework is able to accurately detect vulnerable road users and measure their degree of vulnerability.

A baggage screening system is one of the factors that determine air transport security. It prevents objects and materials that could be used to commit an act of unlawful interference from being placed on board an aircraft. The aim of this paper was to present a model and a computer system supporting the management of a security screening checkpoint's organisation at an airport. This model was to take into account the role of the human factor in this process, in particular of many subjective factors that influence the effectiveness of an airport security system, such as an employee's experience, level of training or attitude to the work he/she does. The studied process involves numerous dependencies which are intuitive and subjective in character and which cannot be unequivocally described. Therefore, a fuzzy model and a fuzzy inference system were created because they are suitable for analysing decision making processes in the context of uncertainty. The model was parameterized based on expert assessments as well as measurements and experiments that had been carried out at the Katowice-Pyrzowice airport. The model and the computer system that have been developed make it possible to evaluate the effectiveness of airport security screeners in detecting prohibited items in baggage. The experiments made it possible to evaluate individual employees and groups of employees working during the same shift. The tools that had been obtained allowed us to make a recommendation that comprehensive training sessions should be organised every 12 months and ongoing training sessions should be held every 6 months.

Since the concept of Mobility as a Service (MaaS) was defined in 2014 by Sonja Heikkilä, many transportation agencies around the world have explored the potential of creating MaaS and have piloted MaaS. Specifically, agencies are deploying technologies and creating the partnerships with mobility service providers (MSPs) that are required to provide the basis for full-featured MaaS systems. However, many of the pilots and deployments are in urban areas.

Typically, these areas have not only robust public transportation, but also other mobility services such as bikesharing, scootersharing, carsharing, ridesourcing, etc. This white paper focuses on the application of MaaS in a small urban or rural area, which looks different from a large urban implementation and typically has different goals than large-urban deployments.

This paper describes the progress that has been made with MaaS in several rural and small urban areas in the US by:
• Reviewing the definition of MaaS and related concepts;
• Describing rural MaaS and “Universal MaaS;”2
• Providing examples from agencies that are deploying MaaS;
• Defining a potential MaaS “roadmap;”
• Describing a MaaS readiness index/tool; and
• Describing a potential MaaS evaluation framework.

Mobile Adhoc Network (MANET) is a network of a number of mobile routers and associated hosts, organized in a random fashion via wireless links [16]. During recent years MANET has gained enormous amount of attention and has been widely used for not only military purposes but for search-andrescue operations, intelligent transportation system, data collection, virtual classrooms and ubiquitous computing [14]. Service Discovery is one of the most important issues in MANET. It is defined as the process of facilitating service providers to advertise their services in a dynamic way and to allow consumers to discover and access those services in an efficient and scalable manner [20]. In this paper, we are proposing a flexible and efficient approach to service discovery for MANET by extending the work of [5]. Most of the service discovery protocols proposed in literature don't provide an appropriate route from consumer to service provider. Hence after services are discovered, a route request needs to be initiated in order to access the service. In this paper, we are proposing a robust and flexible approach to service discovery for MANET that not only discovers a service provider in the vicinity of a node, but at the same time, it also provides a route to access the service. We have extended the approach proposed in [5] for efficiency by adding the push capabilities to service discovery

The article deals with the analysis and interpretation of dynamic scenes typical of urban driving. The key objective is to assess risks of collision for the ego-vehicle. We describe our concept and methods, which we have integrated and tested on our experimental platform on a Lexus car and a driving simulator. The on-board sensors deliver visual, telemetric and inertial data for environment monitoring. The sensor fusion uses our Bayesian Occupancy Filter for a spatio-temporal grid representation of the traffic scene. The underlying probabilistic approach is capable of dealing with uncertainties when modeling the environment as well as detecting and tracking dynamic objects. The collision risks are estimated as stochastic variables and are predicted for a short period ahead with the use of Hidden Markov Models and Gaussian processes. The software implementation takes advantage of our methods, which allow for parallel computation. Our tests have proven the relevance and feasibility of our approach for improving the safety of car driving.

In this paper a novel Vehicular cooperative map matching method is presented. This map matching method uses the V2V communication in a VANET to exchange GPS information between vehicles. Then vehicles can apply the road constraints of other vehicles in their own map matching process and acquire a significant improvement in their positioning. The dependency of GPS measurements between different vehicles, which can lead to an over converged positioning result has been considered and circumvented in our method. The performance of the proposed algorithm has been verified with simulations in several realistic scenarios.

