scholarly journals Space-Efficient, Fast and Exact Routing in Time-Dependent Road Networks

Algorithms ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 90
Author(s):  
Ben Strasser ◽  
Dorothea Wagner ◽  
Tim Zeitz
Keyword(s):  
Shortest Paths ◽  
Road Networks ◽  
Time Dependent ◽  
Travel Times ◽  
Traffic Patterns ◽  
Two Phase ◽  
The Road ◽  
On The Road ◽  
Core Idea ◽  
Point To Point

We study the problem of quickly computing point-to-point shortest paths in massive road networks with traffic predictions. Incorporating traffic predictions into routing allows, for example, to avoid commuter traffic congestions. Existing techniques follow a two-phase approach: In a preprocessing step, an index is built. The index depends on the road network and the traffic patterns but not on the path start and end. The latter are the input of the query phase, in which shortest paths are computed. All existing techniques have large index size, slow query running times or may compute suboptimal paths. In this work, we introduce CATCHUp (Customizable Approximated Time-dependent Contraction Hierarchies through Unpacking), the first algorithm that simultaneously achieves all three objectives. The core idea of CATCHUp is to store paths instead of travel times at shortcuts. Shortcut travel times are derived lazily from the stored paths. We perform an experimental study on a set of real world instances and compare our approach with state-of-the-art techniques. Our approach achieves the fastest preprocessing, competitive query running times and up to 38 times smaller indexes than competing approaches.

scholarly journals Development of driving cycle under real world traffic conditions: A case study

2019 ◽  
Vol 9 (6) ◽  
pp. 4798
Author(s):  
Geetha A. ◽  
Subramani C.
Keyword(s):  
Driving Cycle ◽  
Time Dependent ◽  
Maximum Speed ◽  
Time Data ◽  
Maximum Acceleration ◽  
The Road ◽  
Traffic Conditions ◽  
Condensed Form ◽  
On The Road

<p><span>The modeling of a car is essentially done by taking into consideration the driving terrain, traffic conditions, driver’s behavior and various other factors which may directly or indirectly affect the vehicle’s performance. A vehicle is modeled for given specifications and constraints like maximum speed, maximum acceleration, and braking time, appropriate suspension for the gradient of the road and fuel consumption. Henceforth, a profound study and analysis of different drive cycles are essential. A time dependent drive cycle is a condensed form of data that helps us to determine the time taken to conduct the driving test on the road. This article highlights the development of a real driving cycle in the area of Tamilnadu, India. On-road vehicle’s speeds versus time data were obtained along the selected route. The data obtained were analyzed first and then a new driving cycle was developed.</span></p>

The Integrative Time-Dependent Modeling of the Reliability and Failure of the Causes of Drivers' Error Leading to Road Accidents

2015 ◽  
pp. 1279-1294
Author(s):  
Khashayar Hojjati-Emami ◽  
Balbir S. Dhillon ◽  
Kouroush Jenab
Keyword(s):  
Human Error ◽  
Time Dependent ◽  
Failure Rates ◽  
Road Accidents ◽  
Road Transportation ◽  
The Road ◽  
Representational Model ◽  
On The Road ◽  
The Moment ◽  
Dependent Failure

Nowadays, the human error is usually identified as the conclusive cause of investigations in road accidents. The human although is the person in control of vehicle until the moment of crash but it has to be understood that the human is under continued impact by various factors including road environment, vehicle and human's state, abilities and conduct. The current advances in design of vehicle and roads have been intended to provide drivers with extra comfort with less physical and mental efforts, whereas the fatigue imposed on driver is just being transformed from over-load fatigue to under-load fatigue and boredom. A representational model to illustrate the relationships between design and condition of vehicle and road as well as driver's condition and state on fatigue and the human error leading to accidents has been developed. Thereafter, the stochastic mathematical models based on time-dependent failure rates were developed to make prediction on the road transportation reliability and failure probabilities due to each cause (vehicle, road environment, human due to fatigue, and human due to non fatigue factors). Furthermore, the supportive assessment methodology and models to assess and predict the failure rates of driver due to each category of causes were developed and proposed.

scholarly journals Analysis of Traffic Evolution on Road Networks of a Roundabout

