An Improved Differential Evolution Algorithm for Maritime Collision Avoidance Route Planning

High accuracy navigation and surveillance systems are pivotal to ensure efficient ship route planning and marine safety. Based on existing ship navigation and maritime collision prevention rules, an improved approach for collision avoidance route planning using a differential evolution algorithm was developed. Simulation results show that the algorithm is capable of significantly enhancing the optimized route over current methods. It has the potential to be used as a tool to generate optimal vessel routing in the presence of conflicts

A multi-objective GA-based optimisation for holistic Manufacturing, transportation and Assembly of precast construction

Resource scheduling of construction proposals allows project managers to assess resource requirements, provide costs and analyse potential delays. The Manufacturing, transportation and Assembly (MtA) sectors of precast construction projects are strongly linked, but considered separately during the scheduling phase. However, it is important to evaluate the cost and time impacts of consequential decisions from manufacturing up to assembly. In this paper, a multi-objective Genetic Algorithm-based (GA-based) searching technique is proposed to solve unified MtA resource scheduling problems (which are equivalent to extended Flexible Job Shop Scheduling Problems). To the best of the authors' knowledge, this is the first time that a GA-based optimisation approach is applied to a holistic MtA problem with the aim of minimising time and cost while maximising safety. The model is evaluated and compared to other exact and non-exact models using instances from the literature and scenarios inspired from real precast constructions

A novel online data-driven algorithm for detecting UAV navigation sensor faults

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate

Urban bus positioning: Location based services and high level system architecture

Today’s urban transport systems are dominated by private vehicles, which are significant contributors to traffic congestion and pollution. This is expected to increase as the urban population grows, predicted to account for about 68% of the world’s population by 2050. In comparison to private cars, transport systems dominated by buses produce lower traffic congestion and emissions. Therefore, improvements in bus operation activities most of which require information on bus location (i.e. location based services) should facilitate urban transport sustainability. However, to date there is no agreement globally on the location based services, their location requirements and technologies to deliver significant improvement in bus operations. Therefore, this paper creates for the first time, a comprehensive list of bus operation services and specifies the performance requirements. These are considered together with challenging spatio-temporal characteristics of the urban environment to specify a high-level location determination system architecture for urban bus operations. The services, their requirements, standards and positioning system architecture are essential for the formulation of appropriate policies, regulation, service provision, and development and procurement of urban bus positioning systems

An integrated solution for lane level irregular driving detection on highways

Global Navigation Satellite Systems (GNSS) has been widely used in the provision of Intelligent Transportation System (ITS) services. Current meter level system availability can fulfill the road level applications, such as route guide, fleet management and traffic control. However, meter level of system performance is not sufficient for the advanced safety applications. These lane level safety applications requires centimeter/decimeter positioning accuracy, with high integrity, continuity and availability include lane control, collision avoidance and intelligent speed assistance, etc. Detecting lane level irregular driving behavior is the basic requirement for these safety related ITS applications. The two major issues involved in the lane level irregular driving identification are accessing to high accuracy positioning and vehicle dynamic parameters and extraction of erratic driving behaviour from this and other related information. This paper proposes an integrated solution for the lane level irregular driving detection. Access to high accuracy positioning is enabled by GNSS and Inertial Navigation System (INS) integration using filtering with precise vehicle motion models and lane information. The detection of different types of irregular driving behaviour is based on the application of a Fuzzy Inference System (FIS). The evaluation of the designed integrated systems in the field test shows that 0.5 m accuracy positioning source is required for lane level irregular driving detection algorithm and the designed system can detect irregular driving styles

Integrated design of transport infrastructure and public spaces considering human behavior: A review of state-of-the-art methods and tools

In order to achieve holistic urban plans incorporating transport infrastructure, public space and the behavior of people in these spaces, integration of urban design and computer modeling is a promising way to provide both qualitative and quantitative support to decision-makers. This paper describes a systematic literature review following a four-part framework. Firstly, to understand the relationship of elements of transport, spaces, and humans, we review policy and urban design strategies for promoting positive interactions. Secondly, we present an overview of the integration methods and strategies used in urban design and policy discourses. Afterward, metrics and approaches for evaluating the effectiveness of integrated plan alternatives are reviewed. Finally, this paper gives a review of state-of-the-art tools with a focus on seven computer simulation paradigms. This article explores mechanisms underlying the complex system of transport, spaces, and humans from a multidisciplinary perspective to provide an integrated toolkit for designers, planners, modelers and decision-makers with the current methods and their challenges

