scholarly journals An Adaptive Route Planning Method of Connected Vehicles for Improving the Transport Efficiency

2022 ◽  
Vol 11 (1) ◽  
pp. 39
Author(s):  
Baoju Liu ◽  
Jun Long ◽  
Min Deng ◽  
Xuexi Yang ◽  
Yan Shi
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Route Planning ◽  
Planning Method ◽  
Planning Problem ◽  
Transport Efficiency ◽  
Bidding Price ◽  
Bidding Mechanism ◽  
Dynamic Route ◽  
Bidding Process

In recent years, the route-planning problem has gained increased interest due to the development of intelligent transportation systems (ITSs) and increasing traffic congestion especially in urban areas. An independent route-planning strategy for each in-vehicle terminal improves its individual travel efficiency. However, individual optimal routes pursue the maximization of individual benefit and may contradict the global benefit, thereby reducing the overall transport efficiency of the road network. To improve traffic efficiency while considering the travel time of individual vehicles, we propose a new dynamic route-planning method by innovatively introducing a bidding mechanism in the connected vehicle scenario for the first time. First, a novel bidding-based dynamic route planning is proposed to formulate vehicle routing schemes for vehicles affected by congestion via the bidding process. Correspondingly, a bidding price incorporating individual and global travel times was designed to balance the travel benefits of both objectives. Then, in the bidding process, a new local search algorithm was designed to select the winning routing scheme set with the minimum bidding price. Finally, the proposed method was tested and validated through case studies of simulated and actual driving scenarios to demonstrate that the bidding mechanism would be conducive to improving the transport efficiency of road networks in large-scale traffic flow scenarios. This study positively contributes to the research and development of traffic management in ITSs.

Heuristic-Based Dynamic Route Planning Method for a Homogeneous Multi-robot Team

2009 ◽  
Vol 23 (3) ◽  
pp. 269-287 ◽  
Author(s):  
Ahmet Yazici ◽  
Aydin Sipahioglu ◽  
Osman Parlaktuna
Keyword(s):  
Route Planning ◽  
Planning Method ◽  
Dynamic Route ◽  
Multi Robot

scholarly journals Trialing Innovative Technologies in Crisis Management—“Airborne and Terrestrial Situational Awareness” as Support Tool in Flood Response

2020 ◽  
Vol 10 (11) ◽  
pp. 3743 ◽  
Author(s):  
Elisa Schröter ◽  
Ralph Kiefl ◽  
Eric Neidhardt ◽  
Gaby Gurczik ◽  
Carsten Dalaff ◽  
...  
Keyword(s):  
Crisis Management ◽  
Urban Areas ◽  
Large Scale ◽  
New Technologies ◽  
Situational Awareness ◽  
Route Planning ◽  
Added Value ◽  
Aerial Image ◽  
Specific Response ◽  
Test Bed

Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but also to test and evaluate its benefit in a realistic environment before the disaster strikes. To bridge the gap between theoretic potential and actual integration into practice, the EU-funded project DRIVER+ has designed a methodical and technical environment to assess innovation in a realistic but non-operational setup through trials. The German Aerospace Center (DLR) interdisciplinary merged mature technical developments into the “Airborne and terrestrial situational awareness” system and applied it in a DRIVER+ Trial to promote a sustainable and demand-oriented R&D. Experienced practitioners assessed the added value of its modules “KeepOperational” and “ZKI” in the context of large-scale flooding in urban areas. The solution aimed at providing contextual route planning in police operations and extending situational awareness based on information derived through aerial image processing. The user feedback and systematically collected data through the DRIVER + Test-bed approved that DLR’s system could improve transport planning and situational awareness across organizations. However, the results show a special need to consider, for example, cross-domain data-fusion techniques to provide essential 3D geo-information to effectively support specific response tasks during flooding.

scholarly journals OBJECTS GROUPING FOR SEGMENTATION OF ROADS NETWORK IN HIGH RESOLUTION IMAGES OF URBAN AREAS

2016 ◽  
Vol XLI-B7 ◽  
pp. 897-902 ◽  
Author(s):  
M. Maboudi ◽  
J. Amini ◽  
M. Hahn
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Urban Areas ◽  
Traffic Management ◽  
Large Scale ◽  
Route Planning ◽  
Technological Advancement ◽  
Image Objects ◽  
High Resolution Images ◽  
Road Segments

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors – as the main source of large scale mapping applications – was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of “Object-based Image Analysis (OBIA)” as an alternative to pixel-based image analysis methods. <br><br> Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

scholarly journals OBJECTS GROUPING FOR SEGMENTATION OF ROADS NETWORK IN HIGH RESOLUTION IMAGES OF URBAN AREAS

2016 ◽  
Vol XLI-B7 ◽  
pp. 897-902 ◽  
Author(s):  
M. Maboudi ◽  
J. Amini ◽  
M. Hahn
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Urban Areas ◽  
Traffic Management ◽  
Large Scale ◽  
Route Planning ◽  
Technological Advancement ◽  
Image Objects ◽  
High Resolution Images ◽  
Road Segments

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors – as the main source of large scale mapping applications – was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of “Object-based Image Analysis (OBIA)” as an alternative to pixel-based image analysis methods. <br><br> Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

Route Planning of Geomagnetic Aided Navigation for Vehicle under Matching Suitability Constraints

2013 ◽  
Vol 454 ◽  
pp. 39-42
Author(s):  
Peng Wang ◽  
Xiao Ping Hu ◽  
Mei Ping Wu ◽  
Hua Mu ◽  
Hai Ping Yuan
Keyword(s):  
Particle Swarm Optimization ◽  
Fitness Function ◽  
Particle Swarm ◽  
Route Planning ◽  
Pso Algorithm ◽  
Planning Method ◽  
Experimental Results ◽  
Planning Problem ◽  
Swarm Optimization ◽  
Movement Distance