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Tolesa Hundesa Muleta ◽  
Legesse Lemecha Obsu
Keyword(s):  
Traffic Congestion ◽  
Road Network ◽  
Road Networks ◽  
Point Of View ◽  
Traffic Dynamics ◽  
Demand And Supply ◽  
The Road ◽  
On The Road ◽  
Detailed Mathematical Analysis ◽  
Control Traffic

In this paper, the analyses of traffic evolution on the road network of a roundabout having three entrances and three exiting legs are conducted from macroscopic point of view. The road networks of roundabouts are modeled as a merging and diverging types 1×2 and 2×1 junctions. To study traffic evolution at junction, two cases have been considered, namely, demand and supply limited cases. In each case, detailed mathematical analysis and numerical tests have been presented. The analysis in the case of demand limited showed that rarefaction wave fills the portion of the road network in time. In the contrary, in supply limited case, traffic congestion occurs at merging junctions and shock wave propagating back results in reducing the performance of a roundabout to control traffic dynamics. Also, we illustrate density and flux profiles versus space discretization at different time steps via numerical simulation with the help of Godunov scheme.

scholarly journals Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Shichao Sun ◽  
Zhengyu Duan ◽  
Dongyuan Yang
Keyword(s):  
Large Scale ◽  
Time Window ◽  
Transportation Networks ◽  
Optimal Path ◽  
Time Dependent ◽  
Travel Times ◽  
Urban Network ◽  
Routing Problem ◽  
On The Road ◽  
Stochastic Time

This paper addressed the vehicle routing problem (VRP) in large-scale urban transportation networks with stochastic time-dependent (STD) travel times. The subproblem which is how to find the optimal path connecting any pair of customer nodes in a STD network was solved through a robust approach without requiring the probability distributions of link travel times. Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP), and algorithms for such TD-VRPs can also be introduced to obtain the solution. Numerical experiments were conducted to address STD-VRPTW of practical sizes on a real world urban network, demonstrated here on the road network of Shenzhen, China. The stochastic time-dependent link travel times of the network were calibrated by historical floating car data. A route construction algorithm was applied to solve the STD problem in 4 delivery scenarios efficiently. The computational results showed that the proposed STD-VRPTW model can improve the level of customer service by satisfying the time-window constraint under any circumstances. The improvement can be very significant especially for large-scale network delivery tasks with no more increase in cost and environmental impacts.

The Integrative Time-Dependent Modeling of the Reliability and Failure of the Causes of Drivers’ Error Leading to Road Accidents

2013 ◽  
Vol 4 (1) ◽  
pp. 25-39 ◽  
Author(s):  
Khashayar Hojjati-Emami ◽  
Balbir S. Dhillon ◽  
Kouroush Jenab
Keyword(s):  
Human Error ◽  
Time Dependent ◽  
Failure Rates ◽  
Road Accidents ◽  
Road Transportation ◽  
The Road ◽  
Representational Model ◽  
On The Road ◽  
The Moment ◽  
Dependent Failure

Nowadays, the human error is usually identified as the conclusive cause of investigations in road accidents. The human although is the person in control of vehicle until the moment of crash but it has to be understood that the human is under continued impact by various factors including road environment, vehicle and human’s state, abilities and conduct. The current advances in design of vehicle and roads have been intended to provide drivers with extra comfort with less physical and mental efforts, whereas the fatigue imposed on driver is just being transformed from over-load fatigue to under-load fatigue and boredom. A representational model to illustrate the relationships between design and condition of vehicle and road as well as driver’s condition and state on fatigue and the human error leading to accidents has been developed. Thereafter, the stochastic mathematical models based on time-dependent failure rates were developed to make prediction on the road transportation reliability and failure probabilities due to each cause (vehicle, road environment, human due to fatigue, and human due to non fatigue factors). Furthermore, the supportive assessment methodology and models to assess and predict the failure rates of driver due to each category of causes were developed and proposed.

