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In 2008, heavy trucks were found to be 3.2 times more likely than other vehicles to be struck from behind in twovehicle fatal crashes. The U.S. Federal Motor Carrier Safety Administration awarded a contract to the Virginia Tech Transportation Institute to perform Phase III of the Enhanced Rear Signalling for Heavy Trucks project which was directed at investigating methods to reduce or mitigate those...
Despite the widely acknowledged potential of intelligent transport systems and services (ITS), the deployment of ITS has generally been scattered and slow. One of the main reasons for this is that people deciding on investments in the road and public transport sector often lack knowledge of the feasibility, cost-effectiveness, impacts and user acceptance of ITS solutions to their own transport related...
This study gives an overview on applications of speed optimisation as one control measure for intelligent traffic management in rail-bound public transportation systems. The concept of operational target points and target windows is introduced. Speed and dwell time control are used to reach these targets, thereby improve throughput through system-related bottlenecks and reduce energy consumption....
Statistical traffic data analysis is a hot topic in traffic management and control. In this field, current research progresses focus on analysing traffic flows of individual links or local regions in a transportation network. Less attention are paid to the global view of traffic states over the entire network, which is important for modelling large-scale traffic scenes. Our aim is precisely to propose...
Constrained cognitive abilities cause imperfections in drivers' choice behaviour and appear largely systematic and predictable. This study introduces the concept of 'effective control space' to build upon this knowledge as an opportunity to increase the effectiveness of Dynamic Traffic Management (DTM). Within the control space boundaries it is assumed that drivers do not act upon the effects of DTM...
Reactive multi-agent systems are increasingly applied to problem solving, modelling and simulation. Among the benefits of this approach, there is the capability to solve complex problems, whereas maintaining functional and conceptual simplicity of involved entities. Many examples have shown that approaches based on multi-agent systems are effective in solving complex problems such as life simulation...
Service station experts examine the sound patterns of the motorcycles to diagnose the faults. Automatic fault diagnosis is a challenging task and more so is recognition of multiple faults. This study presents a methodology for localisation of multiple faults in motorcycles. The sound signatures of multiple faults are constructed by fusing the individual signatures of faults from engine and exhaust...
This study presents a method that combines travel-time estimation and adaptive traffic signal control. The proposed method explores the concept of vehicle-to-infrastructure communication, through which real-time vehicle localisation data become available to traffic controllers. This provides opportunity to frequently sample vehicle location and speed for online travel-time estimation. The control...
This study develops a more accurate range prediction for electric vehicles (EVs) resulting in a routing system that could extend the driving range of EVs through calculating the minimum energy route to a destination, based on topography and traffic conditions of the road network. Energy expenditure of EVs under different conditions is derived using high-resolution real-world data from the SwitchEV...
From the 1980s, new telematic technologies have meant a great evolution in several areas. In the transportation domain, their use has implied the development and implementation of several intelligent transport systems (ITS). However, these deployments were done in an isolated way. Traffic managers, public and private organisations, stakeholders and others have implemented ITS without much perspective,...
Chaotic non-linear dynamics approach is now the most powerful tool for scientists to deal with complexities in real cases; and artificial neural networks and neuro-fuzzy models are widely used for their capabilities in non-linear modelling of chaotic systems. Chaos, uncertain behaviours, demanding fluctuation, complexity of the traffic flow situations and the problems with those methods, however,...
This study considers deployment paths for automated vehicles, evaluating the new approach of an evolutionary process of isolated deployment. Here, isolated, fully automated systems are developed from the ground-up in areas with the greatest need/ opportunity; over time, such systems can expand and become interconnected. This is an alternative to the integrated deployment strategies developed by the...
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