The primary objectives of this study are to develop two roundabout entry capacity models using a regression-based multiple non-linear regression model (MNLR) and artificial intelligence (AI)-based ANFIS (adaptive neuro-fuzzy inference system) model under heterogeneous traffic conditions. ANFIS is the latest technique in the field of AI that integrates both neural networks and fuzzy logic principles in a single framework. Required data have been collected from 27 roundabouts in eight states of India. To assess the significance of these models and select the best model among them, modified rank index is applied in this study. The coefficient of determination (R 2) and Nash-Sutcliffe model efficiency coefficient 'E' values are found to be 0.92, 0.91 and 0.98, 0.98 for the MNLR and ANFIS model, respectively. The ANFIS model is found to be the best model in this study. However, from a practical point of view, the MNLR model is recommended for determining roundabout entry capacity under heterogeneous traffic conditions. Sensitivity analysis reports that critical gap is the prime variable and shares 18.43% for the development of roundabout entry capacity. As compared with the Girabase formula (France), Brilon wu formula (Germany), and HCM 2010 models, the proposed MNLR model is quite reliable under low to medium ranges of traffic volumes. Roundabouts are a specialized form of an un-signalized intersection in which traffic moves in one direction around a central island. Direction of traffic, according to left-hand or right-hand driving rules, depends on the specific country. Roundabouts have been used as an effective intersection control measure to improve safety and operational performance under low to high circulating traffic flow conditions. As compared with other, signa-lized, intersections, roundabouts have several basic advantages, such as speed reduction of vehicles, less delay, pedestrian safety, aesthetics, and reduction of conflict points. A signalized intersection has 32 conflict points, whereas a roundabout with two circulating and entry lanes has 8 and 16 conflict points, respectively. Because of the increase in the use of roundabouts, an assessment regarding operational performance needs to be undertaken. Evaluation of capacity at roundabouts is an important aspect of operational performance that describes the present traffic scenario, level of service, delay, accidents, operational cost, and environmental issues. Under heterogeneous traffic conditions, vehicles of various kinds have varying physical and operational characteristics. In developing countries, driver behavior, vehicular characteristics (size, engine efficiency, and years of usage), and intersection geometric design vary significantly. The vehicle fleet is composed of heavy vehicles (HV), light motor vehicles (LMV), motor cycles/ scooters (MC/S), bicycles (BC) and human-drawn vehicles (HDV). These vehicles share the main carriageway without any physical or marked segregation. When there are vehicles of different types with varying static and dynamic characteristics, follow-the-lane discipline and the follow-the-leader concept become irrelevant. Under constraints of flow and space, small-sized vehicles try to move into the circulating area without following lane discipline. Also, HV forcibly merge into the circulating stream of traffic. These points reflect that the rule of priority is not respected under such a heterogeneous traffic condition. In these circumstances, the study of

The river link connecting Central Europe river networks to the Mediterranean has been object of considerations and planning for many years. The progress in technological means and the expression of interest by the Chinese to invest in such a project mean that this project is now mature for materialization. This presentation, the third one in within two years, aims at making preliminary estimates of the traffic it is going to attract and at the gains from its operation for users and countries.

This paper proposes image mosaicking technique for controlling of traffic signals. Limitation of conventional automatic traffic signal control methods is that they can detect the vehicle using sensors, whereas sensors are failed to detect the vehicle, if vehicle is out of range of infrared rays, also sensors are incapable to give response if vehicle stops due to technical problem in the range of infrared rays. This paper proposed an intelligent traffic control method using image mosaicking technique. The striking feature of proposed method is that it measures the density of traffic dynamically .. The efficacy of proposed method has been evaluated, using MATLAB TM Software. It is found that proposed method is quite effective for the control of the traffic signals for controlling congestion on the road.

Detailed specifications of urban traffic from different perspectives and scales are crucial for understanding and predicting traffic situations from the view of an autonomous vehicle (AV). We suggest a data-driven specification scheme for maneuvers at different design elements of the built infrastructure and focus on urban roundabouts in Germany. Based on real observations, we define classes of maneuvers, interactions and driving strategies for cyclists, pedestrians and motorized vehicles and define a matrix for merging different maneuvers, resulting in more complex interactions. The sequences of these interactions, which partially consist of explicit communications, are extracted from real observations and adapted into microscopic traffic flow simulations. The simulated maneuver sequences are then visualized in 3D environments and experienced by bicycle simulator test subjects. Using trajectory segments (in fictional space) from two conducted simulator studies, we relate the record...