In geomagnetic aided navigation (GAN), the vehicle is expected to traverse the areas with excellent matching suitability in order to obtain high matching precision. The route planning problem under matching suitability constraints is studied based on particle swarm optimization (PSO) algorithm in this article. Firstly, the PSO algorithm is briefly introduced and the expanding space of route nodes is determined with the maneuverability constraints of the vehicle. Then the minimum movement distance, the ability of avoiding threats and the proximity to suitable-matching areas are considered to construct the fitness function of PSO algorithm. Further the route planning method under matching suitability constraints is proposed. Experimental results show that the proposed method is effective, and the vehicle can successfully avoid the threats and can traverse the suitable-matching areas.

scholarly journals Dynamic Route Network Planning Problem for Emergency Evacuation in Restricted-Space Scenarios

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yi Hong ◽  
Deying Li ◽  
Qiang Wu ◽  
Hua Xu
Keyword(s):  
Graph Transformation ◽  
Network Planning ◽  
Classical Problem ◽  
Route Planning ◽  
Emergency Evacuation ◽  
Set Cover ◽  
Planning Problem ◽  
Geographic Space ◽  
Route Network ◽  
Dynamic Route

We investigate a dynamic route planning problem in restricted-space evacuation, namely, the Multiobjective Dynamic Route Network Planning (MODRNP) problem. It models the multisource to multidestination evacuation in restricted-space scenarios, with the objectives of minimizing the whole evacuation delay and maximizing the evacuation efficiency. We study the problem in 3D scenarios, which can provide intuition vision for the geographic space and contribute to the evacuation plan and implementation. Based on the auxiliary graph transformation, we propose a heuristic algorithm referred to the classical problem, Minimum Weighted Set Cover. We finally conduct extensive experiments to evaluate the performance of the proposed algorithm and give an application instance on a typical kind of restricted-space scenarios. The results indicate that the proposed algorithm outperforms the existing alternatives in terms of the utilization as well as timeliness.

Engineering in the time of cholera: overcoming institutional and political challenges to rebuild Zimbabwe's water and sanitation infrastructure in the aftermath of the 2008 cholera epidemic

2013 ◽  
Vol 3 (2) ◽  
pp. 222-229 ◽  
Author(s):  
Clarissa Brocklehurst ◽  
Murtaza Malik ◽  
Kiwe Sebunya ◽  
Peter Salama
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Humanitarian Aid ◽  
Urban Systems ◽  
Political Crisis ◽  
Rapid Improvement ◽  
Cholera Epidemic ◽  
Rapid Action ◽  
Water And Sanitation Infrastructure ◽  
Urban Rehabilitation

A devastating cholera epidemic swept Zimbabwe in 2008, causing over 90,000 cases, and leaving more than 4,000 dead. The epidemic raged predominantly in urban areas, and the cause could be traced to the slow deterioration of Zimbabwe's water and sewerage utilities during the economic and political crisis that had gripped the country since the late 1990s. Rapid improvement was needed if the country was to avoid another cholera outbreak. In this context, donors, development agencies and government departments joined forces to work in a unique partnership, and to implement a programme of swift improvements that went beyond emergency humanitarian aid but did not require the time or massive investment associated with full-scale urban rehabilitation. The interventions ranged from supply of water treatment chemicals and sewer rods to advocacy and policy advice. The authors analyse the factors that made the programme effective and the challenges that partners faced. The case of Zimbabwe offers valuable lessons for other countries transitioning from emergency to development, and particularly those that need to take rapid action to upgrade failing urban systems. It illustrates that there is a ‘middle path’ between short-term humanitarian aid delivered in urban areas and large-scale urban rehabilitation, which can provide timely and highly effective results.

scholarly journals Modeling Spatiotemporal Population Changes by Integrating DMSP-OLS and NPP-VIIRS Nighttime Light Data in Chongqing, China

2021 ◽  
Vol 13 (2) ◽  
pp. 284
Author(s):  
Dan Lu ◽  
Yahui Wang ◽  
Qingyuan Yang ◽  
Kangchuan Su ◽  
Haozhe Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Relative Error ◽  
Urban Areas ◽  
Large Scale ◽  
Population Distribution ◽  
Spatial Optimization ◽  
Distribution Data ◽  
Mountainous Areas ◽  
Mean Relative Error ◽  
Nighttime Light

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing’s population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased.

Route planning of intelligent bridge cranes based on an improved artificial potential field method

2021 ◽  
pp. 1-8
Author(s):  
Zhengyan Chang ◽  
Zhengwei Zhang ◽  
Qiang Deng ◽  
Zheren Li
Keyword(s):  
Potential Field ◽  
Autonomous Navigation ◽  
Route Planning ◽  
Simple Algorithm ◽  
Field Method ◽  
Artificial Potential Field ◽  
Planning Problem ◽  
Operating Characteristics ◽  
Potential Field Method ◽  
Artificial Potential Field Method

The artificial potential field method is usually applied to the path planning problem of driverless cars or mobile robots. For example, it has been applied for the obstacle avoidance problem of intelligent cars and the autonomous navigation system of storage robots. However, there have been few studies on its application to intelligent bridge cranes. The artificial potential field method has the advantages of being a simple algorithm with short operation times. However, it is also prone to problems of unreachable targets and local minima. Based on the analysis of the operating characteristics of bridge cranes, a two-dimensional intelligent running environment model of a bridge crane was constructed in MATLAB. According to the basic theory of the artificial potential field method, the double-layer artificial potential field method was deduced, and the path and track fuzzy processing method was proposed. These two methods were implemented in MATLAB simulations. The results showed that the improved artificial potential field method could avoid static obstacles efficiently.

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