DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM
In this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots) with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordi...
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doaj-0558a3df8ad0469cb238d91aba06b1962020-11-25T00:59:40ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502015-07-01II-4/W210310910.5194/isprsannals-II-4-W2-103-2015DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHMH. Chen0T. Cheng1S. Wise2SpaceTimeLab, Department of Civil, Environmental & Geomatic Engineering, University College London, London WC1E 6BT, UKSpaceTimeLab, Department of Civil, Environmental & Geomatic Engineering, University College London, London WC1E 6BT, UKSpaceTimeLab, Department of Civil, Environmental & Geomatic Engineering, University College London, London WC1E 6BT, UKIn this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots) with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability in patrol routes. Previous studies have designed different police patrol strategies for routing police patrol, but these strategies have difficulty in generalising to real patrolling and meeting various requirements. In this research we develop a new police patrolling strategy based on Bayesian method and ant colony algorithm. In this strategy, virtual marker (pheromone) is laid to mark the visiting history of each crime hotspot, and patrollers continuously decide which hotspot to patrol next based on pheromone level and other variables. Simulation results using real data testifies the effective, scalable, unpredictable and extensible nature of this strategy.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-4-W2/103/2015/isprsannals-II-4-W2-103-2015.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
H. Chen T. Cheng S. Wise |
spellingShingle |
H. Chen T. Cheng S. Wise DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
H. Chen T. Cheng S. Wise |
author_sort |
H. Chen |
title |
DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM |
title_short |
DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM |
title_full |
DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM |
title_fullStr |
DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM |
title_full_unstemmed |
DESIGNING DAILY PATROL ROUTES FOR POLICING BASED ON ANT COLONY ALGORITHM |
title_sort |
designing daily patrol routes for policing based on ant colony algorithm |
publisher |
Copernicus Publications |
series |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
2194-9042 2194-9050 |
publishDate |
2015-07-01 |
description |
In this paper, we address the problem of planning police patrol routes to regularly cover street segments of high crime density (hotspots) with limited police forces. A good patrolling strategy is required to minimise the average time lag between two consecutive visits to hotspots, as well as coordinating multiple patrollers and imparting unpredictability in patrol routes. Previous studies have designed different police patrol strategies for routing police patrol, but these strategies have difficulty in generalising to real patrolling and meeting various requirements. In this research we develop a new police patrolling strategy based on Bayesian method and ant colony algorithm. In this strategy, virtual marker (pheromone) is laid to mark the visiting history of each crime hotspot, and patrollers continuously decide which hotspot to patrol next based on pheromone level and other variables. Simulation results using real data testifies the effective, scalable, unpredictable and extensible nature of this strategy. |
url |
http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-4-W2/103/2015/isprsannals-II-4-W2-103-2015.pdf |
work_keys_str_mv |
AT hchen designingdailypatrolroutesforpolicingbasedonantcolonyalgorithm AT tcheng designingdailypatrolroutesforpolicingbasedonantcolonyalgorithm AT swise designingdailypatrolroutesforpolicingbasedonantcolonyalgorithm |
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