O projeto Transcolar Rural foi desenvolvido segundo a necessidade de melhora do sistema de transporte escolar em áreas rurais. Muitos alunos residentes no campo estão em atraso escolar e possuem baixo rendimento, fato que pode ser explicado pela dificuldade de deslocamento dos estudantes até as escolas. Municípios do estado de Minas Gerais têm aderido ao sistema através de um convênio com a Universidade Federal de Minas Gerais (UFMG) a fim de implementar o Transcolar Rural em seus contextos locais. Após a conclusão dos estudos, coleta de dados, e formatação do banco de dados, novas rotas de transporte escolar são geradas pelos modelos de otimização do projeto. Com as viagens definidas, é feito o cálculo de custos e confecção dos relatórios com as informações geradas, sendo esses dois processos o objeto deste artigo. O sistema objetiva diminuir os custos de operação, tanto do próprio programa, quanto da execução das rotas pelos operadores, a fim de produzir resultados a serem utilizados no planejamento do serviço.

Since the advent of modern transportation, the necessity to orderly move huge volumes of vehicles on the road has heightened while the techniques to conduct the orderly movements have grown ever challenging. This paper focuses on a novel approach for handling road traffic by incorporating an intelligent traffic light controlling system with the aid of artificial neural networks algorithm. As our experimental model, we have selected Dhaka city to be the center of our research as it is infested with traffic jam, ranking it towards the top among least livable cities of the world. Our endeavor is to make use of 24/7 Dynamic Traffic Light Controllers (DTLCs) based on artificial neural networks. As part of the solution, we have developed a program using a popular programming platform that would calculate sets of drive orders for traffic signal lights and we have optimized it to run on low power hardware. The output from the application is then verified within a road traffic simulation software. The cumulative results from the experiment portray the efficiency of applying an adaptive algorithm that dynamically calculates the order of signal lights. The decision making algorithm is designed to replicate, in a meager form, the human brain with the system trained to learn to respond to certain traffic situations. Static Traffic Light Controllers (STLCs) handle traffic flow with predetermined traffic conditions. In contrast, our approach would be a fully dynamic and spontaneous solution to mitigate the ongoing traffic crisis.

Abstract: In this paper, intelligent transportation systems, with complete infrastructure with special emphasis on the regional and overall development. The work is based on a large number of papers in these areas and experiences from neighboring countries and the practices of the European Union. In this paper we apply the advantages and benefits brought by the use of these systems in singergiji with modern information technology and IT solutions.
Key words: Ineligentni Transport Systems, Development, ICT, Transport Strategy

Given the current connected vehicles program in the United States, as well as other similar initiatives in vehicular networking, it is highly likely that vehicles will soon wirelessly transmit status data, such as speed and position, to nearby vehicles and infrastructure. This will drastically impact the way traffic is managed, allowing for more responsive traffic signals, better traffic information, and more accurate travel time prediction. Research suggests that to begin experiencing these benefits, at least 20% of vehicles must communicate, with benefits increasing with higher penetration rates. Because of bandwidth limitations and a possible slow deployment of the technology, only a portion of vehicles on the roadway will participate initially. Fortunately, the behavior of these communicating vehicles may be used to estimate the locations of nearby non-communicating vehicles, thereby artificially augmenting the penetration rate and producing greater benefits. We propose an algorithm to predict the locations of individual noncommunicating vehicles based on the behaviors of nearby communicating vehicles by comparing a communicating vehicle's acceleration with its expected acceleration as predicted by a carfollowing model. Based on analysis from field data, the algorithm is able to predict the locations of 30% of vehicles with 9-meter accuracy in the same lane, with only 10% of vehicles communicating. Similar improvements were found at other initial penetration rates of less than 80%. Because the algorithm relies on vehicle interactions, estimates were accurate only during or downstream of congestion. The algorithm was applied to an existing ramp metering algorithm, and was able to significantly improve its performance at low connected vehicle penetration rates, and maintain performance at high penetration rates.

This paper elaborates a macroscopic, non-iterative algorithm to estimate the fuel consumption of vehicles. The algorithm uses the Willan's internal combustion engine model and needs no instantaneous values of speed and acceleration. The efficiency of the proposed algorithm has been compared with measurement results for the following three cycles: motor vehicle expert group (MVEG-95), European driving cycle (ECE), and extra-urban driving cycle (EUDC). For eco-routing, experiments show that there are tradeoffs between fuel savings and travel time. Results reported in this paper show that up to 33% of fuel savings have been achieved at the expense of 3% increase in trip-time.

