A Dynamic Shortest Travel Time Path Planning Algorithm with an Overtaking Function Based on VANET

The vehicular ad-hoc network (VANET) is a promising technology in near future. VANET allows vehicles to communicate with each other and with roadside units (RSUs). Wireless Access in Vehicular Environment (WAVE), defined by IEEE, provides the Internet connectivity for vehicles as well as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. RSUs can form a wireless mesh network (WMN) as a backbone infrastructure to enhance the performance of VANET. However, WAVE supports only one-hop communications for IP packets in VANET, and existing researches do not consider the compatibility between VANET and WMN infrastructure formed by RSUs. We propose the extended WMN (ExWMN) which has the feasibility to extend WMN to VANET domain. In ExWMN, the vehicles can send IP packets to an access router by using the multi-hop capability of WMN. ExWMN uses the addressing scheme of WMN for the extended VANET domain and exploits geographical routing protocols instead of existing routing protocols of WMN due to VANET characteristics such as mobility and dynamically changing network topologies. ExWMN supports the compatibility between the extended VANET and a WMN infrastructure due to RSUs, which provide a bridging function between them. This paper presents the architecture and the detailed procedures of the ExWMN.

At present, the walking routes of service robots are mostly formulated and fixed. Therefore, there are many places that the robots cannot reach and appear inflexible. When obstacles are on the walking route of the robot, collisions may occur. Thus, an area-optional regeneration Rapidly-Exploring Random Tree (RRT) algorithm for dynamic path planning is proposed to plan the walking route of the service robot in real-time in an environment with moving obstacles in this paper. First, sub-regions that need path planning can be determined according to the target points, and each sub-region corresponds to a root node, so that a feasible path that does not touch obstacles through a narrow area can be found faster, and the speed of path planning can be improved. Secondly, in real-time path planning, it is analyzed that whether tree nodes near moving obstacles need to be removed. Besides, how to remove, add, and reconnect are also analyzed, avoiding global planning and improving the efficiency of path planning in frequently changing environments. It is verified by simulation that the efficiency of path planning can be improved after dividing the area, and the effectiveness and superiority of the algorithm are verified in a real-time changing environment.KeywordsArea-optionalRegeneration RRT algorithmObstacle avoidanceReal-time path planning

Dynamic path planning of mobile robot based on improved simulated annealing algorithm

This paper presents a novel ACO algorithm to solve the global path planning problem, called Heterogeneous ACO (HACO) algorithm. We proposed HACO algorithm to improve the performance of ACO for global path planning in the previous paper. The HACO algorithm differs from the Conventional ACO (CACO) algorithm for the path planning in three respects. First, we proposed modified Transition Probability Function (TPF) and Pheromone Update Rule (PUR). Second, we newly introduced the Path Crossover (PC) in the PUR. Finally, we also proposed the first introduction of the heterogeneous ants in the ACO algorithm. We apply the proposed HACO algorithm to general path planning problem and we verify the effect of the each scheme through the simulation.

An integrated multiple autonomous underwater vehicle (multi-AUV) dynamic task assignment and path planning algorithm is proposed by combing the improved self-organizing map (SOM) neural network and...

Vehicular ad hoc networks have played a key role in intelligent transportation systems that considerably improve road safety and management. This new technology allows vehicles to communicate and share road information. However, malicious users may inject false emergency alerts into vehicular ad hoc networks, preventing nodes from accessing accurate road information. In order to assure the reliability and trustworthiness of information through the networks, assessing the credibility of nodes has become a critical task in vehicular ad hoc networks. A new scheme for malicious node detection is proposed in this work. Multiple factors are fed into a fuzzy logic model for evaluating the trust for each node. Vehicles are divided into clusters in our approach, and a road side unit manages each cluster. The road side unit assesses the credibility of nodes before accessing vehicular ad hoc networks. The road side unit evicts a malicious node based on trust value. Simulations are used to validate our technique. We demonstrate that our scheme can detect and evict all malicious nodes in the vehicular ad hoc network over time, lowering the ratio of malicious nodes. Furthermore, it has a positive impact on selfish node participation. The scheme increases the success rate of delivered data to the same level as the ideal cases when no selfish node is present.

Emergency response time often makes difference between life and death in cases that man-made or natural disasters happen. In this paper, we propose a real-time route guidance strategy to reduce the traveling time of emergency vehicles. Our strategy consists of path planning and reverse path planning for emergency vehicles. Since the traffic condition changes at any time, we use current and historical traffic information to plan a path. Furthermore, we propose a lane reservation scheme for emergency vehicles to minimize the crash risks. Before an emergency vehicle arrives at each road segment, Road Side Units (RSUs) will at suitable time start to disseminate the warning message so that other drivers have enough time to take proper actions such as speed deceleration or changing lane. Simulation results show that the proposed approach can reduce more than 20% traveling time of emergency vehicles comparing to the shortest path approach with sirens and lights to alert other drivers. By reducing the traveling time, the emergency rescue teams have higher probability to rescue lives and property in time.

