A Global and Dynamitic Route Planning Application for Smart Transportation

Sun, Ning; Han, Guangjie; Duan, Pengfei; Tan, Jiayao

doi:10.1109/ccitsa.2015.43

Cited by 5 publications

(4 citation statements)

References 8 publications

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“…All of the navigation systems mentioned above are in the stage of simulation testing, so they are obviously not available to users. Other researchers have created a navigation app that uses Dijkstra's algorithm for route planning and takes advantage of data from RSUs [21]. The application was not designed for DTA, and cannot be applied with Jakarta's infrastructure.…”

Section: Related Workmentioning

confidence: 99%

Entropy-Based k Shortest-Path Routing for Motorcycles: A Simulated Case Study in Jakarta

Asvial¹,

Pandoyo

Arifin³

2020

IJACSA

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Traffic congestion is a serious problem in rapidly developing urban areas like Jakarta, Indonesia's capital city. To avoid the congestion, motorcycles assisted with navigation apps are popular solution. However, the existing navigation apps do not take into account traffic data. This paper proposes an opensource navigation app for motorcycle by taking into account the traffic data and wide road to avoid congestion. The propose navigation app uses entropy-balanced k shortest paths (EBkSP) algorithm to suggest different routes to different users to prevent further congestion. Tests show that the proposed route planning system in the app gives routes that are significantly shorter than motorcycle routes planned by Google Maps. The EBkSP algorithm also distributes vehicles more evenly among routes than the random kSP algorithm and does so in a practical amount of computing time.

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Section: Related Workmentioning

confidence: 99%

Entropy-Based k Shortest-Path Routing for Motorcycles: A Simulated Case Study in Jakarta

Asvial¹,

Pandoyo

Arifin³

2020

IJACSA

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show abstract

“…where P i represents control points of the Bezier curves, u represents the parameters, and B i,n (u) are known as Bernstein basis polynomials and satisfy Equations (7) and 8:…”

Section: Trajectory Generation By Bezier Curvesmentioning

confidence: 99%

“…There have been a number of studies regarding local path planning. an intelligent system is designed which can monitor urban traffic congestion in real time through wireless sensor networks [7], and urban application-oriented route planning are researched based on the mobile communication network [8]. A vision-based approach is addressed to identify the leader vehicle [9], and a path planning algorithm is proposed for autonomous driving in a complex urban environment [10].…”

Section: Introductionmentioning

confidence: 99%

Local Path Planning of Driverless Car Navigation Based on Jump Point Search Method Under Urban Environment

Zhou

Long

et al. 2017

Future Internet

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Abstract:The Jump Point Search (JPS) algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS) map, including Global Positioning System (GPS) position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the JPS algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that JPS can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH), the Rapidly Exploring Random Tree (RRT), A*, and the Probabilistic Roadmaps (PRM) algorithms. Furthermore, JPS is validated usefully in the structured urban environment.

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“…Automated Guided Vehicles (AGVs) are the main tools, which enable automatic access to goods transportation without human labor. With the development of Smart City and Internet of ings technology, the route-planning algorithms of AGVs in SRNSs are commonly used not only in logistics industries and smart factories but also in intelligent transportation systems [1], energy transmission systems [2], and even network planning [3]. With the wide application of AGVs route planning, the goal of route planning is not only to find the route with the shortest distance from AGVs' start nodes to their goal nodes but also to minimize the system operating time and reduce energy cost.…”

Section: Introductionmentioning

confidence: 99%

AGVs Route Planning Based on Region-Segmentation Dynamic Programming in Smart Road Network Systems

Zhang¹,

Chen²,

Guo³

2021

Scientific Programming

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In this paper, a route-planning approach is proposed based on the region-segmentation Dynamic Programming (DP) algorithm for Automated Guided Vehicles (AGVs) in large Smart Road Network Systems (SRNSs) to deal with the problem of low route computation efficiency of the classical DP algorithm. We introduced an improved Markov Decision Process (MDP) to describe SRNSs, in which the SRNSs are divided into several regions according to the AGVs’ start nodes and their goal nodes to improve the route-planning efficiency. Moreover, the route with the minimum number of turns is selected to reduce the system running time and energy cost in the following way: first, all the equidistant shortest routes are acquired from the AGVs’ start nodes to their goal nodes using the improved DP algorithm; then, the routes are screened by calculating the angular deviation between all feasible routes and AGVs’ initial directions, and the route with the fewest number of turns is taken as the shortest-time route. The simulation results verified that the proposed method can effectively solve the route-planning problem of AGVs in current SRNSs.

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A Global and Dynamitic Route Planning Application for Smart Transportation

Cited by 5 publications

References 8 publications

Entropy-Based k Shortest-Path Routing for Motorcycles: A Simulated Case Study in Jakarta

Entropy-Based k Shortest-Path Routing for Motorcycles: A Simulated Case Study in Jakarta

Local Path Planning of Driverless Car Navigation Based on Jump Point Search Method Under Urban Environment

AGVs Route Planning Based on Region-Segmentation Dynamic Programming in Smart Road Network Systems

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