scholarly journals Time-varying K factor of the mm-Wave vehicular channel: Velocity, vibrations and the road quality influence

2017 ◽  
Author(s):  
Jiri Blumenstein ◽  
Ales Prokes ◽  
Josef Vychodil ◽  
Martin Pospisil ◽  
Tomas Mikulasek
Keyword(s):  
Time Varying ◽  
The Road ◽  
K Factor ◽  
Channel Velocity

Spatiotemporal Object Database Approach to Dynamic Segmentation

2003 ◽  
Vol 1836 (1) ◽  
pp. 118-125 ◽  
Author(s):  
Bo Huang ◽  
Li Yao
Keyword(s):  
Query Language ◽  
Time Varying ◽  
Data Types ◽  
The Road ◽  
Dynamic Segmentation ◽  
Management Group ◽  
Object Database ◽  
On The Road ◽  
Temporal Dimensions ◽  
Spatiotemporal Queries

Dynamic segmentation is viewed as one of the most important functions of geographic information systems for transportation applications. Although the road network and associated events (e.g., pavement material, traffic volume, incidents) can be referenced to both space and time, the spatial and temporal dimensions have not been well integrated. Modeling space-varying, time-varying, and space-time-varying events in dynamic segmentation by using an object database approach that is in line with the Object Database Management Group standard is explored. A mechanism called parametric polymorphism is used to lift conventional data types to spatial, temporal, and spatiotemporal types for maintaining knowledge about events that could change spatially, temporally, and spatiotemporally along linear features. An associated object query language, DS-OQL, was designed to support the formulation of spatial, temporal, and spatiotemporal queries on the road and event information.

Optimal Toll Design Problem in Dynamic Traffic Networks with Joint Route and Departure Time Choice

2005 ◽  
Vol 1923 (1) ◽  
pp. 61-72 ◽  
Author(s):  
Dusica Joksimovic ◽  
Michiel C. J. Bliemer ◽  
Piet H. L. Bovy
Keyword(s):  
Travel Behavior ◽  
Dynamic Pricing ◽  
Design Problem ◽  
Road Pricing ◽  
Control Measures ◽  
Time Varying ◽  
Dynamic Traffic ◽  
The Road ◽  
Departure Time ◽  
Departure Time Choice

Road pricing is one of the market-based traffic control measures that can influence travel behavior to alleviate congestion on roads. This paper addresses the effects of uniform (constant, fixed) and time-varying (step) tolls on the travel behavior of users on the road network. The problem of determining optimal prices in a dynamic traffic network is considered by applying second-best tolling scenarios imposing tolls only to a subset of links on the network and considering elastic demand. The optimal toll design problem is formulated as a bilevel optimization problem with the road authority (on the upper level) setting the tolls and the travelers (on the lower level) who respond by changing their travel decisions (route and departure time choice). To formulate the optimal toll design problem, the so-called mathematical program with equilibrium constraints (MPEC) formulation was used, considering the dynamic nature of traffic flows on the one hand and dynamic pricing on the other. Until now, the MPEC formulation has been applied in static cases only. The model structure comprises three interrelated levels: (a) dynamic network loading, (b) route choice and departure time choice, and (c) road pricing level. For solving the optimal toll design problem in dynamic networks, a simple search algorithm is used to determine the optimal toll pattern leading to optimization of the objective function of the road authority subject to dynamic traffic assignment constraints. Nevertheless, uniform and time-varying pricing is analyzed, and a small hypothetical network is considered.

Low-carbon VRP for cold chain logistics considering real-time traffic conditions in the road network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qinyang Bai ◽  
Xaioqin Yin ◽  
Ming K. Lim ◽  
Chenchen Dong
Keyword(s):  
Road Network ◽  
Cold Chain ◽  
Time Varying ◽  
Low Carbon ◽  
Content Type ◽  
Distribution Costs ◽  
The Road ◽  
Traffic Conditions ◽  
Real Time Traffic ◽  
Distribution Cost

