Intelligent Transportation Systems

A multitude of new technologies (ranging from guidance systems to speed-limit exceeding systems and to fatigue detection systems) are emerging, many of which are either explicitly targeted to older drivers or expected to benefit them the most. However, these same older drivers are more likely to find adapting to the use of such technologies challenging. Therefore, understanding older drivers' perception of such devices will allow experts to take the necessary steps to ensure their smoother acceptance and complete success of their deployment. Using Greek drivers' data collected within the scope of an extensive recent survey in 23 European countries (the SARTRE-3 dataset), a statistical analysis of the perception of usefulness and acceptance of new technologies by older drivers is presented, indicating that -in this dataset-older drivers are more willing to accept these new technologies. The results of the developed ordered logit models provide insight into the human-factors' aspect of the introduction of advanced technologies with respect to the more sensitive segments of the driver population.

Today, Islamic banks (IB) are starting to understand the relevance and importance of knowledge sharing. They are also beginning to appreciate knowledge as the most significant and valued asset that leads to organizational performance. Hence, promising motivational factors are expected to be helpful in emphasizing the need for employees to share not only crucial knowledge but also new knowledge to further ensure that the Islamic banking industry possesses the competitive edge they seek. This study aims to compare the use of IT to support KS behavior between staff members in conventional banks that have included Islamic banking in their system (CBs) and IB in Malaysia. The methodology in this study involves connecting two types of data when the researcher realizes the need to collect additional data after analysing the first set of data. The second phase of the research, which is based on the results of the first phase, is marginal, supportive, and intended to explain the initial resu...

The rapid proliferation of unmanned aerial vehicles (UAVs) has introduced both opportunities and challenges within the European Union. This research paper examines the dual aspects of drone utilization in the EU, focusing on security threats posed by unauthorized drone incursions and regulatory frameworks designed to ensure safe integration into civilian airspace. Drawing from recent incidents in 2025, including drone disruptions at airports in Denmark and Norway, the analysis highlights how these events-often linked to hybrid warfare tactics-underscore vulnerabilities in critical infrastructure. The European Union Aviation Safety Agency (EASA) has implemented a comprehensive riskbased regulatory system since 2021, with 2025 updates emphasizing harmonized rules across member states, including drone classifications, registration requirements, and operational restrictions. This framework aims to foster innovation in sectors such as agriculture, delivery services, and surveillance while mitigating associated risks. Through comparative analysis, the paper contrasts EU approaches with those of the United States Federal Aviation Administration (FAA) and China's regulatory models, revealing differences in emphasis on privacy protection, security priorities, and commercial growth strategies. The study employs a mixed-method approach, incorporating data from official EASA reports, NATO statements, and public sentiment analyses. Findings indicate that while EU regulations provide a robust foundation for safe drone operations, gaps in counter-unmanned aircraft system (C-UAS) capabilities persist, necessitating enhanced coordination between civilian and military responses. Recommendations include development of unified detection systems along eastern borders, increased investments in C-UAS technologies, and streamlined crossjurisdictional protocols. This paper argues for a balanced strategy that safeguards security without impeding technological advancement, contributing to scholarly discourse on aviation policy and international relations in an era of asymmetric threats.

The critical density of a freeway link is subject to changes over time owing to such circumstances as environmental conditions (snow, rain, etc.) and traffic incidents. Because of the critical density's impacts on the performance of some ramp metering strategies that make use of it as a threshold value for control action, it is necessary to trace the real value of the critical density. Hence, methodologies for the online estimation of critical density using the extended Kalman filter (EKF) and Kalman filter (KF) are proposed in this paper. Basically, critical density is chosen as the state variable to be determined using the system output, namely the measurement of traffic flow on the downstream freeway link. These methods are compared with a similar methodology by Smaragdis et al. ( ) using the same traffic conditions implemented in a macroscopic simulation model based on MATLAB. Then, these proposed methods are evaluated in microscopic simulation environments using PARAMICS. In tracing timedependent changes of real critical occupancy effectively, the results indicate that both methods (using KF and EKF) provide better performance compared with the case where constant critical occupancy is used for all the scenarios tested. Our paper contributes to state of the art by using a novel on-line parameter estimation techniques combined with two different feedback based ramp metering strategies namely ALINEA and MIXCROS and then by testing this new approach in a highly stochastic microscopic simulation environment that can be considered a close representation of real-world conditions. TRB 2006 Annual Meeting CD-ROM Paper revised from original submittal.