Self-Driving Robotic Cars

2021 ◽  
pp. 599-631
Author(s):  
Jelena L. Pisarov ◽  
Gyula Mester
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicle ◽  
Closed Circuit ◽  
Small Scale ◽  
Traffic Patterns ◽  
Complex Environments ◽  
The Road ◽  
Traffic Jams ◽  
Simulation Techniques ◽  
On The Road

Even the behavior of a single driver can have a dramatic impact on hundreds of cars, making it more difficult to manage traffic. While the attempts to analyze and correct the traffic patterns that lead to congestion began as early in the 1930s, it wasn't until recently that scientists developed simulation techniques and advanced algorithms to create more realistic visualizations of traffic flow. In experiments conducted by Alexandre Bayen and the Liao-Cho, which included several dozen cars in a small-scale closed circuit, a single autonomous vehicle could eliminate traffic jams by moderating the speed of every car on the road. In larger simulations, the research showed that once their number rises to 5-10% of all cars in the traffic, they can manage localized traffic even in complex environments, such as merging multiple lanes of traffic into two or navigating extremely busy sections.

Self-Driving Robotic Cars

2022 ◽  
pp. 969-1001
Author(s):  
Jelena L. Pisarov ◽  
Gyula Mester
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicle ◽  
Closed Circuit ◽  
Small Scale ◽  
Traffic Patterns ◽  
Complex Environments ◽  
The Road ◽  
Traffic Jams ◽  
Simulation Techniques ◽  
On The Road

Even the behavior of a single driver can have a dramatic impact on hundreds of cars, making it more difficult to manage traffic. While the attempts to analyze and correct the traffic patterns that lead to congestion began as early in the 1930s, it wasn't until recently that scientists developed simulation techniques and advanced algorithms to create more realistic visualizations of traffic flow. In experiments conducted by Alexandre Bayen and the Liao-Cho, which included several dozen cars in a small-scale closed circuit, a single autonomous vehicle could eliminate traffic jams by moderating the speed of every car on the road. In larger simulations, the research showed that once their number rises to 5-10% of all cars in the traffic, they can manage localized traffic even in complex environments, such as merging multiple lanes of traffic into two or navigating extremely busy sections.

Using GIS in Disaster Response Operations

2021 ◽  
pp. 176-199
Author(s):  
Zafer Yilmaz
Keyword(s):  
Disaster Response ◽  
Linear Models ◽  
Economic Losses ◽  
Travel Times ◽  
The Road ◽  
On The Road ◽  
Logistic Support ◽  
Earthquake Effects ◽  
Road Segments

Earthquakes come first compared with other disasters concerning casualties and economic losses. Thousands of people need heath and logistic support after earthquakes. Therefore, legal authorities focus on finding best locations for logistics depots to reach the demand points as soon as possible. Linear and non-linear models are used to find depot locations. In this study, alternatively, geographic information system (GIS) is used to find the optimal locations of depots among candidates. A new model is introduced which cover the earthquake effects while estimating the vehicle speeds on road segments. Optimal locations of depots are found both with and without including the earthquake effects on vehicle speeds and travel times on the road segments in order to compare the results. A case study is applied for Bahçelievler town in Istanbul. Three depot locations are found among 21 candidate locations (facilities) for 62 estimated demand points. The results show that the depot locations are not necessarily the same whether the earthquake effects on travel times are included or not.

scholarly journals CAPACITY DISTRIBUTIONS IN SPATIAL STOCHASTIC MODELS FOR TELECOMMUNICATION NETWORKS

2011 ◽  
Vol 28 (3) ◽  
pp. 155 ◽  
Author(s):  
Florian Voss ◽  
Catherine Gloaguen ◽  
Volker Schmidt
Keyword(s):  
Stochastic Models ◽  
Numerical Study ◽  
Shortest Paths ◽  
Telecommunication Networks ◽  
Cable System ◽  
The Road ◽  
Cox Processes ◽  
Spatial Stochastic Model ◽  
On The Road ◽  
Typical Length

We consider the stochastic subscriber line model as a spatial stochastic model for telecommunication networks and we are interested in the evaluation of the required capacities at different locations of the network in order to provide, in fine, an estimation of the cable system which has to be installed. In particular, we consider hierarchical telecommunication networks with higher–level components (HLC) and lower–level components (LLC) located on the road system underlying the network. The cable paths are modeled by shortest paths along the edge set of a stationary random tessellation, whereas both HLC and LLC are modeled by Cox processes concentrated on the edges of this tessellation. We then introduce the notion of capacity which depends on the length of some subtree on the edge set of the underlying tessellation. Moreover, we investigate estimators for the density and distribution function of the typical length of this subtree which can be computed based on Monte Carlo simulations of the typical serving zone. In a numerical study, the density of the typical subtree length is determined for different specific models.

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