An Innovative Routing Technique to Optimize Time and Speed

AbstractIn this paper we introduce a novel algorithm, MAXSMINT (Maximizing Speed and Minimizing Time) for determining the shortest route in a railway network. In today's busy world, no one takes the effort to determine the shortest route to the destination but expect to reach their destinations in the shortest possible time. Thus, this system involves providing the shortest time taking path to their destination automatically. Optimization is achieved by splitting the entire process into two. First finding the shortest paths to the end station and then calculating and zero down to the final shortest time taking path. This approach is more generalized and is proved to offer higher efficiency and shorter process time then the conventional methodologies

A Two-layered Fast Marching Path Planning Algorithm for an Unmanned Surface Vehicle Operating in a Dynamic Environment

This paper describes a modified fast marching (FM) path planning algorithm for unmanned surface vehicles (USVs). The modified FM algorithm generates a two-layered synthetic vector field to represent a dynamic environment. The synthetic vector field integrates the obstacle information and the environment information, where current and wind velocities vary in both magnitude and direction. The path planning algorithm then employs the anisotropic FM method to calculate a safe trajectory to avoid obstacles and to minimise any negative effects of the environment. The algorithm has been tested in the environment with simulated current. The resulting trajectory shows that the two-layered FM algorithm is able to deal with environmental influence satisfactory

Vehicle-based interactive management with multi-agent approach

Under the energy crisis and global warming, mass transportation becomes more important than before. The disadvantages of mass transportation, plus the high flexibility and efficiency of taxi and with the revolution of technology, electric-taxi is the better transportation choice for metropolis. On the other hand, among the many taxi service types, dial-a-ride (DAR) service system is the better way for passenger and taxi. However the electricity replenishing of electric-taxi is the biggest shortage and constraint for DAR operation system. In order to more effectively manage the electric-taxi DAR operation system and the lots of disadvantages of physical system and observe the behaviors and interactions of simulation system, multi-agent simulation technique is the most suitable simulation technique. Finally, we use virtual data as the input of simulation system and analyze the simulation result. We successfully obtain two performance measures: average waiting time and service rate. Result shows the average waiting time is only 3.93 seconds and the service rate (total transport passenger number / total passenger number) is 37.073%. So these two performance measures can support us to make management decisions. The multiagent oriented model put forward in this article is the subject of an application intended in the long term to supervise the user information system of an urban transport network.Peer Reviewe

