Implementation of a generic concurrent engineering environment framework for boatbuilding

Boatbuilding is a growth market with global competition and tight profit margins. Concurrent engineering is not presently prevalent within the boatbuilding industry and yet this is a technique that has found much success in other industries. A methodology has, therefore, been developed to aid design in the leisure boatbuilding industry. This environment uses collaborative engineering and automated communication to aid the passing of direct communication between all members of the design team. This paper determines the characteristics of importance within boatbuilding and relates these to a framework concurrent engineering environment aimed specifically at this industry. The current work focuses on the structural and production subsystems in an attempt to improve design for production. The use of concurrent engineering tools has been highlighted with an example.     

On the allocation of city space to multiple transport modes

Abstract

This paper analyzes urban multimodal transportation systems in an aggregated way. To describe the aggregate behavior of traffic in cities, use is made of an idea that is now receiving some attention: the macroscopic fundamental diagram (MFD). We demonstrate through simulation how the MFD can be used to monitor and control a real network, in this case a portion of San Francisco, using readily available input data. We then show how different modes interact on the same network and discuss how these interactions might be incorporated into an MFD for multimodal networks. The work unveils two main results: first, it confirms recent results showing that restricting access to a city's congested areas can improve mobility for all travelers, including those who endure the restrictions; and second, that dedicating street space to collective transport modes can improve accessibility for all modes, even those from which space is taken away.     

Updating predictive accident models of modern rural single carriageway A-roads

Abstract

Reliable predictive accident models (PAMs) are essential to design and maintain safe road networks, and yet the models most commonly used in the UK were derived using data collected 20 to 30 years ago. Given that the national personal injury accident total fell by some 30% in the last 25 years, while road traffic increased by over 60%, significant errors in scheme appraisal and evaluation based on the models currently in use seem inevitable. In this paper, the temporal transferability of PAMs for modern rural single carriageway A-roads is investigated, and their predictive performance is evaluated against a recent data set. Despite the age of these models, the PAMs for predicting the total accidents provide a remarkably good fit to recent data and these are more accurate than models where accidents are disaggregated by type. The performance of the models can be improved by calibrating them against recent data.     

Techniques for the inference of mileage rates from MOT data

Abstract

Mathematical and computational techniques are developed for the processing and analysis of annual Ministry of Transport roadworthiness (MOT) test data that the UK Department for Transport has placed in the public domain. First, techniques are given that clean erroneous records and a linking procedure is provided that permits the inference of an individual vehicle's mileage between consecutive tests. Methods are then developed that analyse aggregate mileage totals, as a function of vehicle age, class and geography. The inference of aggregate mileage rates as a function of time is then considered.     

Applications of intuitionistic fuzzy set aggregation operators in transport multi-factor project evaluation

Abstract

An intuitionistic fuzzy set (IFS) is a generalisation of a fuzzy set characterised by a truth membership function and a false membership function. The former is a lower bound on the grade of membership of the evidence in favour of a particular element belonging to the set and the latter is a lower bound on the negation of that element belonging to the set derived from evidence against that element belonging to the set. A similar concept is a vague set, though vague sets have been shown to be identical to IFSs. In the context of project evaluation, an IFS may be used to represent the degree to which a project satisfies a criterion and the degree to which it does not. Aggregation of such IFSs has been considered in recent years to identify a best project in terms of several criteria or factors. A particular desirable way to aggregate IFS is in terms of an ordered weighted average (OWA) which can be expressed in different forms such as arithmetic and geometric. In an OWA operator, weights are applied to the position of an element in the aggregation. In addition, hybrid OWA operators may be developed to not only weight the position of elements in the aggregation but the element itself. An example is given relating to the Kuranda Range Road upgrade (Queensland, Australia) which is limited by grade, poor overtaking opportunities, poor horizontal alignment and other constraints and the road is expected to become increasingly congested over the next few years. A more flexible multi-factor decision method is used to identify a ‘best’ project from a set of four alternative projects.     

Estimation of a route choice model for urban public transport using smart card data

This paper describes a logit model of route choice for urban public transport and explains how the archived data from a smart card-based fare payment system can be used for the choice set generation and model estimation. It demonstrates the feasibility and simplicity of applying a trip-chaining method to infer passenger journeys from smart card transactions data. Not only origins and destinations of passenger journeys can be inferred but also the interchanges between the segments of a linked journey can be recognised. The attributes of the corresponding routes, such as in-vehicle travel time, transfer walking time and to get from alighting stop to trip destination, the need to change, and the time headway of the first transportation line, can be determined by the combination of smart card data with other data sources, such as a street map and timetable. The smart card data represent a large volume of revealed preference data that allows travellers' behaviour to be modelled with higher accuracy than by using traditional survey data. A multinomial route choice model is proposed and estimated by the maximum likelihood method, using urban public transport in ?ilina, the Slovak Republic, as a case study     

Use and Effects of Advanced Traveller Information Services (ATIS): A Review of the Literature

Abstract

Rapid technological developments in the field of personal communication services probe visions of a next generation in Advanced Traveller Information Services (ATIS). These technological developments provoke a renewed interest in the use and effect of such next‐generation ATIS among academia as well as practitioners. To understand better the potential use and effects of such next‐generation ATIS, a thorough review is warranted of contemporary conceptual ideas and empirical findings on the use of travel information (services) and their effects on travellers’ choices. This paper presents such a review and integrates behavioural determinants such as the role of decision strategies with manifest determinants such as trip contexts and socio‐economic variables into a coherent framework of information acquisition and its effect on travellers’ perceptions.     

Development of a biology inspired manufacturing system for machining transmission cases

Disruptions in automated manufacturing systems for machining automotive parts caused by system changes and disturbances reduce the productivity, and increase the downtime as well as the cost of products. To cope with these challenges, the paper presents a biology inspired manufacturing system (Bio-MS). The model of Bio-MS is inherited from the organization of the living systems in biology and nature such as ant colony, school of fish, bee’s foraging behaviors, and so on. In which, the resources of the manufacturing system are considered as biological organisms, which are autonomous entities so that the manufacturing system has the advanced characteristics inspired from biology such as self-adaptation, self-diagnosis, and self-healing. To realize the Bio-MS, the cognitive agent and swarm intelligence were proposed. The disturbances happening when machining the transmission cases at an automotive company in Korea were analyzed to classify them and to find out the corresponding management methods. Currently, the system utilization was too low due to the manual recovery, only 70–76 percent of total production time is used for manufacturing and the rest of the time is wasted in different disturbances. The Bio-MS with autonomous behaviors adapts efficiently to the changes of the manufacturing environment. It enables to increase the system utilization more than 80 percent.     

Dynamic sensor zeroing algorithm of 6D IMU mounted on ground vehicles

The main focus of this paper is to compensate the steady state offset error of the 6D IMU which provides the measurements that include the vehicle linear accelerations and angular rates of all three axes. Additionally, the sensor compensation algorithm exploits the wheel speed data and the steering angle information, since they are already available in most of the modern mass production vehicles. These inputs are combined with the inverse vehicle kinematics to estimate the steady state offset error of each sensor inputs as it is done in a disturbance observer, and the raw sensor measurements are compensated by the estimated offset errors. The stability of the error dynamics regarding the integrated signal processing system is verified, and finally, the performance of the system is tested via experiments based on a real production SUV.