The present disclosure provides a method of monitoring for an unstable approach of an aircraft during flight in one aspect, the method including: determining, using values of a ground speed and a height of the aircraft derived from measurements acquired during the flight, a specific energy of the aircraft during an approach phase
of the flight. The method further includes determining a reference specific energy of the aircraft, defining an energy range relative to the reference specific energy, and visually displaying, using a first flight instrument of the aircraft, an indicator of the specific energy relative to the energy range.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

This first survey obtained background information and opinions/experiences on participating drivers about railroad crossings. A total of 752 professional drivers representing 34 companies participated in the survey. Drivers gave an average effectiveness rating of 4.7 for crossing gates, 4.5 for flashing lights, 3.5 for clanging bell, 3.3 for train horn, 3.1 for crossbuck signs, and 3.0 for advance warning signs (5 means very high and 1 means very low). About 47% of the drivers said that railroad crossings present a significant driving hazard above normal driving conditions, but 46% said they do not. Seventy four percent of the drivers said that most railroad crossings are adequately protected/have adequate safety warning devices. However, 22% said that the crossings need more protection/more warning devices. The perception of hazards does not depend on the frequency of crossing railroad tracks or the number of times the drivers stop at the crossings. The perception of hazards does not influence the rating of the effectiveness of the warning devices. However, the perception of hazards influences the drivers' views on the current standard of railroad grade crossing devices. The precautions drivers take when crossing the tracks are influenced by their perception of hazards and the adequacy of the current standard of warning devices. Drivers who thought crossings needed more protective warning devices rely on the train horn and advance warning signs more than other groups of drivers. Their view of the current standard of railroad warning devices also depends on the type of vehicle they drive. A higher proportion of the drivers in the group that thinks that railroad crossings need more protection drove a bus most frequently.

Waste management is one of crucial problems in developed living areas. It is also an area of problems and threats for normal functioning. Therefore this is an object of interest of lots of specialist including logisticians. Improving waste management is not only projecting flows but also using mathematical methods of optimization of elements of these flows.

Mobilności zorganizowanym w ramach realizacji projektu Caravel/Civitas II. Odbyło się ono w Urzędzie Miasta Krakowa w dniu 17 września br. Było ono poświęcone prezentacji prowadzonych prac z zakresu logistyki miejskiej i wymianie poglądów na ten temat. Artykuł powstał jako refleksja po dyskusji o systemach dostaw ładunków do centrum Krakowa. W ostatnich kilku dekadach nastąpił znaczący wzrost zapotrzebowania na przewóz towarów (nazywanych w tym artykule również ładunkami) w miastach, wzrosły także oczekiwania i ambicje wszystkich podmiotów zaangażowanych w partycypacji w korzyściach, jakie daje dostępność towarów. Zainteresowani są praktycznie wszyscy; bezpośrednio korzyści (lub ich brak) odczuwają dostawcy, pośrednicy w dostawach oraz odbiorcy ładunków (detaliści), klienci -nabywcy oraz (pośrednio) użytkownicy dróg . Zmiany te podyktowane są rosnącą konsumpcją z jednej strony i wzrostem świadomości konsumenckiej i obywatelskiej z drugiej strony. Warto przyjrzeć się prognozom gospodarczym (tablica 1). Podstawowym źródłem wzrostu gospodarczego po stronie popytowej staną się inwestycje i spożycie krajowe. Zgodnie z prognozami makroekonomicznymi tempo wzrostu konsumpcji prywatnej będzie w Polsce nieco wolniejsze od wzrostu produktu krajowego brutto wynosząc średnio ,9% w latach 005-006 i 5,0% w okresach 007-013 i 014-00. W latach 005-006 inwestycje będą rosły średniorocznie w tempie 6,8%, w latach 007-013 -8,%, zaś w okresie 014-00 ich wzrost ustabilizuje się na poziomie 4,7%.

— Chittagong is the Commercial Capital of Bangladesh. The study area at Agrabad in Chittagong is one of the most commercial activity centers of Chittagong. Many light industry and commercial land use and residential area are found by the both side of the road. This study is mainly focused on the demand & supply of parking system analysis in Agrabad commercial area. Existing parking accommodation, parking demand, parking index, parking turnovers, parking management, parking types are analyzed on the base of modified patrol survey. Both off street & on street parking have surveyed to find out the actual measurement of the demand & supply of parking in the Agrabad commercial area. Highest number of vehicles was calculated to find out the peak hour time where vehicles are parked in highest numbers. Some specific purposes are determined for which the illegal on street parking is increased day by day. The demand supply ratio is also finding out in data analysis part.