We consider the problem of warehouse multi-robot automation system in discrete-time and discrete-space configuration with focus on the task allocation and conflict-free path planning. We present a system design where a centralized server handles the task allocation and each robot performs local path planning distributively. A genetic-based task allocation algorithm is firstly presented, with modification to enable heuristic learning. A semi-complete potential field based local path planning algorithm is then proposed, named the recursive excitation/relaxation artificial potential field (RERAPF). A mathematical proof is also presented to show the semi-completeness of the RERAPF algorithm. The main contribution of this paper is the modification of conventional artificial potential field (APF) to be semi-complete while computationally efficient, resolving the traditional issue of incompleteness. Simulation results are also presented for performance evaluation of the proposed path planning algorithm and the overall system.

Emerging as the effective strategy of intelligent transportation system (ITS), vehicular ad hoc networks (VANETs) have the capacity of drastically improving the driving experience and road safety. In typical VANET scenarios, high mobility and volatility of vehicles result in dynamic topology of vehicular networks. That is, individual vehicle may pass through the effective domain of multiple neighboring road-side-units (RSUs) during a comparatively short time interval. Hence, efficient and low-latency cross-domain verification with all the successive RSUs is of significance. Recently, a lot of research on VANET authentication and key distribution was presented, while the critical cross-domain authentication (CDA) issue has not been properly addressed. Particularly, the existing CDA solutions mainly reply on the acquired confidential keying information from the neighboring entities (RSUs and vehicles), while too much trustworthiness is granted to the involved RSUs. Please note that the RSUs are distributively located and may be compromised or disabled by adversary, thus vital vehicle information may be revealed. Furthermore, frequent data interactions between RSUs and cloud server are always the major requisite so as to achieve mutual authentication with cross-domain vehicles, which leads to heavy bandwidth consumption and high latency. In this paper, we address the above VANET cross-domain authentication issue under the novel RSU edge networks assumption. Please note that RSUs are assumed to be semi-trustworthy entity in our design, where critical vehicular keying messages remain secrecy. Homomorphic encryption design is applied for all involved RSUs and vehicles. In this way, successive RSUs could efficiently verify the cross-domain vehicle with the transited certificate from the neighbor RSUs and vehicle itself, while the identity and secrets of each vehicle is hidden all the time. Afterwards, dynamic updating towards the anonymous vehicle identity is conducted upon validation, where conditional privacy preserving is available. Moreover, pairing-free mutual authentication method is used for efficiency consideration. Formal security analysis is given, proving that the HCDA mechanism yields desirable security properties on VANET cross domain authentication issue. Performance discussions demonstrate efficiency of the proposed HCDA scheme compared with the state-of-the-art.

Vehicular ad-hoc network (VANET) technology enables communication between vehicles, or vehicles and road-side units (RSUs) through wireless communication devices installed on the vehicles. One of the most important goals of VANETs is providing safety applications for passengers. In addition, VANETs provide comfort applications to users. Guaranteeing a reliable and stable routing protocol over VANETs is a very important step. The proposed research attempts to improve routing protocols that decrease the end-to-end delay to suit VANET communication characteristics. In addition, it proposes analysis of the end-to-end delay probability distribution. More specifically, we derive a closed-form expression for the probability distribution of the re-healing delay in a VANET conditioned on the distance between two VANET clusters. Furthermore, we propose a closed-form expression for the probability distribution of the unconditional re-healing delay. Moreover, we develop a mathematical model to calculate the probability distribution of the end-to-end delay. On the other hand, using Unmanned Aerial Vehicles (UAVs) or drones in wireless communications and Vehicular Ad-hoc Networks (VANETs) has started to attract attention. We propose a routing protocol that uses infrastructure drones for boosting VANET communications to achieve a minimum vehicle-to-drone packet delivery delay. In addition, we propose a closed-form expression for the probability distribution of the vehicle-to-drone packet delivery delay on a two-way highway. Moreover, based on that closed-form expression, we can calculate the minimum drone density (maximum separation distance between two adjacent drones) that stochastically limits the worst case of the vehicle-to-drone packet delivery delay. Furthermore, we propose a drones-active service (DAS) that is added to the location service in a VANET. This service dynamically and periodically obtains the required number of active drones based on the current highway connectivity state by obtaining the maximum distance between each two adjacent drones while satisfying a probabilistic constraint for vehicle-todrone packet delivery delay. Our analysis focuses on two-way highway VANET networks with low vehicular density. The simulation results show the accuracy of our analysis and reflect the relation between the drone density, vehicular density and speed, other VANET parameters, and the vehicle-to-drone packet delivery delay. In addition, we propose a new routing protocol called multi-copy intersection-based routing (MCIR) for vehicular ad-hoc networks (VANETs) in urban areas. MCIR is an intersectionbased routing protocol that forwards multiple copies of the packets in different road segments. Moreover, it is a beacon-less routing protocol with a carry-and-forward strategy. We show via simulation that the MCIR protocol is superior to other existing routing protocols, especially in low vehicular density scenarios. The results show that MCIR achieves a shorter end-to-end delay and a higher packet delivery ratio in urban VANET communications.