Optimal ship navigation and algorithms for stochactic obstacle scenes

Tezin basılısı İstanbul Şehir Üniversitesi Kütüphanesi'ndedir.This thesis is comprised of two different but related sections. In the first section, we consider the optimal ship navigation problem wherein the goal is to find the shortest path between two given coordinates in the presence of obstacles subject to safety distance and turn-radius constraints. These obstacles can be debris, rock formations, small islands, ice blocks, other ships, or even an entire coastline. We present a graph-theoretic solution on an appropriately-weighted directed graph representation of the navigation area obtained via 8-adjacency integer lattice discretization and utilization of the A∗ algorithm. We explicitly account for the following three conditions as part of the turn-radius constraints: (1) the ship’s left and right turn radii are different, (2) ship’s speed reduces while turning, and (3) the ship needs to navigate a certain minimum number of lattice edges along a straight line before making any turns. The last constraint ensures that the navigation area can be discretized at any desired resolution. We illustrate our methodology on an ice navigation example involving a 100,000 DWT merchant ship and present a proof- of-concept by simulating the ship’s path in a full-mission ship handling simulator at Istanbul Technical University. In the second section, we consider the stochastic obstacle scene problem wherein an agent needs to traverse a spatial arrangement of possible-obstacles, and the status of the obstacles may be disambiguated en route at a cost. The goal is to find an algorithm that decides what and where to disambiguate en route so that the expected length of the traversal is minimized. We present a polynomial-time method for a graph-theoretical version of the problem when the associated graph is restricted to parallel avenues with fixed policies within the avenues. We show how previously proposed algorithms for the continuous space version can be adapted to a discrete setting. We propose a gener- alized framework encompassing these algorithms that uses penalty functions to guide the navigation in realtime. Within this framework, we introduce a new algorithm that provides near-optimal results within very short execution times. Our algorithms are illustrated via computational experiments involving synthetic data as well as an actual naval minefield data set. Keywords: Graph theory, shortest path, ship navigation, probabilistic path planning, stochastic dynamic programming, Markov decision process, Canadian traveler’s problemContents Declaration of Authorship ii Abstract iv ¨ Oz v Acknowledgments vii List of Figures x List of Tables xi 1 Optimal Ship Navigation with Safety Distance and Realistic Turn Con- straints 1 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Previous Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 The Optimal Ship Navigation Problem . . . . . . . . . . . . . . . . . . . . 4 1.4 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4.1 Safety Distance Constraints . . . . . . . . . . . . . . . . . . . . . . 5 1.4.2 Lattice Discretization . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.4.3 Ship-Turn Constraints . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4.4 The A∗ Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.4.5 Smoothing the Optimal Path . . . . . . . . . . . . . . . . . . . . . 13 1.5 Ice Navigation Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 1.6 Simulator Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 1.7 Summary, Conclusions, and Future Research . . . . . . . . . . . . . . . . 18 2 Algorithms for Stochastic Obstacle Scenes 21 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.2 The Stochastic Obstacle Scene Problem: Continuous vs. Discrete Settings 23 2.2.1 Deciding Where to Disambiguate: Single Disk Case . . . . . . . . 23 2.2.2 Deciding Where to Disambiguate: Two Disks Case . . . . . . . . . 25 2.2.3 Discretization of the Continuous Setting: An Example . . . . . . . 27 2.3 Definition of the Stochastic Obstacle Scene Problem . . . . . . . . . . . . 27 2.3.1 Continuous SOSP . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.3.2 Discrete SOSP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.3.3 Discretized SOSP . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.4 A Polynomial Algorithm for Discrete SOSP on Parallel Graphs . . . . . . 29 2.5 Discrete Adaptation of the Simulated Risk Disambiguation Algorithm . . 30 2.5.1 Adaptation to Discrete SOSP . . . . . . . . . . . . . . . . . . . . . 30 2.5.2 Adaptation to Discretized SOSP . . . . . . . . . . . . . . . . . . . 32 2.6 Discrete Adaptation of the Reset Disambiguation Algorithm . . . . . . . . 33 2.7 Generalizing SRA and RDA: Penalty-Based Algorithms and DTA . . . . . 34 2.7.1 Illustration of the Algorithms . . . . . . . . . . . . . . . . . . . . . 36 2.8 Computational Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.8.1 Environment A (The COBRA Data) Experiments . . . . . . . . . 40 2.8.2 Environment B Experiments . . . . . . . . . . . . . . . . . . . . . 41 2.8.3 Environment C Experiments . . . . . . . . . . . . . . . . . . . . . 43 2.9 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 A Impact of Cost Change in Parallel Graphs 47 Bibliograph

Delineating Sea-Level Rise Inundation: An Exploration of Data Structures and Performance Optimization

Based on a conservative projection by the IPCC (IPCC 2007), inundation caused by sea level rise will likely disrupt the physical, economic, and social systems in coastal regions around the world. This research proposed an innovative method to calculate the minimum sea level rise required to inundate a cell in a Digital Elevation Model (DEM). The method, which accounts for water connectivity when determining inundation height for each cell, performs better than the simple “bathtub” approach, especially with sea level rises below 1 m. Several implementation data structures are proposed and compared. The combination of a binary heap and hash table data structure gives the most efficient implementation. The implementation is further parallelized using a master / worker paradigm. The parallel approach significantly outperforms serial implementations with respect to running time and memory footprint. Performance can be further improved with additional processing cores and using the supercomputing resources in the XSEDE (Towns, et al., 2014) program

Development of a spatial sugarcane transport infrastructure-planning model.

Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.Due to the significant cost of transport in the sugar industry, a model, named FastTrack, was developed to investigate infrastructure planning opportunities. The model mathematically incorporates road construction and maintenance costs, terrain and land-use maps, vehicle performance specifications and annual sugarcane volumes to determine the most cost effective route, per vehicle type, from a production region to a mill. Route planning using geographical information systems (GIS) is a standard approach for determining the optimum alignment for pipelines, roads and canals. Theory of this approach was reviewed to create a foundation for the development of FastTrack. A small portion of the Noodsberg sugar mill region in the KwaZulu-Natal midlands was selected as a case study area to test the capabilities of FastTrack. A start location was identified as a natural flow point for 70 000 tons of sugarcane hauled from an area south of the mill. Currently this volume is transported along a 9.3 km stretch of national road from the start location to the sugar mill, while the Euclidean distance is approximately 7 km. Three vehicle types, differing in payload, fuel consumption and road speed were assessed. Two common and currently utilised vehicles, the tractor hilo and interlink combinations, were aligned by FastTrack along existing national roads. A financial penalty for driving on national roads was assumed for the third vehicle type considered, land trains, as these are currently not permitted to operate on national roads in South Africa. This high bulk vehicle was selected to test the capabilities of FastTrack and to identify if cost savings could be realised through increased consignment capacity as has been achieved in Australia, Malawi and Brazil. Utilising the model a new and more direct theoretical route was generated for the land train with a length of 7.4 km. Existing farm roads which would require upgrading made up 34 % of this proposed route. An economic analysis was conducted and showed that under current conditions, the private route generated by FastTrack for land train use, would be the most cost effective, with a system cost of R 57.50 t" . The tractor hilo and interlink had system costs of R 59.58 t" and R 60.98 t"1 respectively. Repeating the economic analysis with projected fuel prices indentified that the cost saving advantage of the land train system over the other two vehicle configurations increases with increasing fuel costs. A rigorous validation process, including a sensitivity analysis of results from FastTrack, revealed that the model performs predictably under a wide range of input conditions and could be a valuable tool for decision making in the sugar industry. However, further research is required to combine more economic and logistical aspects into FastTrack and to increase its usability

Development of a spatial sugarcane transport infrastructure-planning model.

Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.Due to the significant cost of transport in the sugar industry, a model, named FastTrack, was developed to investigate infrastructure planning opportunities. The model mathematically incorporates road construction and maintenance costs, terrain and land-use maps, vehicle performance specifications and annual sugarcane volumes to determine the most cost effective route, per vehicle type, from a production region to a mill. Route planning using geographical information systems (GIS) is a standard approach for determining the optimum alignment for pipelines, roads and canals. Theory of this approach was reviewed to create a foundation for the development of FastTrack. A small portion of the Noodsberg sugar mill region in the KwaZulu-Natal midlands was selected as a case study area to test the capabilities of FastTrack. A start location was identified as a natural flow point for 70 000 tons of sugarcane hauled from an area south of the mill. Currently this volume is transported along a 9.3 km stretch of national road from the start location to the sugar mill, while the Euclidean distance is approximately 7 km. Three vehicle types, differing in payload, fuel consumption and road speed were assessed. Two common and currently utilised vehicles, the tractor hilo and interlink combinations, were aligned by FastTrack along existing national roads. A financial penalty for driving on national roads was assumed for the third vehicle type considered, land trains, as these are currently not permitted to operate on national roads in South Africa. This high bulk vehicle was selected to test the capabilities of FastTrack and to identify if cost savings could be realised through increased consignment capacity as has been achieved in Australia, Malawi and Brazil. Utilising the model a new and more direct theoretical route was generated for the land train with a length of 7.4 km. Existing farm roads which would require upgrading made up 34 % of this proposed route. An economic analysis was conducted and showed that under current conditions, the private route generated by FastTrack for land train use, would be the most cost effective, with a system cost of R 57.50 t" . The tractor hilo and interlink had system costs of R 59.58 t" and R 60.98 t"1 respectively. Repeating the economic analysis with projected fuel prices indentified that the cost saving advantage of the land train system over the other two vehicle configurations increases with increasing fuel costs. A rigorous validation process, including a sensitivity analysis of results from FastTrack, revealed that the model performs predictably under a wide range of input conditions and could be a valuable tool for decision making in the sugar industry. However, further research is required to combine more economic and logistical aspects into FastTrack and to increase its usability