Urban centers across the globe are grappling with the growing challenge of traffic congestion, vehicular emissions, and inefficient road usage. As cities expand and vehicle numbers continue to rise, conventional traffic monitoring systems are proving increasingly inadequate. They are often reactive, manually managed, and lack the dynamic adaptability to respond to real-time traffic fluctuations. In the context of the smart city framework, there is a pressing need for intelligent, autonomous systems that can actively monitor, analyze, and optimize traffic flows using real-time data. This paper presents a comprehensive approach to the development of an AI-based real-time traffic monitoring system tailored specifically for the requirements of modern smart cities. Using a combination of machine learning algorithms, deep learning object detection frameworks, edge computing, and IoT integration, this system can detect vehicle counts, classify vehicle types, identify congestion hotspots, and detect road anomalies such as stalled vehicles or accidents. The system architecture is designed for scalability, with an emphasis on low-latency processing and userfriendly dashboard visualization. Experimental deployments demonstrate a significant improvement in traffic management efficiency, situational awareness, and response coordination. The proposed system is not only technically robust but also aligned with sustainable urban mobility goals.

This paper presents an edge-deployable, real-time adaptive traffic light control system designed for complex and undisciplined urban traffic environments. The system integrates computer vision and Internet of Things (IoT) technologies to enable smart traffic management. A robust dataset was developed to capture diverse traffic conditions, including occlusions and unstructured vehicle movement. A lightweight vehicle detection model, based on (You Only Look Once) YOLO and deployed on a Jetson Xavier NX-powered roadside edge node (RSEN), enables real-time traffic monitoring with a mean Average Precision (mAP) of 90% and 74 frames per second (FPS). To improve traffic flow representation, we introduce a traffic density estimation method that incorporates Passenger Car Equivalent (PCE) factors, considering the varying impact of different vehicle types. The estimated density is used by an adaptive traffic light control (ATLC) algorithm, deployed on a resource-constrained Portenta H7 board, which dynamically adjusts signal timings using real-time data, starvation prevention, and tie-breaking mechanisms. The proposed system reduces traffic congestion at intersections by up to 33% and waiting times by 23% compared to traditional fixed-time controls. The proposed framework is cost-effective, scalable, and fully operational on edge devices, offering a practical solution for real-world smart city deployments. INDEX TERMS Adaptive traffic signal control, deep learning, edge computer vision, hardware implementation, intelligent transportation systems, Internet of Things, real-time vehicle detection, YOLO, traffic density estimation.

The paper describes an implementation of interface for playing chess game realized through motion detection and object tracking. User hand movements are recorded with a web camera and used to move chess pieces in a given board position. We are primarily concerned with the perception and identification of user movements compared to the chess playing strategies and the game logic. The interpretation of the chessboard position and the computer next moves are performed using standard chess engine. This work contributes to the development of more natural interfaces that enable communication via user motions and gestures instead of standard computer devices.

Sustainable traffic behaviour is increasing in importance as traffic volume rises due to population growth. In this paper, a model for traffic flow at a stationary bottleneck is developed to determine the parameters that cause congestion. Towards this goal, traffic density, speed, and delay were acquired during peak and off-peak periods in the morning and afternoon at a stationary bottleneck in Peshawar, KPK, Pakistan. The morning and afternoon peak periods have high densities, low speeds, and considerable delays. Regression models are developed using this data. These results indicate that there is a linear relationship between density and time at the stationary bottleneck and a negative linear relationship between density and speed. Thus, an increase in density increases the time delay and reduces the speed. I comprehensive traffic delay model is characterized by a stationary bottleneck. The Kolmogorov-Smirnov (KS) test and P-values were used to identify the best-fit distribution for speed and density. The binomial and generalized extreme values are considered the best fits for density and speed. The results presented can be used to develop accurate simulation models for stationary bottlenecks to reduce congestion.

South Africa is known for its high level of road fatalities (Vanderschuren et al., 2017). In order to curb the problem, various solutions have been proposed, with mitigation efforts achieving varying level of successes between provinces. In the Western Cape, despite substantial improvement to combat the road safety burden, more needs to be done to continue this downward trend. As part of the recent “Western Cape Road Safety Implementation Plan” development, fatality data for the years 2011 to 2015 was taken to a local level. Absolute fatalities, as well as the fatalities per 100 000 population, were compared. Location specific data was also available, providing an opportunity to use a Geographic Information System (GIS) to assist in the analysis. This paper starts with a comparison of road safety trends in various South African provinces, followed by a location specific analysis that identified the top ten hazardous locations for the six districts in the Western Cape viz Cape Town M...

