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

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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

Waste-to-fuel opportunities for British quick service restaurants: A case study

The fast food supply chain is facing increasing operating costs due to volatile food and energy prices. Based on a case study of a major fast food logistics operator, this paper quantifies the potential for fuel generation from the waste generated by quick-service restaurants in Britain. Several fuel pathways and supply chains were mapped to understand the carbon intensity of the various waste-to-fuel opportunities, the number of heavy goods vehicles that might be powered and the key factors that could help companies make better informed decisions related to fuel generation from waste. The research suggested that depending on the scenarios considered, between 13.9 and 17.2 million GJ of energy could be obtained from fuels made from the waste arisings of British quick service restaurants and their distribution centres (DCs), representing between 4.4 and 5.8% of the national energy consumption from heavy goods vehicles (HGVs) and well-to-wheel (WTW) greenhouse gases (GHG) savings of between 652 and 898 thousand tonnes of CO2 equivalent annually. Used cooking oil and burger fat arising from British quick-service restaurants could generate enough energy to power up to 3891 HGVs with FAME diesel (B100), 1622 with HVO diesel (B100) or 1943 with biomethane annually. The paper and card generated by these same establishments could also power an additional 4623 biomethane vehicles, wood pallets could power an additional 73 bioethanol trucks and plastics could also power 341 vehicles running with synthetic diesel. The results showed that collections of separate waste fractions by logistics operators could make a relevant contribution towards the decarbonisation of the supply chain while reducing disposal fees and fuel costs. The carbon emissions resulting from this approach depend greatly on the footprint of the collection and transportation systems used to move waste from the restaurants to the processing plants and return the converted fuel back to the distribution centres where the vehicles are refuelled. Logistics firms are in a privileged position to manage these flows as they can use empty back-haul trips to collect and consolidate waste in distribution centres