Urban Traffic Management System Research Articles

The impact of strategic transport policies on future urban traffic management systems

Urban traffic management and traffic signal control systems, denoted as Urban Traffic Control (UTC) systems, are used extensively worldwide by Local Government Authorities (LGAs) when implementing strategic transport policies. However, it is not clear how well the requirements imposed by LGA policy implementation will be met by UTC systems being developed for the future. Therefore, research was undertaken to analyse how delivery of urban transport policies over the next 5–10 years would shape LGAs' requirements for the next generation of UTC systems, and thereby to identify Key Performance Indicators (KPIs) to provide user-led guidance for future system development. A two-stage survey of LGA policy makers and implementers from around the world was conducted. The results produced consensus among the group of participants (n = 16) on 17 KPIs, representing a synthesis of expert opinions on the desired features of future UTC systems from a policy implementation perspective. The research makes an important contribution in eliciting the wide-ranging breadth of issues associated with delivering strategic transport policies and understanding how these issues affect the requirements LGAs have for future UTC systems. Aligning future UTC system capabilities with LGAs’ requirements will enable more effective implementation of strategic urban transport policies worldwide and allow the benefits to society associated with those policies to be realised.

A Survey on Operation Concept, Advancements, and Challenging Issues of Urban Air Traffic Management

The recent growth and adoption of unmanned aerial vehicles (UAVs) is due to their low development cost, high aerial mobility, advanced battery technology, rotors, gyroscopes, GPS, cameras, sensors, and wide range of applications. The UAV offers new possibilities for business in civil and noncivil applications such as parcel delivery, aerial mapping, agriculture, wildlife conservation, surveillance, and search and rescue. However, considering the exponential growth of various types of aerial vehicles, it is clear that advanced air traffic management services are urgently needed to control and handle the ever-increasing air traffics. In this paper, we first present the two major low-altitude UAV traffic management systems in the United States and Europe and compare them thoroughly. We present the global vision and advancement of UAV traffic management system. To understand the complexity of future air transportation system, we discuss the necessary elements required for an urban air traffic management system. We provide key strategic elements for an advanced urban traffic management through connectivity, open source, safety enhancement, and automation to maximize its impacts on the innovative future air traffic and mobility system. In the end, we discuss the challenging security issues in urban traffic management system.

«SMART CITY» IN THE CONTEXT OF CYBERSECURITY: INCIDENTS, RISKS, THREATS

Smart city systems are becoming more and more widespread in the nearest future. Their deployment allows focusing on combining diverse and varied urban information systems into a single sustainable, energy-efficient, low carbon energy, wasteless, clean "ecosystem" which will be friendly and comfortable for its citizens. This system integrates into itself all existing city IT-systems from individual smartphones to complex urban traffic management systems. And the practice shows that the IT-systems of the smart city do not yet sufficiently meet requirements of security and protection from attacks, malware and external threats. In this respect, the Ukrainian epidemic of ransomware WannaCry and Petya presents a good example. It wasn't targeted attack, ransomware wasn't directed or aimed at any of metropolitan or urban infrastructure it-systems, but as a result of collateral damage, more than a third of Ukrainian computer networks (including banking and state ones) were disabled. There is also a significant and growing demand for a targeted attack against industrial and urban infrastructure. Currently, cases of the following attacks are already known and considered in detail: the malicious computer worm Stuxnet which targets industrial systems and is believed to be responsible for causing substantial damage to the nuclear program of Iran and related malware as Duqu and Flame, Triton/Trisis malware which the first appearance was at a petrochemical plant in 2017, and was aimed at attacking the "last line of defense" - safety instrumented systems (SIS) of Schneider Triconex. Thus, it was only a matter of time before smart city faces IT-infrastructure attack. The paper considers sources of threats and the reasons for the weak security of smart city IT-systems including the following: an increase of the attack surface, the lack of a unified strategy and security service, the developers' emphasis on simplicity and ease of systems deployment at the expense of security, a large percentage of wireless technologies that facilitate access to critical infrastructure objects, the presence of obsolete and legacy code sections in the system. The article proposes a set of measures and actions for smart city IT-systems hardening. Also, the paper considers redundancy and inefficiency of old protection methods and measures such as "air gap", proprietary protocols, "secure by obscure" and others. Keywords: smart city, information ecosystems, cybersecurity, municipal economy, risks, threats, incidents, protection.