Recent smart urban mobility innovations such as intelligent transportation systems, electric vehicles, autonomous vehicles, demand-responsive transportation, shared transportation, and mobility-asa-service are consistently identified as the panacea to many of the economic, social and environmental effects associated with private vehicles-including road congestion, urban sprawl, social exclusion, increased costs, crashes, emissions, and environmental degradation. One of the strategies of many smart urban mobility policies is to view the transportation system from a holistic perspective to seek reduction of negative effects and an improve performance. Nonetheless, given the rapid technological advances in the transportation sector, there is a need to identify and evaluate primary smart mobility innovations from a sustainability perspective. This article presents a thorough technology review and evaluation of the main smart mobility innovations identified in the literature. The study has identified and categorized six main smart mobility innovations most commonly discussed within the literature including: (a) intelligent transport systems; (b) alternative fuel systems; (c) driving automation systems; (d) shared mobility services; (e) demand responsive transport; and (f) integrated mobility systems. Furthermore, this article includes a brief description of their characteristics, applications, and also evaluates their sustainability according to their proposed impacts on transport safety, road congestion, energy consumption, the environment, and accessibility.

Le train à sustentation magnétique T-Flight, de fabrication chinoise, qui sera le véhicule de transport terrestre le plus rapide jamais construit au monde, a été révélé cet été à Pékin – un projet ambitieux qui devrait réduire considérablement les temps de trajet et consolider la réputation de la Chine en tant que leader mondial des réseaux ferroviaires à grande vitesse.

Traffic congestion has been considered one of the most serious global issues confronting all nations in recent years. Basrah City's highways in general, and particularly the highways surrounding and leading to the University of Basrah, the campus of Bab Azzubair, and the college complex, have experienced traffic congestion and higher delays. The focus of this study is to propose some solutions to mitigate traffic congestion and higher delays on these highways. Field traffic data and questionnaires where SPSS was used to analyse the collected data, and Highway Capacity Software (HCS 2010) was used to assess the level of service (LOS) on the highways. The results showed that the LOS reaches level F on Baghdad Street, while other streets range from level B to level C. Two proposals have been suggested to improve the LOS on Baghdad Street: (1) applying a park-and-ride system; and (2) widening Baghdad Street by adding two lanes in each direction. The LOS for both proposals has been evaluated, and the results showed that the first proposal performed better. The analysis of the collected data also showed that public transportation services are very limited on the highways surrounding and leading to the Bab Azzubair campus. Therefore, public transportation services should be promoted and enhanced in Basrah City.

Ageing societies face tough challenges namely in terms of the pressure on their healthcare and social security systems, which makes it urgent to find new models to accommodate current demographic trends. A possible answer to this challenge may come from new integrated and technology-supported services. In this direction, a European roadmapping initiative has addressed the implementation of a new vision for technological support to ageing. The main findings of this initiative are presented as a roadmap, which synthesizes the contribution of a large number of stakeholders
coming from different backgrounds.

The problem of motion planning of an autonomous vehicle amidst other vehicles on a straight road is considered. Traffic in a number of countries is unorganized, where the vehicles do not move within predefined speed lanes. In this paper, we formulate a mechanism wherein an autonomous vehicle may travel on the "wrong" side in order to overtake a vehicle. Challenges include assessing a possible overtaking opportunity, cooperating with other vehicles, partial driving on the "wrong" side of the road and safely going to and returning from the "wrong" side. The experimental results presented show vehicles cooperating to accomplish overtaking manoeuvres.

Probe vehicle data (also known as “floating car data”) can be used to analyze travel time reliability of an existing road corridor in order to determine where, when, and how often traffic congestion occurs at particular road segments. The aim of the study is to find the best reliability performance measures for assessing congestion frequency and severity based on probe data. Pilot surveys conducted on A2 motorway in Poland confirm the usefulness and reasonable accuracy of probe data for measuring speed variation in both congested and free-flowing traffic. Historical probe vehicle data and traditional traffic counts from Polish S6 expressway were used to analyze travel time reliability on its 24 road sections. Travel time indexes and reliability ratings for the whole year 2016 were calculated to identify segments with lower reliability and higher expected delay. It is concluded that unlike the HCM-6 method, travel times obtained from probe data should be averaged in 1-hour intervals....

