Dynamic travel time provision for road networks

Pfoser, Dieter; Brakatsoulas, Sotiris; Brosch, Petra; Umlauft, Martina; Tryfona, Nektaria; Tsironis, G. P.

doi:10.1145/1463434.1463513

Cited by 35 publications

(22 citation statements)

References 4 publications

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“…Other studies, which contributed to a significant improvement in the traffic control, focused on the identification of unique road sections [23], assessment of the commuting time between defined destinations [24], exploring the pattern of traffic condition in a city, and thereby assess and forecast the traffic patterns [25].…”

Section: Potential Of Vr In Visualizing Smart Transportation For a Citymentioning

confidence: 99%

Investigating the Role of Virtual Reality in Planning for Sustainable Smart Cities

et al. 2017

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Abstract:With rapid population growth, urban designers face tremendous challenges to accommodate the increasing size of the population in urban areas while simultaneously considering future environmental, social, and economic impacts. A "smart city" is an urban development vision that integrates multiple information and communication technologies to manage the assets of a city, including its information systems, transportation systems, power plants, water supply networks, waste management systems, and other community services provided by a local department. The goal of creating a smart city is to improve the quality of life of citizens by using technology and by addressing the environmental, social, cultural, and physical needs of a society. Data modeling and data visualization are integral parts of planning a smart city, and planning professionals currently seek new methods for real-time simulations. The impact analysis of "what-if scenarios" frequently takes a significant amount of time and resources, and virtual reality (VR) is a potential tool for addressing these challenges. VR is a computer technology that replicates an environment, whether real or imagined, and simulates the physical presence and environment of a user to allow for user interaction. This paper presents a review of the capacity of VR to address current challenges in creating, modeling, and visualizing smart cities through material modeling and light simulation in a VR environment. This study can assist urban planners, stakeholders, and communities to further understand the roles of planning policies in creating a smart city, particularly in the early design stages. The significant roles of technologies, such as VR, in targeting real-time simulations and visualization requirements for smart cities are emphasized.

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Section: Potential Of Vr In Visualizing Smart Transportation For a Citymentioning

confidence: 99%

Investigating the Role of Virtual Reality in Planning for Sustainable Smart Cities

et al. 2017

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“…Sung et al [21] present a Flow Speed Model that computes the travel time on each road segment as a piecewise linear function of time. Pfoser et al [17,18] contribute techniques that can derive the up-to-date speed associated with a road segment at a given time based on Floating Car Data. Kanoulas et al in [13] propose an A*-extended algorithm.…”

Section: Exp-4 Impact Of the Length Of Time Interval [T D Ta]mentioning

confidence: 99%

Finding the cost-optimal path with time constraint over time-dependent graphs

Yang

Gao

et al. 2014

Proc. VLDB Endow.

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Shortest path query is an important problem and has been well studied in static graphs. However, in practice, the costs of edges in graphs always change over time. We call such graphs as timedependent graphs. In this paper, we study how to find a costoptimal path with time constraint in time-dependent graphs. Most existing works regarding the Time-Dependent Shortest Path (TD-SP) problem focus on finding a shortest path with the minimum travel time. All these works are based on the following fact: the earliest arrival time at a vertex v can be derived from the earliest arrival time at v's neighbors. Unfortunately, this fact does not hold for our problem. In this paper, we propose a novel algorithm to compute a cost-optimal path with time constraint in time-dependent graphs. We show that the time and space complexities of our algorithm are O(kn log n + mk) and O((n + m)k) respectively. We confirm the effectiveness and efficiency of our algorithm through conducting experiments on real datasets with synthetic cost.

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“…Deploying a fixed infrastructure [1,2,3], such as wireless sensors [2] or RFID readers and wireless APs [10], on roadsides or traffic lights, is a relatively steady approach to collect and transmit traffic data. However, applying such models on large cities usually costs much on installation and maintenance.…”

Section: Related Workmentioning

confidence: 99%

“…Otherwise, if it is elected to forward the query by our DDFS algorithm (to be introduced later), it identifies the entry <seg_id, aggregate, count> in path_info, based on the id of the road segment it is currently located in. Assume the current aggregate is v avg , the current velocity of the vehicle is v own , and count is c, the new aggregate will be updated as v' avg according to (1) and then count is increased by one.…”

Section: A Routing Andtraffic Data Aggregationmentioning

confidence: 99%

“…These centralized infrastructures rely on a large number of sensors or other devices located on roadsides or traffic lights to collect traffic data and report to a central server. Then, the real-time traffic information is broadcasted to vehicles via infrastructure equipments [1,2,3]. While such kinds of systems are useful, they are not widely deployed in large cities yet.…”

Section: Introductionmentioning

confidence: 99%

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VAN: Vehicle-assisted shortest-time path navigation

Chen

Zhu

2010

The 7th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (IEEE MASS 2010)

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Abstract-Traffic congestion is a very serious problem in large cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. In this paper, by leveraging the techniques of Vehicular Ad hoc Networks (VANETs) we present a dynamic navigation protocol called VAN for individual vehicles to find the shortest-time paths toward their given destinations. Specifically, a vehicle initiates a number of queries, which are routed by VANETs along different paths toward its destination. During query forwarding, the real-time road traffic information in each road segment is aggregated from multiple participating vehicles and returned to the source after the query reaches the destination. This information enables the source to calculate the shortest-time path. We also propose two forwarding optimization methods to reduce communication costs and an error handling mechanism to deal with abnormal circumstances. To evaluate its performance, we use the real traffic data of Beijing, including 2,308 road segments at two different times. Our simulation results demonstrate that our protocol, on average, could save around 30% driving time, compared to traveling along the shortest distance paths.

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Dynamic travel time provision for road networks

Cited by 35 publications

References 4 publications

Investigating the Role of Virtual Reality in Planning for Sustainable Smart Cities

Investigating the Role of Virtual Reality in Planning for Sustainable Smart Cities

Finding the cost-optimal path with time constraint over time-dependent graphs

VAN: Vehicle-assisted shortest-time path navigation

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