A bibliography of the leaf-cutting ants, Atta spp. and Acromyrmex spp., up to 1975

Abstract not availabl

The use of simulation in the design of a road transport incident detection algorithm

Automatic incident detection is becoming one of the core tools of urban traffic management, enabling more rapid identification and response to traffic incidents and congestion. Existing traffic detection infrastructure within urban areas (often installed for traffic signal optimization) provides urban traffic control systems with a near continuous stream of data on the state of traffic within the network. The creation of a simulation to replicate such a data stream therefore provides a facility for the development of accurate congestion detection and warning algorithms. This paper describes firstly the augmentation of a commercial traffic model to provide an urban traffic control simulation platform and secondly the development of a new incident detection system (RAID-Remote Automatic Incident Detection), with the facility to use the simulation platform as an integral part of the design and calibration process. A brief description of a practical implementation of RAID is included along with summary evaluation results

Making training more cognitively effective: making videos interactive

The cost of health and safety (H&S) failures to the UK industry is currently estimated at up to £6.5 billion per annum, with the construction sector suffering unacceptably high levels of work-related incidents. Better H&S education across all skill levels in the industry is seen as an integral part of any solution. Traditional lecture-based courses often fail to recreate the dynamic realities of managing H&S on site and therefore do not sufficiently create deeper cognitive learning (which results in remembering and using what was learned). The use of videos is a move forward, but passively observing a video is not cognitively engaging and challenging, and therefore learning is not as effective as it can be. This paper describes the development of an interactive video in which learners take an active role. While observing the video, they are required to engage, participate, respond and be actively involved. The potential for this approach to be used in conjunction with more traditional approaches to H&S was explored using a group of 2nd-year undergraduate civil engineering students. The formative results suggested that the learning experience could be enhanced using interactive videos. Nevertheless, most of the learners believed that a blended approach would be most effective

Identifying abnormal traffic congestion on non-signalised urban roads using journey time estimation

This paper describes a technique for estimating vehicle journey times on non-signalised roads using 250-ms digital loop-occupancy data produced by single inductive loop detectors. The technique was assessed to see whether abnormal periods of traffic congestion (caused by accidents and special events) could be identified using the journey time estimates produced along a key urban corridor in the city of Southampton. The technique used a neural network approach to provide historical journey time estimates every 30-seconds based on the average loop-occupancy time per vehicle (ALOTPV) data collected from the detectors during the previous 30-second period. Results showed that using the output from 8 detectors over 1149m, journey time estimates with a mean absolute percentage deviation from the mean measured speed (MAPD) of 15% were returned. These were achieved using a neural network trained on 7 days of morning peak period data. The journey time estimates produced were presented to the control room operator in the form of a moving graph, updating every 30-seconds. Results showed that the journey time estimates identified 73% of the logged incidents on the test network during the analysis period

Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles

UK logistics fleets face increasing competitive pressures due to volatile fuel prices and the small profit margins in the industry. By reducing fuel consumption, operational costs and carbon emissions can be reduced. While there are a number of technologies that can reduce fuel consumption, it is often difficult for logistics companies to identify which would be the most beneficial to adopt over the medium and long terms. With a myriad of possible technology combinations, optimising the vehicle specification for specific duty cycles requires a robust decision-making framework. This paper combines simulated truck and delivery routes with a metaheuristic evolutionary algorithm to select the optimal combination of low-carbon technologies that minimise the greenhouse gas emissions of long-haul heavy goods vehicles during their lifetime cost. The framework presented is applicable to other vehicles, including road haulage, waste collection fleets and buses by using tailored parameters in the heuristics model

A hybrid metaheuristic for the time-dependent vehicle routing problem with hard time windows

This article paper presents a hybrid metaheuristic algorithm to solve the time-dependent vehicle routing problem with hard time windows. Time-dependent travel times are influenced by different congestion levels experienced throughout the day. Vehicle scheduling without consideration of congestion might lead to underestimation of travel times and consequently missed deliveries. The algorithm presented in this paper makes use of Large Neighbourhood Search approaches and Variable Neighbourhood Search techniques to guide the search. A first stage is specifically designed to reduce the number of vehicles required in a search space by the reduction of penalties generated by time-window violations with Large Neighbourhood Search procedures. A second stage minimises the travel distance and travel time in an ‘always feasible’search space. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%), travel distance (10.88%) and travel time (12.00%) compared to previous implementations in reasonable tim