The present paper deals with the study of drivers' behavior at individual level when interactions affect vehicle movements in several urban traffic conditions. Main objectives of the research, which is still on progress, are the investigation of the 2-car following behavior, even in a non consecutive scheme, through the assessment of existing well-known models and searching for possible alternative formulations, as well as the analysis of platoon departures at signals in order to deduce useful information to improve usual calibration of ...

The objective of the research is the experimental validation of macro traffic relationship combining micro and macro data. We exploit the well-known relationship between the microscopic car following model and the macroscopic flow model in steady-state conditions. Microscopic data have been detected in a series of experiments involving vehicles equipped with differential high frequency sampling GPS devices in several urban traffic conditions. Aggregate data have been collected through fixed detector, such as ...

From 2001 to 2003, the Federal Highway Administration (FHWA) Road Weather Management program partnered with the National Weather Service (NWS) to conduct five research projects through the Cooperative Program for Operational Meteorology, Education and Training (COMET) (www.comet.ucar.edu). The goal was to create teams of personnel from State Departments of Transportation (DOT), NWS Weather Forecast Offices (WFO), and universities to foster collaborative and productive relationships between meteorological and transportation agencies. These teams were to use data from Road Weather Information Systems (RWIS) to improve the utilization of these data in both weather and transportation operations and to create new predictive algorithms for use in road maintenance activities. Such advances in road weather management ultimately will improve safety and mobility on the roads, and DOT productivity in operations. This document summarizes the five research projects, including research results and lessons learned. It concludes with general recommendations for all State DOTs to inform future collaborative research efforts.

Resurgent interest in artificial intelligence (AI) techniques focused research attention on their application in aviation systems including air traffic management (ATM), air traffic flow management (ATFM), and unmanned aerial systems traffic management (UTM). By considering a novel cognitive human–machine interface (HMI), configured via machine learning, we examined the requirements for such techniques to be deployed operationally in an ATM system, exploring aspects of vendor verification, regulatory certification, and end-user acceptance. We conclude that research into related fields such as explainable AI (XAI) and computer-aided verification needs to keep pace with applied AI research in order to close the research gaps that could hinder operational deployment. Furthermore, we postulate that the increasing levels of automation and autonomy introduced by AI techniques will eventually subject ATM systems to certification requirements, and we propose a means by which ground-based AT...

Progress in spaceflight research has led to the introduction of various manned and unmanned reusable space vehicle concepts, opening up uncharted opportunities for the newborn space transport industry. For future space transport operations to be technically and commercially viable, it is critical that an acceptable level of safety is provided, requiring the development of novel mission planning and decision support tools that utilize advanced Communication, Navigation and Surveillance (CNS) technologies, and allowing a seamless integration of space operations in the current Air Traffic Management (ATM) network. A review of emerging platform operational concepts is conducted, highlighting both the challenges and the opportunities brought in by the integration with conventional atmospheric air transport. Common launch and re-entry planning methodologies are then discussed, where the physical and computational limitations of these approaches are identified and applicability to future commercial space transport operations is assessed. Attention is then turned to the on-orbit phase, where the unique hazards of the space environment are examined, followed by an overview to the necessary elements required for space object de-confliction and collision avoidance modelling. The regulatory framework evolutions required for spacecraft operations are then discussed, with a focus on space debris mitigation strategies and operational risk assessment. Within the atmospheric domain, possible extensions and alternatives to the conventional airspace segregation approaches are identified including promising Air Traffic Flow Management (ATFM) techniques to facilitate the integration of new-entrant platforms. Lastly, recent modelling approaches to meet on-orbit risk criteria are discussed and evolutionary requirements to improve current operational procedures are identified. These insights will inform future research on CNS/ATM and Avionics (CNS + A) systems and associated cyber-physical architectures for Space Traffic Management (STM).

