A distributed approach for shortest path algorithm in dynamic multimodal transportation networks

Idri, Abdelfattah; Oukarfi, Mariyem; Boulmakoul, Azedine; Zeitouni, Karine; Masri, Ali El

doi:10.1016/j.trpro.2017.12.094

Cited by 16 publications

(9 citation statements)

References 8 publications

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“…References [7], [14], [35], [36] focus on the shortest path between specified starting and target points. Reference [25] proposed a sharing considered route assignment mechanism for fair taxi route recommendations (SCRAM), which is capable of providing taxi drivers with more efficient routes that have the least driving cost per customer.…”

Section: The Navigation Systems For the Path Planningmentioning

confidence: 99%

A Novel Vector-Based Dynamic Path Planning Method in Urban Road Network

Cai

Cui

et al. 2020

IEEE Access

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The optimal path planning is one of the hot spots in the research of intelligence transportation and geographic information systems. There are many productions and applications in path planning and navigation, however due to the complexity of urban road networks, the difficulty of the traffic prediction increases. The optimal path means not only the shortest distance in geography, but also the shortest time, the lowest cost, the maximum road capacity, etc. In fast-paced modern cities, people tend to reach the destination with the shortest time. The corresponding paths are considered as the optimal paths. However, due to the high data sensing speed of GPS devices, it is different to collect or describe real traffic flows. To address this problem, we propose an innovative path planning method in this paper. Specially, we first introduce a crossroad link analysis algorithm to calculate the real-time traffic conditions of crossroads (i.e. the CrossRank values). Then, we adopt a CrossRank value based A-Star for the path planning by considering the real-time traffic conditions. To avoid the high volume update of CrossRank values, a R-Tree structure is proposed to dynamically update local CrossRank values from the multi-level subareas. In the optimization process, to achieve desired navigation results, we establish the traffic congestion coefficient to reflect different traffic congestion conditions. To verify the effectiveness of the proposed method, we use the actual traffic data of Beijing. The experimental results show that our method is able to generate the appropriate path plan in the peak and low dynamic traffic conditions as compared to online applications. INDEX TERMS CrossRank, path planning, vector, heuristic algorithm.

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Section: The Navigation Systems For the Path Planningmentioning

confidence: 99%

A Novel Vector-Based Dynamic Path Planning Method in Urban Road Network

Cai

Cui

et al. 2020

IEEE Access

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“…Step 4: The membership degree of each vector element f to the three cluster centers is calculated in Formula (6).…”

Section: (3) Improved Fuzzy C-means Clusteringmentioning

confidence: 99%

“…The clustering results of the log road vector element features relative to the time (red), economic (green), and comfort (blue) cluster centers are shown in Figure 3. Step 4: The membership degree of each vector element to the three cluster centers is calculated in Formula (6).…”

Section: (3) Improved Fuzzy C-means Clusteringmentioning

confidence: 99%

“…Mature navigation systems and path planning algorithms mainly focus on the fastest path [1][2][3][4], the shortest path [5][6][7][8] or the most comfortable path [4,9] between specified starting and target points. In recent years, path optimization algorithms of multi-objective optimization [10][11][12][13][14] and single-objective optimization [15,16], as well as a few traffic impact factors, have deepened [17,18] and popular routes planning [19,20].…”

Section: Introductionmentioning

confidence: 99%

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Path Planning Strategy for Vehicle Navigation Based on User Habits

et al. 2018

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Vehicle navigation is widely used in path planning of self driving travel, and it plays an increasing important role in people's daily trips. Therefore, path planning algorithms have attracted substantial attention. However, most path planning methods are based on public data, aiming at different driver groups rather than a specific user. Hence, this study proposes a personalized path decision algorithm that is based on user habits. First, the categories of driving characteristics are obtained through the investigation of public users, and the clustering results corresponding to the category space are obtained by log fuzzy C-means clustering algorithm (LFCM) based on the driving information contained in the log trajectories. Then, the road performance personalized quantization algorithm evaluation is proposed to evaluate roads from the user's field of vision. Finally, adaptive ant colony algorithm is improved and used to validate the path planning based on the road performance personalized values. Results show that the algorithm can meet the personalized requirements of the user path selection in the path decision.

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“…On the contrary, it is a dynamic path optimization (DPO) problem to optimize the emergency path by using the forecast information about adverse weather, because some nodes and/or links of route network might temporarily become inaccessible due to adverse weather. Now, there are many algorithms for DPO [31][32][33][34][35][36][37][38][39][40]. Once the road network changes due to adverse weather, traditional DPO methods usually have to conduct real-time online re-optimization of travelling path.…”

Section: Introductionmentioning

confidence: 99%

A Method to Assess and Reduce Pollutant Emissions of Logistic Transportation under Adverse Weather

Zhang

Wang

2019

Sustainability

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With the increase of vehicle activities and adverse weather under the background of modernization and global warming, more attention should be paid to vehicle emissions reduction in such circumstances for environmental protection and sustainable transportation. Different from some typical measures, e.g., relevant government policies, improvement of vehicle hardware technologies, and optimization of traffic management, this paper develop a new method based on emergency path optimization to evaluate and reduce pollutant emissions of logistic transportation under adverse weather. Firstly, we establish a calculation model of pollutant emissions (LT-PE model) to calculate the amount of vehicle pollutant emissions produced under adverse weather. Then, a co-evolving path optimization (CEPO) method-based ripple-spreading algorithm is proposed in order to reduce pollutant emissions. To validate the effectiveness of the proposed method, this paper selects fruit logistics transportation affected by typhoon in China’s Hainan Island as a case study. The results show that total vehicle pollutant emissions from the fruit transportation of 35 farms under the typhoon are 28.1% more than when there is no typhoon. The proposed method can reduce pollutant emissions by 21.2% compared with the traditional methods under typhoon.

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A distributed approach for shortest path algorithm in dynamic multimodal transportation networks

Cited by 16 publications

References 8 publications

A Novel Vector-Based Dynamic Path Planning Method in Urban Road Network

A Novel Vector-Based Dynamic Path Planning Method in Urban Road Network

Path Planning Strategy for Vehicle Navigation Based on User Habits

A Method to Assess and Reduce Pollutant Emissions of Logistic Transportation under Adverse Weather

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