Dynamic RFID Identification in Urban Traffic Management Systems.

The paper covers the application of Radio Frequency IDentification (RFID) technology in road traffic management with regard to vehicle identification. Various infrastructure configurations for Automated Vehicle Identification (AVI) have been presented, including configurations that can be used in urban traffic as part of the Smart City concept. In order to describe the behavior of multiple identifications of moving vehicles, an operation model of the dynamic identification using RFID is described. While it extends the definition of the correct work zone, this paper introduces the concept of dividing the zone into sections corresponding to so-called inventory rounds. The system state is described using a set of matrices in which unread, read, and lost transponders are recorded in subsequent rounds and sections. A simplified algorithm of the dynamic object identification system was also proposed. The results of the simulations and lab experiments show that the efficiency of mobile object identification is conditioned by the parameters of the communication protocol, the speed of movement, and the number of objects.

Traffic parameter estimation and control system based on machine vision

With the rapid development of urbanization in the world, it has brought enormous pressure on urban traffic management and control such as traffic congestion. An excellent urban traffic management and control system consists of three critical aspects: obtaining traffic parameters, developing traffic control scheme, and evaluating traffic control scheme. Intersection signal timing is one of the most important parts in urban traffic control. This paper proposed an intersection signal timing system based on traffic video which consists of three parts: acquisition of video-based traffic parameters, calculation of traffic flow-based signal timing scheme, and evaluation of intersection signal timing scheme. In the first part, we used advanced techniques such as deep learning and image processing to obtain traffic parameters such as traffic flow, vehicle type, composition of different vehicle types, and speed of vehicles passing through a scene in a traffic video. In the second part, we calculated the signal timing scheme of the video at the traffic scene through the obtained traffic flow information with Webster method. In the third part, the detailed traffic parameters and signal timing scheme were input into the VISSIM software for traffic microscopic simulation, which was used to evaluate the signal timing scheme. The experimental results show that the accuracy of the detailed traffic flow information obtained by the proposed system can reach more than 90%, the accuracy of composition of different vehicle types can be achieved more than 98%, and the vehicle speed accuracy can reach more than 95%. Therefore, the system improves the reliability and adaptability of the whole signal timing network. At the same time, the simulation results show that the proposed system integrates the acquisition of traffic parameters and the calculation and evaluation of signal timing schemes, and provides a good solution for solving research problems and actual needs such as signal timing optimization.

Understanding Human Activity and Urban Mobility Patterns From Massive Cellphone Data: Platform Design and Applications

Large-scale cellphone data provide an emerging source for acquiring urban movements and patterns. Existing researches on cellphone data based travel behavior detection are mostly concentrated on algorithms exploration and evaluation. The framework and layers of the monitoring platform from data collection to application are not very clear, and existing platform are mostly concentrated on limited functions, some important travel characteristics and influencing factors have not been clearly explored. Therefore, this paper tries to propose a real-time urban mobility monitoring and traffic management platform using cellular data. First, the systems and essential modules of the platform including global system architecture, functional service system, core technology system, data system, and security & privacy protection system are proposed. Second, a field case study in Guiyang China, covering over 3 million people daily and a total 3 years 600TB cellphone data, is carried out to evaluate the methods. 6 visualization platforms 36 sub-functions including jobs-housing distribution, real-time passenger mobility, regional contacting, hotspot passenger attraction, traffic congestion and distribution etc. are constructed and analyzed. This paper aims to provide practical experience and reference for urban mobility monitoring and traffic management system construction using cellular data.

A deep-learning model for urban traffic flow prediction with traffic events mined from twitter

Short-term traffic parameter forecasting is critical to modern urban traffic management and control systems. Predictive accuracy in data-driven traffic models is reduced when exposed to non-recurring or non-routine traffic events, such as accidents, road closures, and extreme weather conditions. The analytical mining of data from social networks – specifically twitter – can improve urban traffic parameter prediction by complementing traffic data with data representing events capable of disrupting regular traffic patterns reported in social media posts. This paper proposes a deep learning urban traffic prediction model that combines information extracted from tweet messages with traffic and weather information. The predictive model adopts a deep Bi-directional Long Short-Term Memory (LSTM) stacked autoencoder (SAE) architecture for multi-step traffic flow prediction trained using tweets, traffic and weather datasets. The model is evaluated on an urban road network in Greater Manchester, United Kingdom. The findings from extensive empirical analysis using real-world data demonstrate the effectiveness of the approach in improving prediction accuracy when compared to other classical/statistical and machine learning (ML) state-of-the-art models. The improvement in predictive accuracy can lead to reduced frustration for road users, cost savings for businesses, and less harm to the environment.