STAQ – Static Traffic Assignment with Queuing: Model properties and applications Luuk Brederode, Adam Pel, Luc Wismans, Erik de Romph & Serge Hoogendoorn To cite this article: Luuk Brederode, Adam Pel, Luc Wismans, Erik de Romph & Serge Hoogendoorn (2018): STAQ – Static Traffic Assignment with Queuing: Model properties and applications, Transportmetrica A: Transport Science, DOI: 10.1080/23249935.2018.1453561 To link to this article: https://doi.org/10.1080/23249935.2018.1453561

Various strategies exist to choose the best intersection design considering the operational performance of an intersection. There are model-based strategies which for example choose the design with the minimal average delay or rule-based strategies which choose the design based on the total volume or specific safety preferences. These strategies choose the design for a local situation. The analysis of network effects (e.g. the total travel time in the network) of these strategies is an unexplored area of research. This paper provides some first insights in the network effects of various local intersection design strategies in comparison with a global network optimization. Strategies, advising all-way stop-controlled, two-way stop-controlled and signalized intersections and roundabouts are tested on the well-known Sioux Falls network. Results show substantial differences between the network performances and solutions of the different strategies, providing a base for future improvemen...

This paper presents a theoretical framework to derive static, quasi-dynamic, and semi-dynamic traffic assignment models from a general first order dynamic traffic assignment model. By explicit derivation from a dynamic model, the resulting models maintain maximum consistency with dynamic models. Further, the derivations can be done with any fundamental diagram, any turn flow restrictions, and deterministic or stochastic route choice. We demonstrate the framework by deriving static (quasidynamic) models that explicitly take queuing and spillback into account. These models are generalisations of models previously proposed in the literature. We further discuss all assumptions usually implicitly made in the traditional static traffic assignment model.

Multi objective optimization of externalities of traffic solving a network design problem in which Dynamic Traffic Management measures are used, is time consuming while heuristics are needed and solving the lower level requires solving the dynamic user equilibrium problem. Use of response surface methods in combination with evolutionary algorithms could accelerate the determination of the Pareto optimal set. Three of these methods are compared with employing the SPEA2+ evolutionary algorithm without use of these methods. The results show that the RSM methods accelerate the search considerably at the start, but tend to converge faster and therefore loose their head start.

Gezgin robot sistemleri alanında araştırmalar gün geçtikçe artmaktadır. Gerçek robotlarla, bu geliştirme ortamını kurmak zaman kaybına ve zamanla robotların yıpranması ve maliyet kaybına sebep olmaktadır. Bu çalışmada turtlebot gezgin robotun matlab Simulink ile oluşturulmuş bir kontroller model kullanılarak ROS üzerinden kontrolü gerçeklenmiştir.

This survey presents a comprehensive examination of diverse encryption and decryption techniques, encompassing historical methods like DES to modern approaches such as elliptic curve cryptography and genetic algorithms applied to 3-DES encryption. The paper explores the operational principles, security features, and practical considerations of each cryptographic method, shedding light on strengths, potential vulnerabilities, and real-world applicability. Key aspects such as encryption and decryption efficiency, security mechanisms, and the interplay between symmetric and asymmetric cryptography are addressed. The survey aims to guide researchers, practitioners, and policymakers in making informed decisions for robust and secure data communication and storage. Additionally, the paper identifies potential areas for future research, emphasizing advanced encryption techniques, secure key management, and the integration of cryptographic methods to address emerging challenges in data security.

In today's society, there is an even more apparent need to find solutions to two real causes for concern, where traffic congestion can bare so many adverse consequences, and where levels of obesity are higher than before, the quest to stem the flow of these plagues of modern day living is undeniable. This research considers whether the use of a financial incentive has been an effective and useful tool in achieving at least one of these goals. The overarching aim of this study is to establish the value of the Cycle to Work (tax-free) Bike scheme in encouraging people to cycle to work. Using primary data, collected from 248 scheme participants and 101 non-participants, it attempts to identify whether there was a change in travel behaviour among scheme participants and to what extent; and to evaluate if publicity and promotion of the scheme encouraged scheme participation. The study also investigates which socio-economic and other factors influence the propensity to participate in the scheme, and explores the correlation between stages of behaviour change and a person's intention to cycle. The impact of the Cycle to Work scheme

