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A VANET-Based A* Route Planning Algorithm for Travelling Time- and Energy-Efficient GPS Navigation App:

TLDR
A vehicular-ad-hoc-network- (VANET-) based route planning algorithm is proposed to calculate the route with the shortest travelling time or the lowest fuel consumption, depending on two real-time traffic information sources, which have not been used in traditional GPS navigation applications.
Abstract
Most current navigation devices or apps, based on the global positioning system (GPS), only adopt static information for route planning. Although some are equipped with an RDS-TMC receiver to receive real-time traffic events, many of these real-time traffic events are irrelevant to the vehicle. This paper offers three major contributions. First, a vehicular-ad-hoc-network- (VANET-) based () route planning algorithm is proposed to calculate the route with the shortest travelling time or the lowest fuel consumption, depending on two real-time traffic information sources, which have not been used in traditional GPS navigation applications. The first traffic information source is the recorded traffic information of the road segment that the vehicle has passed through. It is further exchanged between vehicles through an IEEE 802.11p wireless link. The second traffic information is provided by Google Maps. A GPS navigation app is then implemented on the Android platform to realize . Finally, simulations for six route planning algorithms are executed by VANET simulator The ONE, in one congested and one noncongested time period, respectively. In summary, achieves significant reductions in both the average travelling time and fuel consumption of the planned route, as compared to traditional route planning algorithms.

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Citations
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Journal ArticleDOI

A Review of Machine Learning and IoT in Smart Transportation

TL;DR: A self-contained review of ML techniques and IoT applications in Intelligent Transportation Systems (ITS) and obtain a clear view of the trends in the aforementioned fields and spot possible coverage needs.
Journal ArticleDOI

Overview of Path-Planning and Obstacle Avoidance Algorithms for UAVs: A Comparative Study

TL;DR: This research presents a probabilistic procedure that can be used to estimate the altitude and speed of UAVs using a 3D camera system, and shows the effectiveness of this method for short-term, low-frequency navigation.
Journal ArticleDOI

ICARUS: Improvement of traffic Condition through an Alerting and Re-routing System

TL;DR: Simulation results show the effectiveness of ICARUS in calculating new routes and disseminating them to vehicles approaching a congested area and it reduces the travel time, fuel consumption, and CO emissions of vehicles in urban environments when compared to existing approaches.
Journal ArticleDOI

Managing Emergency Situations in VANET Through Heterogeneous Technologies Cooperation.

TL;DR: This paper focuses on the design of a new approach for vehicular environments able to gather information during mobile node trips, for advising dangerous or emergency situations by exploiting on-board sensors.
Journal Article

Intelligent Traffic Management System for Prioritizing Emergency Vehicles in a Smart City (TECHNICAL NOTE)

TL;DR: Comparative results exhibits superior performance of the proposed system over the other recently proposed ITS for emergency vehicles, in terms of both congestion avoidance, transmission delay, travel time and respond to hacking.
References
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Journal ArticleDOI

Generalized best-first search strategies and the optimality of A*

TL;DR: It is shown that several known properties of A* retain their form and it is also shown that no optimal algorithm exists, but if the performance tests are confirmed to cases in which the estimates are also consistent, then A* is indeed optimal.
Journal ArticleDOI

A Note on Dijkstra's Shortest Path Algorithm

TL;DR: An assertion that Dijkstra's algorithm for shortest paths (adapted to allow arcs of negative weight) runs in O(n)(supscrpt) steps is disproved by showing a set of networks which take O (O) 2 (n) 3 steps.
Journal ArticleDOI

Model for developing an eco-driving strategy of a passenger vehicle based on the least fuel consumption

TL;DR: In this article, a model of an optimal driving strategy has been developed and it has been applied for assessment of eco-driving rules and the model may be categorized as an optimal control and the objective function is minimization of fuel consumption in a given route.

Operating cost, fuel consumption and emission models in aaSIDRA and aaMOTION

Rahmi Akçelik, +1 more
TL;DR: In this article, the authors describe the method to model operating cost, fuel consumption and emissions (CO2, CO, HC, NOx) in the aaSIDRA intersection analysis and aaMOTION trip / drive-cycle simulator software packages developed by Akcelik & Associates.
Journal ArticleDOI

Hyperstar: A multi-path Astar algorithm for risk averse vehicle navigation

TL;DR: The Spiess and Florian algorithm for generating hyperpaths in transit networks is adapted to road networks by assuming that drivers follow a risk averse strategy whenever a choice of path arises, leading to the Hyperstar algorithm.
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