Optimization of work of urban passenger transport

Recommendations for improving the organization of the logistics system of urban passenger traffic based on the formation of adaptive properties proposed. Definitions of organization and lack of organization of the system, target entropy, orderliness, disorder are considered. The calculation of these indicators allows us to conclude how the company is adapted to the external environment. An important feature of all production systems is the focus of their functioning. If such a system is functioning, it means, first of all, that it solves a finite set of tasks to ensure the adaptability of the urban passenger traffic management system to the flow of passengers and with a certain accuracy the goals of organization and management, of which there is also a finite set. The authors come to a fair conclusion that the lack of organization of functioning is a consequence of the influence of the external environment on the control object, while organization is a quantitative measure of the ability of the system to adapt to the effects of environmental factors. The indicator of organization can be proposed as a criterion that assesses the efficiency of the urban passenger transport system. The worse the internal structures are organized, the less efficiently the control system works and the more mobile and uncertain the external environment, the greater the discrepancy between the goal and the final result.

A Spatio-Temporal Flow Model of Urban Dockless Shared Bikes Based on Points of Interest Clustering

With the advantages of convenient access and free parking, urban dockless shared bikes are favored by the public. However, the irregular flow of dockless shared bikes poses a challenge for the research of flow pattern. In this paper, the flow characteristics of dockless shared bikes are expounded through the analysis of the time series location data of ofo and mobike shared bikes in Beijing. Based on the analysis, a model called DestiFlow is proposed to describe the spatio-temporal flow of urban dockless shared bikes based on points of interest (POIs) clustering. The results show that the DestiFlow model can find the aggregation areas of dockless shared bikes and describe the structural characteristics of the flow network. Our model can not only predict the demand for dockless shared bikes, but also help to grasp the mobility characteristics of citizens and improve the urban traffic management system.

Application of Artificial Intelligence Technology in Metro Passenger Flow Control

With the development of science and technology in China, artificial intelligence technology has been widely applied in many fields because of its advantages, and it also plays a good role in promoting the development of urban subway industry. This paper expounds the technology of artificial intelligence, analyzes the composition of artificial intelligence in urban subway traffic management system, and explores the artificial intelligence technology in urban subway traffic management, in the form of realizing the use of passenger flow control value, inspiring people to constantly explore the application of artificial intelligence technology, and better services in the development of the economy, to improve people’s lives.

Application of GIS technology in the construction of urban traffic sharing multimedia information platform

With the gradual maturity of geographical multimedia information system, applying geographical multimedia information system to urban intelligent traffic management information system and urban traffic sharing information platform can realize unified management and real-time update of traffic information. Through the urban traffic sharing information platform, it can increase the value of information. The multimedia information of the entire intelligent traffic management system can be stored, organized and processed by the shared multimedia information platform. It can more effectively ensure the correctness, comprehensibility and avoid redundancy of data relationships. Then it improves the utilization and transmission speed of multimedia information in the system. The urban traffic multimedia information management system has improved the use efficiency of urban road construction in China. And it also made the traffic multimedia information system more scientific and intelligent. It can also improve its management level and play an important role in urban traffic management. This paper first briefly analyzes the current traffic situation and the development of intelligent traffic multimedia information system in China. The basic concepts of GIS and urban intelligent transportation system based on GIS are introduced secondly. At last, the possibility about GIS as urban intelligent traffic management system sharing multimedia information platform is analyzed. The system framework and the basic function of GIS platform are put forward, and the application of GIS in urban traffic common information platform using the key technical support was discussed. It expounds the application of GIS in urban traffic common multimedia information platform.