Dear Colleagues,

Transportation of people and goods is operated in the air, on the land, on the sea, and recently to the edge of the space. Transportation relies on effective vehicles, good infrastructures, as well as good environmental conditions. Transportation contributes significantly to the ongoing changes in climate and is at the same time affected by the global crises which lead to global supply chain shutdowns. The changing climate is creating new waterways in the Arctic, triggering coastal erosion, and is affecting maritime traffic systems. In time, further exciting advancements are expected to emerge in the field of transportation as the USA and the EU are investing billions of USD and EUR, respectively, on new infrastructures, most of them connected with transportation. The challenge is to give the chance to the territories to start their own economies again and to create new systems of soft mobility for new generations of users. With the continuously evolving technologies, transportation of people and goods is becoming smart and intelligent. New autonomous and electrical vehicles are being produced, and government and private sector actors are producing and installing sensors and platforms aiming at providing crucial information on the state of the air, land, and sea. A number of satellites and unmanned aerial vehicle sensors provide crucial information on the state of maritime, land, and air conditions. On-ground sensors and cameras provide important information on the current state of the abovementioned environments. Future transportation will rely heavily on information provided by these sensors, platforms, and their connectivity to transport vehicles. It will greatly benefit from smooth flow of information between these platforms, sensors, and vehicles enabled by the internet and other kinds of modern communications. However, efficiency and the security of that flow and transfer of information is the most important aspect of future transportation of people and goods.

This Special Issue will focus on the latest advances in technologies aiming at future transportation of people and goods. Authors are invited to submit original manuscripts on topics including (but not limited to):

Smart cities and smart logistics;
Blockchain and the Internet of Things;
Artificial Intelligence and machine and deep learning for the mining of raw materials;
Photogrammetry for coastal areas, maritime and land monitoring;
New active and passive sensors for autonomous vehicles;
Geological mapping of nickel, copper, cobalt, and platinum;
Climate and energy technologies;
Evaluation of the impact of transportation on coastal cities and coastal morphological evolution;
New sensors and their applications for fault movements and seismicity analyses and sediment management;
Satellite technologies for transportation of people and goods;
New harbors, new bridges, and tunnel constructions;
Bathymetry mapping of uncharted and hard-to-reach waters for marine transportation and sunk obsolete ships detection.
Prof. Dr. Giovanni Randazzo
Dr. Anselme Muzirafuti
Dr. Dimitrios S. Paraforos
Guest Editors

The Vehicular Ad hoc Network (VANET), gives most ideal chances to the prospective analytics in the Intelligent Transport System (ITS) space, for example, secure passage of vehicles by keeping away from possible threats out and about, pre-educated insights regarding road circumstances, close ahead blockage state of the course, most excellent option ways in the direction of goal amid voyage, infotainment administrations, best business administration's from different administration suppliers, and so on. The Traffic Congestion (TC) is treated as obstacles in the planned journey. The traffic-congestion avoidance event dissemination (T-CAED) algorithm has been an occasion driven method for emergency event management, and road TCs are avoided with successor vehicles with its operations. The ITS with VANET and even distance placement of road side unit(s)' (RSU) on road side assists intelligently to the vehicles in the journey. The study tries to assist the transporters, during TC, via the two kinds of options to do T-CA. The T-CAED algorithm is based on prioritization calculation and is actualized with the rundown of occasions and highlighted occasions. The TC identified intimation and T-CA options intimation have been dispersed to the vehicles via RSUs through the VANET and the vehicles are provided with two options of T-CA. With the simulation, vehicle's congestion avoidance success rate (CASR) is presented on this work to enumerate the importance of un interrupted cum supported travel from source to destination of vehicles.

Object detection and classification is one of the core functions of Intelligence Transport Systems (ITS). It is typically based on extracted features and learning algorithms. Different approaches seem to be appropriate. Researchers should compare and evaluate existing approaches to apply the most efficient. In this paper, we propose a moving vehicle-detection vision system. Two solutions are examined in terms of performance and energy-efficient. The first is a classical Adaboost approach based on the Haar-like in feature extraction whereas the second handles a Local Binary Pattern descriptor that will undergo extraction with Adaboost classifier. Comparison results are illustrated based on the GTI vehicle image dataset. The most pertinent is the Haar-like +Adaboost, leading a DR of 90.1% instead of 87.9% for the LBP+Adaboost. However, LBP+Adaboost shows a low energy consumption, which is very important in any embedded systems.

This paper presents a study of the predictability of bus usage based on massive bus ride data collected from Lisbon, Portugal. An understanding of public bus usage behavior is important for future development of personalized transport information systems that are equipped with proactive capabilities such as predictive travel recommender systems. In this study, we show that there exists a regularity in the bus usage and that daily bus rides can be predicted with a high degree of accuracy. In addition, we show that there are spatial and temporal factors that influence bus usage predictability. These influential factors include bus usage frequency, number of different bus lines and stops used, and time of rides.