Characterisation of GNSS Space Service Volume

There is increasing demand for navigation capability for space vehicles. The idea to extend the application of Global Navigation Satellite Systems (GNSS) from terrestrial to space applications by the use of main beam and side lobe signals has been shown to be feasible. In order to understand the performance and the potential space applications GNSS can support, this paper characterises the Space Service Volume (SSV) in terms of the four parameters of minimum received power, satellite visibility, pseudorange accuracy and Geometric Dilution of Precision (GDOP). This new definition enables the position errors to be estimated. An analytical methodology is proposed to characterise minimum received power for the worst location. Satellite visibility and GDOP are assessed based on grid points at different height layers (to capture the relationship between height and visibility) for single and multiple GNSS constellations, the former represented by BeiDou III (BDS III) and the latter, BDS III in various combinations with GPS, GLONASS and GALILEO. Additional simulation shows that GNSS can potentially support lunar exploration spacecraft at the Earth phasing orbit. This initial assessment of SSV shows the potential of GNSS for space vehicle navigation

Multi-Constellation GNSS Multipath Mitigation Using Consistency Checking

In a typical urban environment, a mixture of multipath-free, multipath-contaminated and non-line-of-sight (NLOS) propagated GNSS signals are received. The errors caused by multipath-contaminated and NLOS reception are the dominant source of reduced consumer-grade positioning accuracy in the urban environment. Many conventional receiver-based and antenna-based techniques have been developed to mitigate either multipath or NLOS reception with mixed success. Nevertheless, the positioning accuracy can be maximised based on the simple principle of selecting only those signals least contaminated by multipath and NLOS propagation to form the navigation solution. The advent of multi-constellation GNSS provides the opportunity to realise this technique that is potentially low-cost and effective for consumer-grade devices. It may also be implemented as an augmentation to other multipath mitigation techniques. The focus of this paper is signal selection by consistency checking, whereby measurements from different satellites are compared with each other to identify the NLOS and most multipath-contaminated signals. The principle of consistency checking is that multipath-contaminated and NLOS measurements produce a less consistent navigation solution than multipath-free measurements. RAIM-based fault detection operates on the same principle. Three consistency-checking schemes based on single-epoch least-squares residuals are assessed: single sweep, recursive checking and a hybrid version of the first two. Two types of weighting schemes are also considered: satellite elevation-based and signal C/N0-based weighting. The paper also discussed the different observables that may be used by a consistency-checking algorithm for different applications and their effect on detection sensitivity. Test results for the proposed algorithms are presented using data from both static positioning and stand-alone dynamic positioning experiments. The static data was collected using a pair of survey-grade multi-constellation GNSS receivers using both GPS and GLONASS signals at open sky and urban canyon locations, while the dynamic data was collected using a consumer-grade GPS/GLONASS receiver on a car in a mixed urban environment. Significant improvements in position domain are demonstrated using the weighted recursive methods in the open environments. However in the urban environments, there are insufficient directly received signals for the conventional RAIM-based signal selection to be effective all the time. Both positioning improvements and risky outliers are demonstrated. More advanced techniques have been identified for investigation in future research

Robustness Analysis of the European Air Traffic Network

The European air traffic network (ATN), consisting of a set of airports and area control cen- tres, is highly complex. The current indicator of its performance, air traffic flow management delays, is insufficient for planning and management purposes. Topological analysis of ATNs of this kind has highlighted betweenness centrality (BC) as an indicator of network robustness, although such an indicator assumes no knowledge of actual traffic flows and the network’s operational characteristics. This paper conducts topological and operational analyses of the European ATN in order to derive a more relevant and appropriate indicator of robustness. By applying a flow maximisation model to the network influenced by a range of capacity reductions at the local level, we propose a new index called the Relative Area Index (RAI). The RAI quantifies the importance of an individual node relevant to the performance of the entire network when it suffers from capacity reduction at a local scale. Air traffic data from three typical busy days in Europe are utilised to show that the RAI is more flexible and capable than BC in capturing the network impact of local capacity degradation. This index can be used to assess network robustness and provide a valuable tool for airspace managers and planners