Towards a Generic Multimodal Architecture for Batch and Streaming Big Data Integration

Big Data are rapidly produced from various heterogeneous data sources. They are of different types (text, image, video or audio) and have different levels of reliability and completeness. One of the most interesting architectures that deal with the large amount of emerging data at high velocity is called the lambda architecture. In fact, it combines two different processing layers namely batch and speed layers, each providing specific views of data while ensuring robustness, fast and scalable data processing. However, most papers dealing with the lambda architecture are focusing one single type of data generally produced by a single data source. Besides, the layers of the architecture are implemented independently, or, at best, are combined to perform basic processing without assessing either the data reliability or completeness. Therefore, inspired by the lambda architecture, we propose in this paper a generic multimodal architecture that combines both batch and streaming processing in order to build a complete, global and accurate insight in near-real-time based on the knowledge extracted from multiple heterogeneous Big Data sources. Our architecture uses batch processing to analyze the data structures and contents, build the learning models and calculate the reliability index of the involved sources, while the streaming processing uses the built-in models of the batch layer to immediately process incoming data and rapidly provide results. We validate our architecture in the context of urban traffic management systems in order to detect congestions.

An approach to GIS-based traffic information system using Spatial Oracle

Traffic congestion is a threat to the economical, environmental, social and sustainable development of a city. The traffic management has always been an issue of concern for urban areas of a city. Geographic information system (GIS) offers an effective solution to the traffic management of a city and it helps the peoples to find out necessary information regarding traffic, road, location and direction of a destination. General traffic system is limited in data sharing and it is difficult to achieve integration in data processing. In this work, an urban traffic management system based on geographic information system (GIS) is implemented to handle the roads, landmarks, sensitive areas and traffic information for urban traffic police locus. Our work solves various traffic related problems and retrieves the traffic centres that have to be alert in different situations. The detected shortest path is visualized with the connected paths in our approach.

An approach to GIS-based traffic information system using Spatial Oracle

Traffic congestion is a threat to the economical, environmental, social and sustainable development of a city. The traffic management has always been an issue of concern for urban areas of a city. Geographic information system (GIS) offers an effective solution to the traffic management of a city and it helps the peoples to find out necessary information regarding traffic, road, location and direction of a destination. General traffic system is limited in data sharing and it is difficult to achieve integration in data processing. In this work, an urban traffic management system based on geographic information system (GIS) is implemented to handle the roads, landmarks, sensitive areas and traffic information for urban traffic police locus. Our work solves various traffic related problems and retrieves the traffic centres that have to be alert in different situations. The detected shortest path is visualized with the connected paths in our approach.

Traffic Management for Emergency Vehicle Priority Based on Visual Sensing.

Vehicular traffic is endlessly increasing everywhere in the world and can cause terrible traffic congestion at intersections. Most of the traffic lights today feature a fixed green light sequence, therefore the green light sequence is determined without taking the presence of the emergency vehicles into account. Therefore, emergency vehicles such as ambulances, police cars, fire engines, etc. stuck in a traffic jam and delayed in reaching their destination can lead to loss of property and valuable lives. This paper presents an approach to schedule emergency vehicles in traffic. The approach combines the measurement of the distance between the emergency vehicle and an intersection using visual sensing methods, vehicle counting and time sensitive alert transmission within the sensor network. The distance between the emergency vehicle and the intersection is calculated for comparison using Euclidean distance, Manhattan distance and Canberra distance techniques. The experimental results have shown that the Euclidean distance outperforms other distance measurement techniques. Along with visual sensing techniques to collect emergency vehicle information, it is very important to have a Medium Access Control (MAC) protocol to deliver the emergency vehicle information to the Traffic Management Center (TMC) with less delay. Then only the emergency vehicle is quickly served and can reach the destination in time. In this paper, we have also investigated the MAC layer in WSNs to prioritize the emergency vehicle data and to reduce the transmission delay for emergency messages. We have modified the medium access procedure used in standard IEEE 802.11p with PE-MAC protocol, which is a new back off selection and contention window adjustment scheme to achieve low broadcast delay for emergency messages. A VANET model for the UTMS is developed and simulated in NS-2. The performance of the standard IEEE 802.11p and the proposed PE-MAC is analysed in detail. The NS-2 simulation results have shown that the PE-MAC outperforms the IEEE 802.11p in terms of average end-to-end delay, throughput and energy consumption. The performance evaluation results have proven that the proposed PE-MAC prioritizes the emergency vehicle data and delivers the emergency messages to the TMC with less delay compared to the IEEE 802.11p. The transmission delay of the proposed PE-MAC is also compared with the standard IEEE 802.15.4, and Enhanced Back-off Selection scheme for IEEE 802.15.4 protocol [EBSS, an existing protocol to ensure fast transmission of the detected events on the road towards the TMC] and the comparative results have proven the effectiveness of the PE-MAC over them. Furthermore, this research work will provide an insight into the design of an intelligent urban traffic management system for the effective management of emergency vehicles and will help to save lives and property.