This paper presents a biomimetic underwater glider inspired by the manta ray. Theoretical research is conducted to establish a dynamic model and address the path planning problem in gliding mode. A novel dynamic model for the gliding mode is developed, which takes the acceleration of a movable mass and the rate of change of a buoyancy control device as control inputs. Compared to previous methods, this model incorporates the real-time dynamic response of the control system, providing a more detailed depiction of the glider's dynamic behavior. Furthermore, the steady-state equation of gliding motion within a vertical section under ocean current conditions is derived, establishing a quantitative relationship between control states and gliding steady states, which is crucial for studying gliding motion under ocean currents. Based on the dynamic model, a performance evaluation model for the glider is proposed, with evaluation metrics including energy consumption, travel time, and detection range. The path planning problem is transformed into a multi-objective optimization problem by incorporating the performance evaluation model into the research and solved using the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) algorithm for different motion strategies. Numerical results demonstrate that under both ocean current and non-current conditions, the proposed path planning method can yield path parameters that meet various performance evaluation criteria and are more comprehensive, thereby validating the effectiveness of the proposed path planning approach.

Vehicular ad hoc network (VANET) has attracted more attention for providing safe and efficient traffic management in the modern roads. Performance of the VANET depends on proper routing protocol, mobility management, and efficient inter-vehicular communications. To ensure the optimal data forwarding and energy efficiency in VANET, a suitable network hierarchy is required. In this paper, we propose a new optical network-based clustering hierarchy (ONCH) to improve the quality of services of the VANET. In the proposed scheme, the road side units (RSUs) of a VANET will be divided into several small groups called clusters. In each cluster, an RSU will act as gateway node and each gateway node will be connected to the WiMAX base station through optical fiber. We have analyzed the performance of the proposed ONCH scheme by numerical simulations. The simulated results prove that the ONCH scheme of VANET provides higher energy efficiency than the conventional wireless network-based clustering hierarchy (WNCH) scheme of VANET.

In order to solve the problems of large storage, excessive redundant nodes and inflection points of paths, and unsmooth track in the traditional A*algorithm. This paper presents a fusion algorithm of mobile robot path planning based on the improved A* and dynamic window approach. Firstly, selectively expand the neighborhood according to the connection between the node to be expanded and the target node, and reduce the expanded nodes in openlist and closelist. Secondly, according to the key node extraction strategy, eliminate the redundant path nodes and unnecessary inflection points generated by A* tracking. Finally, the dynamic window approach is integrated to carry out real-time dynamic path planning. The Matlab simulation experiment results show that the improved fusion algorithm shortens the path length, and the smoothness and security of the path are also optimized.

In recent years, unmanned aerial vehicle (UAV), has been increasingly applied to research in various fields due to its small size and fast speed. Among them, the path planning of UAV under various actual environmental constraints has been one of the hot issues for the past few years. UAV path planning is to find the optimal or feasible route from the starting point to the target point and meet the UAV performance indicators under specific constraints. The essence of the problem is the optimization problem of multi-objective function to find the extreme value under multi-constraints. In this paper, under the background of logistics distribution, Through the research of UAV path planning model and algorithm, this paper summarizes the UAV path planning problems, analyzes several common path planning algorithms in recent years, and carries out simulation experiments with MATLAB on several algorithms with high attention. On this basis, the future research direction is prospected.KeywordsLogistics distributionUnmanned aerial vehicle (UAV)Path planning modelPath planning algorithm

With the development of the vehicular communications technology, roadside units (RSUs) placement problem has recently received considerable attentions in vehicular ad hoc networks (VANETs). This paper addresses the roadside units (RSUs) placement problem for traffic flow coverage requirement number in vehicular ad hoc networks (VANETs). Given a set of road segments, some traffic flows and a coverage requirement number n, the problem is how to find the optimal placement of RSUs, such that each traffic flow is covered by at least n RSUs. We first investigate full RSUs placement problem, which place all the RSUs on the given road segments totally. We prove that this problem is NP-hard. Then, we propose a greedy algorithm to solve the problem and theoretical analysis is given. We also study incremental RSUs placement problem, which place the partial RSUs based on the deployed RSUs on the given road segments. Based on the proposed greedy algorithm, we also propose a algorithm to solve the incremental RSUs placement problem. Extensive simulations have been conducted to show the performance of our proposed algorithms is superior to the other algorithms.