Meeting the European Green Deal's goal of climate neutrality by 2050 calls for a 90 percent decrease in emissions from the transportation sector. Thus, there is need to accelerate the shift to more sustainable mobility for integrated and smarter multimodal and intermodal mobility. In European countries, more than 70% of the inhabitants live in metropolitan areas. Achieving low-carbon and more sustainable mobility is important to ensuring sustainable urban infrastructure. However, current mobility planning frameworks do not consider the key factors and strategies that encourage residents to choose sustainable transport modes. Hence, there is a need to identify the most efficient actions that should be employed either in the short or long term to achieve accessible, safe, cost-effective, and green transport systems specifically through the development of sustainable public transportation. Moreover, a paradigm shift is needed to explore the synergy between transportation and its relationship to the city. Accordingly, this article presents an action plan as an approach to assess key strategies needed to foster sustainable and smart mobility planning and design by deploying effective strategies and design solutions that support different green means of transportation for smart urban development. Qualitative data on sustainable mobility planning and design strategies was collected via secondary sources from the literature, and descriptive data analysis was carried out. Findings from this study identify internal and external factors required to promote sustainable multimodal and intermodal mobility based on the city's transport policies and actions. Implications from this study provide a use case for the technological requirements required for electric mobility planning, design, and system operation for the actualization of sustainable public transportation to improve smart urban development.

We propose a novel method to estimate capability to make bicycle journeys, specifically considering the individual physical capability (IPC) of entire populations of individuals from all population segments of an area, not just current cyclists. IPC considers the physical constraints on the maximum distance people could cycle given the typical topography of where they live (Distance IPC), and then estimates their ability to make a particular journey (Journey IPC). IPC, when estimated in this way for a particular point in time, may be informed by antecedent behavioral choices and capabilities, and may be a constraint or enabler of subsequent capabilities, potential adaptations and behavior. The focus of the present paper is on explaining a generic method of estimating Distance IPC and Journey IPC by constructing an individually based spatially fine-grained model. We show how such an individual-level model may be implemented for a population resident in many small spatial zones by use of spatial micro-simulation (population synthesis), to generate the individual attributes required as inputs to the model. We present a case-study for the city of Leeds, UK. We explain the range of data sources used, explore sensitivity of the results to assumptions of the model, and illustrate the ability of the model to simulate the effects of policies. Finally, we identify several possible application areas and opportunities to further develop the model.

The continuous integration of advanced driver-assist systems (ADAS) into connected and autonomous vehicles (CAV) is accelerating the transition of human-driven vehicles to a fully driverless option. The most available ADASs in current running vehicles with their functions, level of autonomy, and present scenario of CAV deployment are critically reviewed and summarized in this paper. The expected advantages with the probable and observed uncertainties of the CAV deployment are also presented. The technological accomplishments (advanced digital infrastructures along with other technologies) are incorporating rapid improvement in vehicle automation. This paper reviews the engagement of technologies in the functioning of automated vehicles and their implementation challenges. Physical infrastructures facilitate the features of automation and connectivity in moving on the roads. Various roadside infrastructures with the issues in assisting the CAV for path tracking are summarized in this paper. The reduction of lane width due to lane-keeping ADAS and replacement of human drivers (i.e., eye) by machine impacts the various geometric elements of highways. The reduced lane width and truck platooning from the integration of cooperative adaptive cruise control affect the structural performance of the pavements significantly. This paper addresses the effects of connected and automated driving on geometric elements and the structural performance of highways. In addition, various techniques to minimize the additional distresses of connected and automated driving are also explained in this paper.

Most of the population in great Brazilian cities depends on the public transit for the development of their daily activities. A huge difference between levels of mobility and accessibility can be observed between people who owned and use private cars and those who depend upon public transit. This difference is characterized by (i) the unequal spatial coverage of the transit network when comparing the possibilities available to private car users and public transit users, (ii) the difference in hours of service, (iii) the different levels of the impact on the increasing traffic jam in the operation of both systems, and (iv) the difference in the quality of the information provided for users. These differences configure one more iniquity that the low-income people are submitted. The planning and implementation processes of an Integrated Structural System (ISS) for public transit tried to reduce the iniquities mentioned above offering better levels of mobility and accessibility.

This paper presents a white-box intention-aware decision-making for the handling of interactions between a pedestrian and an automated vehicle (AV) in an unsignalized street crossing scenario. Moreover, a design framework has been developed, which enables automated parameterization of the decision-making. This decision-making is designed in such a manner that it can understand pedestrians in urban traffic and can react accordingly to their intentions. That way, a humanlike response to the actions of the pedestrian is ensured, leading to a higher acceptance of AVs. The core notion of this paper is that the intention prediction of the pedestrian to cross the street and decision-making are divided into two subsystems. On the one hand, the intention detection is a data-driven, blackbox model. Thus, it can model the complex behavior of the pedestrians. On the other hand, the decision-making is a whitebox model to ensure traceability and to enable a rapid verification and validation of AVs. This white-box decision-making provides human-like behavior and a guaranteed prevention of deadlocks. An additional benefit is that the proposed decisionmaking requires low computational resources only enabling real world usage. The automated parameterization uses a particle swarm optimization and compares two different models of the pedestrian: The social force model and the Markov decision process model. Consequently, a rapid design of the decisionmaking is possible and different pedestrian behaviors can be taken into account. The results reinforce the applicability of the proposed intention-aware decision-making.