PERFORMANCE OF SELF-ORGANIZED AND METACOGNITIVE NEUROFUZZY SYSTEM FOR TRAFFIC FLOW PREDICTION

Accurate prediction of traffic flow is an important step needed in urban traffic management systems. While several neurofuzzy approaches have been used in literature for this particular problem, most of them need manual intervention in the formulation of the fuzzy rule base and also in determining the architecture of the neurofuzzy system. This paper evaluates two recent neurofuzzy algorithms that are capable of automatically determining the rule base and architecture in a purely data driven approach. An open source traffic data has been evaluate and compare the performance of these neurofuzzy systems.

Efficiency Evaluation of Beijing Intelligent Traffic Management System Based on super-DEA

AbstractIntelligent traffic management system (ITMS) is an effective measure to improve the urban road transport system operating efficiency. With the practice of Beijing urban intelligent traffic management system, this paper takes the urban transportation systems, socio-economic system and energy environment system as the input system, and sets the road traffic management efficiency and urban transport putting indicators as the output systems. The paper develops a corresponding super-efficiency DEA model, and examines the coordination degree between the ITMS level and urban development. The field data of Beijing from 2000 to 2010 are used for empirical analysis. Based on the model results and the practices of Beijing, the paper comparatively analyzes the relative effectiveness trend of urban transportation and the subsystems of economy and energy environment. It aims to provide some references for the future development and construction of the Beijing ITMS.

Missing data imputation for traffic flow based on improved local least squares

Complete and reliable field traffic data is vital for the planning, design, and operation of urban traffic management systems. However, traffic data is often very incomplete in many traffic information systems, which hinders effective use of the data. Methods are needed for imputing missing traffic data to minimize the effect of incomplete data on the utilization. This paper presents an improved Local Least Squares (LLS) approach to impute the incomplete data. The LLS is an improved version of the K Nearest Neighbor (KNN) method. First, the missing traffic data is replaced by a row average of the known values. Then, the vector angle and Euclidean distance are used to select the nearest neighbors. Finally, a regression step is used to get weights of the nearest neighbors and the imputation results. Traffic flow volume collected in Beijing was analyzed to compare this approach with the Bayesian Principle Component Analysis (BPCA) imputation approach. Tests show that this approach provides slightly better performance than BPCA imputation to impute missing traffic data.

Development and Application of an Evaluation Framework for Urban Traffic Management and Intelligent Transport Systems

The aim of this paper is to present and apply a new evaluation framework for traffic management and Intelligent Transport Systems, to assist urban transport authorities in assessing relevant policies and technologies as to their performance. The principles behind performance measures and indices are outlined, along with a description of theframework development methodology. Two Key Performance Indicators (KPIs) for the topics of mobility and traffic accidents respectively are formulated and operative definitions are presented. Then, the new KPIs are applied to a case study in the city of Paris, involving the introduction of a scheme granting priority to buses at signalised junctions. The results from the before- and after-analysis are reported and interpreted, not only in terms of the case study itself, but most importantly from the standpoint of the applicability of the evaluation framework.

Review of urban traffic management and the impacts of new vehicle technologies

Traffic congestion is a growing problem in most urban areas across the world. In recent years, the problem has often been tackled by management of existing capacity rather than the traditional concept of more road building. This requires efficient traffic management tools and has led to widespread implementation of advanced traffic control systems integrated within a wider urban traffic management (UTM) environment. UTM systems collect data from various sources, process and manage the data and use this information to implement various measures to manage traffic. While infrastructure-based UTM systems continue to develop, there is now also a rapid market-driven development of vehicle technologies and in-vehicle driver support systems. Driver information and satellite navigation (sat-nav) systems are two examples already in widespread use, whereas other applications under research and development include intelligent speed adaptation (ISA), adaptive cruise control (ACC) and various other safety-related applications. This study will firstly present state-of-the-art reviews of UTM and in-vehicle systems. It will then discuss the potential impacts of new in-vehicle systems on UTM and opportunities for beneficial cooperation between the two. The research described in the study has been undertaken within a collaborative project FUTURES, funded by the Engineering and Physical Sciences Research Council (EPSRC).