823 research outputs found
Comparison of signalized junction control strategies using individual vehicle position data
No full textThis paper is concerned with the development of control strategies for urban signalized junction that can make use of individual vehicle position data from localization probes on board the vehicles. Strategy development involves simulating the behaviour of vehicles as they negotiate junctions controlled by prototype strategies and evaluating performance. Two strategies are discussed in this paper, a simple auctioning agent strategy and an extended auctioning agent strategy where a machine learning approach is used to enable agents to be trained by a human expert to improve performance. The performance of these two strategies are compared with each other and with the MOVA algorithm in simulated tests. The results show that auctioning agents using individual vehicle position data can out perform MOVA, but that this performance can be improved further still by using learning auctioning agents trained by a human expert
Signal control using vehicle localization probe data
No full textThis paper presents a simulation test bed and methodology for evaluating urban signalized junction control algorithms that use localization probe data from all vehicles in the local area. The simulator is based on SIAS Paramics micro-simulation software with bespoke software modules built on top for automatic network generation, localization data processing and signal control. Localization algorithms tested use a hierarchical structure of auctioning agents. Early tests of control algorithms on an isolated signalized junction indicate performance that compares favourably with the MOVA algorithm using inductive loop data.<br/
A methodology for traffic state estimation and signal control utilizing high wireless device penetration
No full textThis paper presents a methodology for fusing data from multiple sensors, including wireless devices, to make an estimation of the state of an urban traffic network. An extended Kalman filter is employed along with a state evolution model to make estimates of the state in a discretized network. Results are presented from simulation tests of signal controllers on a network with three signalized junctions. Two signal control methods are tested: SCOOT and a machine learning junction control algorithm that employs the discretized state structure described in this paper. These tests represent lower and upper performance benchmarks and present a significant difference. The tests also demonstrate a framework for the future evaluation of the proposed methodology
The genus Prorops Waterson, 1923 (Hymenoptera, Bethylidae) from Madagascar
No full textThree species of the genus Prorops Waterson, 1923 occur in Madagascar. Prorops nasuta Waterson, 1923 is recorded for the first time from Madagascar and two new species are described and illustrated: P. sparsa sp. nov. and P. impotens sp. nov., both based on the morphology of males and females. A brief discussion of the status of the genus, illustrations, and a key to Madagascan species of Prorops are provided
Comparison of signalized junction control strategies that use localization probe data
No full textThis paper presents a simulation test bed and a methodology for evaluating urban signalized junction control algorithms that use localization probe data from all vehicles in the local area. The simulator is based on SIAS Paramics microsimulation software with bespoke software modules built on top for automatic network generation, localization data processing and signal control. Also presented are results from tests carried out using the simulation test bed to evaluate localization strategies. The tested strategies use a hierarchical structure of auctioning agents. Results from tests on an isolated signalized junction indicate that the performance of the auctioning agent algorithms compare favourably with the MOVA algorithm using inductive loop data. Results are also presented for tests on a twin junction where strategies are synchronized. These show a significant improvement in performance through synchronization
Determining rail network accessibility
No full textThe usual representation of optimal path finding problems within transport networks is focused on well established algorithms for identifying the optimal path (or set of paths) between two specific network nodes. When the required solution is the identification of the optimal route between every possible pair of nodes in the network however, these algorithms are inefficient.The Floyd-Warshall algorithm provides an efficient way to compare all possible paths through each pair of nodes more efficiently, requiring only N3 comparisons for a network of N nodes. To illustrate the potential of this approach to network analysis within transport research, this paper considers the issue of determining accessibility between railway stations (on the route between Weymouth and London Waterloo) served by a mixture of high-speed and stopping services.A rail network is physically defined by the locations of tracks, but travel times are also dependent on whether stations are visited by high-speed services as well as stopping services. A single rail route therefore has to be represented not as a (topologically) straight line, but as a more traditional graph with high connectivity between nodes. Reformulating this into a matrix-based definition allows the Floyd-Warshall algorithm to efficiently determine the optimal routing (and hence travel times) between<br/
An automated signalized junction controller that learns strategies by temporal difference reinforcement learning
No full textThis paper shows how temporal difference learning can be used to build a signalized junction controller that will learn its own strategies through experience. Simulation tests detailed here show that the learned strategies can have high performance. This work builds upon previous work where a neural network based junction controller that can learn strategies from a human expert was developed. In the simulations presented, vehicles are assumed to be broadcasting their position over WiFi giving the junction controller rich information. The vehicle’s position data are pre-processed to describe a simplified state. The state-space is classified into regions associated with junction control decisions using a neural network. This classification is the strategy and is parameterized by the weights of the neural network. The weights can be learned either through supervised learning with a human trainer or reinforcement learning by temporal difference (TD).Tests on a model of an isolated T junction show an average delay of 14.12s and 14.36s respectively for the human trained and TD trained networks. Tests on a model of a pair of closely spaced junctions show 17.44s and 20.82s respectively. Both methods of training produced strategies that were approximately equivalent in their equitable treatment of vehicles, defined here as the variance over the journey time distributions
Making in-class skills training more effective: the scope for interactive videos to complement the delivery of practical pedestrian training
No full textSkills and awareness of young pedestrians can be improved with on-street practical pedestrian training, often delivered in schools in the United Kingdom by local authorities with the intention of improving road safety. This training is often supplemented by in-class paper based worksheet activities which are seen to be less effective than practical training in that they focus on knowledge acquisition rather than directly improving the correct application of safe pedestrian skills at the roadside. Previous research indicates that interactive video tools have the potential to develop procedural skills whilst offering an engaging road safety educational experience, which could positively impact on road crossing behaviour.In this paper, the design and development of a hazard-identification interactive road safety training video targeting child road crossing skills is presented. The interactive video was shown to be an engaging training resource for 6-7 year old children. The tool’s scope for improving pedestrians’ roadside skills is considered along with the wider implications for interactive video to aid safety training in other areas
A vision of the European energy future? : the impact of the German response to the Fukushima earthquake
No full textThe German response to the Fukushima nuclear power plant incident was possibly the most significant change of policy towards nuclear power outside Japan, leading to a sudden and very significant shift in the underlying power generation structure in Germany. This provides a very useful natural experiment on the impact of increasing proportions of renewable compared to conventional fuel inputs into power production, helping us to see how changed proportions in future as a result of policy moves in favour of renewables are likely to impact. We find through quasi-experimental exploration of a modified demand-supply framework that despite the swift, unpredicted change, the main impact was a significant increase in prices, partly caused by more frequent situations with unilateral market power. The price impact was also most significant in off-peak hours leading to changed investment incentives. There were no appreciable quantity effects on the market, such as power outages, contrary to some views that the impacts would be significant. Furthermore, we find the sudden and unilateral phase-out decision by the German government has significantly affected electricity prices and thus competitiveness in neighbouring countries
Simulating the impacts of strong bus priority measures
No full textPolicies to reduce levels of traffic congestion and pollution in major urban areas often focus strongly on the concept of a sustainable transport system, but to achieve this vision a significant modal shift from private car to public transport will be required. This paper reports on a recent research study which provides a framework within which to model the behavioral responses of travelers following the implementation of strong bus priority measures (where road capacity is deliberately removed from general traffic and given to buses). A summary of the different behavioral responses which can be expected is given and results from a practical implementation of the framework which has been based on two commercial transport modeling packages (CONTRAM and TRIPS) are discussed. These results suggest firstly that the effect of implementing such strong bus priority measures is as dependent on the characteristics of the local travelers as on the scheme itself and secondly that implementing too strong a scheme may not benefit public transport overall
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