GIS-based dynamic traffic congestion modeling to support time-critical logistics

Miller, Harvey J.; Wu, Yi-Hwa; Hung, Ming-Chih

doi:10.1109/hicss.1999.772611

Cited by 13 publications

(7 citation statements)

References 11 publications

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“…GIS is a collection of computer hardware, software, and geographic data for capturing, managing, analyzing, and displaying all forms of geographically referenced information (Sarkar, 2007). Researchers applied GIS in conjunction with operational research techniques to solve problems such as vehicle routing (Campbell et al, 2001), time-critical logistics (Miller, et al, 1999), site location (Li et al, 2005) and warehouse management (Johnston et al, 1999). Researchers also adopted GIS to solve problems encountered in the construction process, e.g.…”

Section: Smart Logistics Planning Technologies For Mic: Gis Bim and Vrpmentioning

confidence: 99%

Logistics Planning and Visualization of Modular Integrated Construction Projects Based on BIM-GIS Integration and Vehicle Routing Algorithm

Niu

Yang

Pan

2019

mocs

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Logistics planning is a critical part of developing supply chain for modular integrated construction (MiC) projects in Hong Kong where high-rise, high density and hilly landscape is the norm. It is important to minimize the total logistics and to guarantee timely delivery of modules, especially for several MiC projects being constructed during the same period. Nevertheless, there is a significant lack of studies on logistics planning, optimization and visualization for MiC projects. The aim of this paper is to establish an integrated MiC logistics planning and visualization platform, which is grounded on the integration of building information modeling (BIM), geographical information system (GIS) and vehicle routing problem (VRP) algorithm. The framework is then presented and evaluated using a case study to identify optimal logistics scenario of trailer routes to meet the installation time window of MiC projects in Hong Kong. The paper finds that the proposed platform has the ability to make optimized logistics scenario for MiC projects, and to visualize the logistics scenario in a 3-dimentional interactive environment. Future study will focus on adopting flexible control strategies and including more decision-making criteria of logistics planning in MiC projects such as road width limitation, travel speed and different module types

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Section: Smart Logistics Planning Technologies For Mic: Gis Bim and Vrpmentioning

confidence: 99%

Logistics Planning and Visualization of Modular Integrated Construction Projects Based on BIM-GIS Integration and Vehicle Routing Algorithm

Niu

Yang

Pan

2019

mocs

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“…Mobility in urban environments has specific properties that are different from minor cities and rural areas (Miller, Wu, and Hung 1999). There are different modes of transport, private and public, that cause various different movement patterns of many individual traffic participants.…”

Section: Mobility Analyses In Urban Environmentsmentioning

confidence: 99%

Extracting commuter-specific destination hotspots from trip destination data – comparing the boro taxi service with Citi Bike in NYC

Keler

Krisp

Ding

2019

Geo-spatial Information Science

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Taxi trajectories from urban environments allow inferring various information about the transport service qualities and commuter dynamics. It is possible to associate starting and end points of taxi trips with requirements of individual groups of people and even social inequalities. Previous research shows that due to service restrictions, boro taxis have typical customer destination locations on selected Saturdays: many drop-off clusters appear near the restricted zone, where it is not allowed to pick up customers and only few drop-off clusters appear at complicated crossing. Detected crossings imply recent infrastructural modifications. We want to follow up on these results and add one additional group of commuters: Citi Bike users. For selected Saturdays in June 2015, we want to compare the destinations of boro taxi and Citi Bike users. This is challenging due to manifold differences between active mobility and motorized road users, and, due to the fact that station-based bike sharing services are restricted to stations. Start and end points of trips, as well as the volumes in between rely on specific numbers of bike sharing stations. Therefore, we introduce a novel spatiotemporal assigning procedure for areas of influence around static bike sharing stations for extending available computational methods.

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“…Researchers have reported on the development of a GIS-based decision support system (DSS) for dynamic modelling of congestion and routing in a TCL scenario. The system predicts network flows at detailed time-based resolutions while determining the departure time and shortest path required for a shipment to reach its destination in a given time frame [10]. Effective decision support is provided by the GIS through its database management capabilities, graphical user interfaces (GUI), and cartographic visualisation [6].…”

Section: Figure 1: Gis Set-up All-street Network (Source: Adapted Fromentioning

confidence: 99%

A Virtual Store Framework Model: Optimising Travel Route for a Passenger Rail Operation of Maintenance Components Using Gis

Fourie¹,

Chimusoro²,

Asekun³

2018

SAJIE

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Previous studies of supply chain management systems have attempted to focus on transportation, logistics, storage space planning, and time-to-delivery. The biggest challenge for large organisations like the Passenger Rail Agency of South Africa, which has a presence throughout South Africa, is trying to manage all stores efficiently and effectively. This article looks at these challenges, and provides a virtual store framework model to understand the scope and magnitude of an integrated logistics model approach. Geographical information systems were applied to the virtual store to determine an efficient route for transporting components between stores. Furthermore, the authors identified the major aspects and impacts of a virtual store system in a rail passenger transport operation. This was done through on-site studies and a review of the literature on virtual stores. The model was tested on a case study that produced results that include time and cost as the variables for decision-making. OPSOMMINGVorige studies in voorsieningskettingbestuur het meestal probeer fokus op vervoer, logistiek, stoorspasie beplanning, en afleweringstyd. Een van die grootste uitdagings in 'n groot organisasie soos PRASA, wat regoor Suid-Afrika strek, is om alle store doeltreffend en effektief te bestuur. Hierdie artikel ondersoek hierdie uitdagings, en stel 'n virtuele stoor raamwerk model voor om die omvang en grootte van so 'n geïntegreerde model benadering te verstaan. Verder het die outeurs belangrike aspekte en impakte van 'n virtuele stoorstelsel in 'n spoorweg passasiersvervoer organisasie geïdentifiseer. Hierdie is gedoen deur gebruik te maak van studies op die perseel en 'n literatuur oorsig van virtuele store. Toetsing van die model het tyd en koste as veranderlikes in die besluitnemingsproses ingesluit.

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GIS-based dynamic traffic congestion modeling to support time-critical logistics

Cited by 13 publications

References 11 publications

Logistics Planning and Visualization of Modular Integrated Construction Projects Based on BIM-GIS Integration and Vehicle Routing Algorithm

Logistics Planning and Visualization of Modular Integrated Construction Projects Based on BIM-GIS Integration and Vehicle Routing Algorithm

Extracting commuter-specific destination hotspots from trip destination data – comparing the boro taxi service with Citi Bike in NYC

A Virtual Store Framework Model: Optimising Travel Route for a Passenger Rail Operation of Maintenance Components Using Gis

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