In many ways, a precondition to realizing the promise of open government data is the standardization of that data. Open data standards ensure interoperability, establish benchmarks in assessing whether governments achieve their goals in publishing open data, can better ensure accuracy of the data. Interoperability enables the use of off-the shelf software and can ease third party development of products that serves multiple locales. Our project aims to determine which standards for civic data are “best” to open up government data. We began by disambiguating the multiple meanings of what constitutes a data standard by creating a standards stack. The empirical research started by identifying twelve “high value” open datasets for which we found 22 data standards. A qualitative systematic review of the gray literature and standards documentation generated 18 evaluation metrics, which we grouped into four categories. We evaluated the metrics with civic data standards. Our goal is to iden...

It is common to increase road capacity by constructing ring roads to reduce traffic congestion in city areas, although this is often found to be ineffective in the long run. Accordingly, this study investigates various traffic congestion management approaches and their effectiveness in major cities, and explores an identical transport problem in Almaty, Kazakhstan: The Big Almaty Ring Road (BAKAD). Several case examples from the existing literature are examined in which various approaches were taken for managing traffic congestion problems, and these approaches are classified into three concepts. The first concept comprises heavy engineering measures such as ring road development, new road construction, expansion of existing roads, etc. Such measures can initially reduce traffic congestion, but often become ineffective with time due to the generation of induced traffic. Many cities have taken Push and Pull measures that ensure more efficient use of existing capacity and have initiat...

Advances in Data Science permeate every field of Transportation Science and Engineering, resulting in developments in the transportation sector that are data-driven. Nowadays, Intelligent Transportation Systems (ITS) could be arguably approached as a “story” intensively producing and consuming large amounts of data. A diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers’ personal devices act as sources of data flows that are eventually fed into software running on automatic devices, actuators or control systems producing, in turn, complex information flows among users, traffic managers, data analysts, traffic modeling scientists, etc. These information flows provide enormous opportunities to improve model development and decision-making. This work aims to describe how data, coming from diverse ITS sources, can be used to learn and adapt data-driven models for efficiently operating ITS assets, systems and processes; in other words, for data-b...

Vehicular networking has become a significant research area due to its specific features and applications such as standardization, efficient traffic management, road safety and infotainment. Vehicles are expected to carry relatively more communication systems, on board computing facilities, storage and increased sensing power. Hence, several technologies have been deployed to maintain and promote Intelligent Transportation Systems (ITS). Recently, a number of solutions were proposed to address the challenges and issues of vehicular networks. Vehicular Cloud Computing (VCC) is one of the solutions. VCC is a new hybrid technology that has a remarkable impact on traffic management and road safety by instantly using vehicular resources, such as computing, storage and internet for decision making. This paper presents the state-of-the-art survey of vehicular cloud computing. Moreover, we present a taxonomy for vehicular cloud in which special attention has been devoted to the extensive applications, cloud formations, key management, inter cloud communication systems, and broad aspects of privacy and security issues. Through an extensive review of the literature, we design an architecture for VCC, itemize the properties required in vehicular cloud that support this model. We compare this mechanism with normal Cloud Computing (CC) and discuss open research issues and future directions. By reviewing and analyzing literature, we found that VCC is a technologically feasible and economically viable technological shifting paradigm for converging intelligent vehicular networks towards autonomous traffic, vehicle control and perception systems.

Time-of-day (TOD) or departure time choice (DTC) has become an interesting issue over two decades. Many researches have intensely focused on time-of-day or departure time choice study, especially workday departures. However, the travel behavior during long-holiday/intercity travel has received relatively little attention in previous studies. This paper shows the characteristics of long-holiday intercity travel patterns based on 2012 New Year data collected in Thailand with a specific focus on departure time choice of car commuters due to traffic congestion occurring during the beginning of festivals. 590 interview data were analyzed to provide more understanding of general characteristics of DTC behavior for intercity travel at the beginning of a Bangkok long-holiday. Moreover, the Multinomial Logit Model (MNL) was used to find the car-based DTC model. The results showed that travelers tend to travel at the peak period when the parameters of personal and household are not so signifi...