Vehicular networks are one of the most challenging research areas in wireless ad hoc networks. The main benefit of this kind of communication is seen in active safety systems, which aim at increasing passengers’ safety by exchanging warning messages between vehicles. A main goal is to resist to various malicious abuses and security attacks. The IEEE1609.2 standard for vehicular ad hoc networks is based on the ECDSA algorithm for supporting the authentication mechanism. However, any security mechanism comes with overheads in terms of computation and communications. This paper provides an assessment of the processing and communication overhead of ECDSA. We analyze the impact of this mechanism on VANET performance. Then we focus on the impact of authentication communication on the braking distance.

Recent examples driving an increased need for cyber awareness include unmanned aerial vehicles (UAVs) in the airspace, development of the Automatic dependent surveillance-broadcast (ADS-B), and the risk of cyber intrusion. The incident of a civilian UAV disrupting a major airport, is one example of many incidents raising questions on the future of airspace security. While a civilian hobbyist might be ignorant of the impending harm, the situation could pose a threat to the air operations. Using this incident and others like it, ideas on the future trends in cyber awareness applied to avionics are considered. Three general ideas are incorporated: (1) mandates for new rules for airspace restrictions (e.g., geofence), (2) advanced display analytics to support the airport staff and pilots with visual displays, such as collision avoidance, and (3) electronics to support the mitigation of electronic cyber effects posed by the obtrusive aircraft. With a variety of opinions posed, the summary is intended to foster a discussion on research, industry, and commercial directions for the avionics community to consider with respect to cyber awareness.

Qinghai-Tibet railway is famous for its constructional difficulties and challenges imposed during construction of the railway line. The Chinese engineers however managed to overcome the challenges like permafrost, provision of steady gradient and tunneling especially at a height of 4.9 km above Mean Sea Level. Also at such a height the oxygen level is another short coming for passengers. This presentation merely discusses the challenges and its solution. It's expected that young students and university students will find this presentation handy for getting a brief idea on the engineering challenges especially in railway engineering in frozen areas.
(Note: This presentation is best viewed in MS office-2010 and above and windows media player of win-7 and above)

The development of electro-mobility is one of the centerpieces of European country attempts to reduce carbon emissions and increase the quality of life in cities. The goals of reducing emissions from the transport sector and phasing out fossil-fueled vehicles in (urban) transport by 2050 present unrivaled opportunities to foster electro-mobility. This paper provides a comprehensive review of the literature and provides a detailed analysis of the current development of electro-mobility in Europe, assessing social, economic, and environmental aspects under a circular economy (CE) context. It also examines the existing challenges and suggests ways of addressing them towards improving the environmental performance of electro-mobility and the urban quality of life. The paper argues that a narrow technology-only agenda in electro-mobility will be less successful without the imperative of the CE, including not just materials and resources but also energy, to unlock the medium-term co-benef...

Design Engineer often require vital information related to field operating condition, which can be used to improve and optimize their designs. To meet this need a data logging/analyzer system has to be developed. Existing systems available in the market which are capable of logging field data are complex, costly and are not able to determine
the overall performance of vehicle due to its limited functionality.
The purpose of this paper is to develop a Data logging and Analyzer System using CANlog4 device that will help us to determine the Engine performance of “John Deere 5000 series Tractor”. The CANlog is a programmable device used to log data on CAN bus. So ftware is developed in LTL programming language for CANlog device such that it will monitor the Tractor CAN bus and will log the engine performance parameters on the bus. An offline analysis is performed on the logged data using ICE-GlyphWorks tool which will help us to Graphing of logged data for performance comparison.
In this paper the behavior of various engine performance parameters like break torque, break power, indicated power, friction power, mechanical efficiency, mean effective
pressure and specific fuel consumption are studied over its speed range which will helps us to do the performance comparison. Also the time distribution of parameters like
engine speed, engine torque, engine break power, engine percent load, fan speed, ambient air and coolant temperature are graphically summarized using Histogram which will helps us to know the concentration areas of the particular parameter over its test period of time. It has been observed from the result that the maximum torque and maximum power developed by the engine is 307 Nm and 64.57 kW at the speed of 1332 rpm and 2450 rpm respectively. The maximum power loss observed is 36kW and the average pressured generated inside the cylinder is 400kN/m2. The maximum mechanical efficiency of the
engine is observed at the speed of 1900 rpm. The engine speed is more concentrated between the ranges 2000 to 2250 rpm during its test period of time.