PurposeThis paper studies low-carbon vehicle routing problem (VRP) for cold chain logistics with the consideration of the complexity of the road network and the time-varying traffic conditions, and then a low-carbon cold chain logistics routing optimization model was proposed. The purpose of this paper is to minimize the carbon emission and distribution cost, which includes vehicle operation cost, product freshness cost, quality loss cost, penalty cost and transportation cost.Design/methodology/approachThis study proposed a mathematical optimization model, considering the distribution cost and carbon emission. The improved Nondominated Sorting Genetic Algorithm II algorithm was used to solve the model to obtain the Pareto frontal solution set.FindingsThe result of this study showed that this model can more accurately assess distribution costs and carbon emissions than those do not take real-time traffic conditions in the actual road network into account and provided guidance for cold chain logistics companies to choose a distribution strategy and for the government to develop a carbon tax.Research limitations/implicationsThere are some limitations in the proposed model. This study assumes that there are only one distribution and a single type of vehicle.Originality/valueExisting research on low-carbon VRP for cold chain logistics ignores the complexity of the road network and the time-varying traffic conditions, resulting in nonmeaningful planned distribution routes and furthermore low carbon cannot be discussed. This study takes the complexity of the road network and the time-varying traffic conditions into account, describing the distribution costs and carbon emissions accurately and providing the necessary prerequisites for achieving low carbon.

Optimal Trajectory Generation for Intelligent Vehicles in Complex Traffic Based on Iteration Convex Optimization

2021 ◽  
pp. 2159040
Author(s):  
Xiaoyu Zhang ◽  
Aihua Li
Keyword(s):  
Convex Optimization ◽  
Quadratic Programming ◽  
Trajectory Planning ◽  
Three Dimensional ◽  
Intelligent Vehicles ◽  
Feasible Region ◽  
Planning Problem ◽  
Time Varying ◽  
The Road ◽  
On The Road

Intelligent vehicles face considerable challenges in the complex traffic environment since they need to deal with various constraints and elements. This dissertation puts forward a novel trajectory planning framework for intelligent vehicles to generate safe and optimal driving trajectories. First, we design a spatiotemporal occupancy framework to deal with all kinds of elements in the complex driving environment based on the Frenét frame. This framework unifies various constraints on the road in the three-dimensional spatiotemporal representation and clearly describes the collision-free configuration space. Then we use the convex approximation method to construct a time-varying convex feasible region based on the above accurate temporal and spatial description. We formulate the trajectory planning problem as a standard quadratic programming formulation with collision-free and dynamics constraints. Finally, we apply the iterative convex optimization algorithm to solve the quadratic programming problem in the time-varying convex feasible region. Moreover, we design several typical experimental scenarios and have verified that the proposed method has good effectiveness and real-time.

scholarly journals Influence of differential with the limited gear ratio on the efficiency reflecting losses on wheel slip

2019 ◽  
Vol 135 ◽  
pp. 01092
Author(s):  
Andrey Efimov ◽  
Sergey Kireev ◽  
Marina Korchagina ◽  
Alexey Lebedev ◽  
Khaidar Kaderov
Keyword(s):  
Selection Criterion ◽  
Gear Ratio ◽  
Time Varying ◽  
Wheel Slip ◽  
Power Train ◽  
The Road ◽  
Two Factors ◽  
Stiffness And Damping ◽  
Vehicle Movement ◽  
Reduced Adherence

At vehicle movement, there are two factors that specify conflicting requirements for transfer box drive and axle drive. Let’s describe them: each wheel rotating at different speeds and reduced adherence of one or more wheels. The road conditions: the decrease in friction and kinematic disparity, acting often at the same time, present conflicting requirements to drive of the driving wheels. These factors tend to be of time-varying nature. The nature of the studied processes is transient; it will be influenced by the inertia, stiffness and damping properties of the vehicle power train parts. The efficiency reflecting losses on wheel slip is proposed as a uniform selection criterion of an interaxial drive. Based on comparison of dependence of this parameter on road conditions, higher efficiency of differential with limited gear ratio compared to simple differential and blocked drive is shown. The chosen approach on the basis of quantitative indices proves the efficiency of differential with the limited transfer ratio in comparison with other main types of the drive, such as differential and blocked.

scholarly journals Risk Analysis and Route Optimization of Dangerous Goods Transportation Based on the Empirical Path Set

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Haixing Wang ◽  
Qianqian Liang
Keyword(s):  
Risk Analysis ◽  
Path Selection ◽  
Route Optimization ◽  
Time Varying ◽  
Road Transportation ◽  
The Road ◽  
Dangerous Goods ◽  
Comprehensive Method ◽  
On The Road ◽  
Population And Environment

Based on the empirical path set generated from the track data of dangerous goods vehicles, we present a new method for the risk analysis and path optimization of dangerous goods transportation. First of all, by exploring the travel rules of dangerous goods transport vehicles hidden in the track data, combined with the path set generation algorithm, the method of determining the empirical path set of dangerous goods transport is studied. Secondly, based on the empirical path set, mainly considering the travel rules of vehicles and people on the road, as well as the distribution of population and environment-sensitive areas along the road, a dual objective path selection model is proposed to comprehensively measure the risk and cost of road transportation under time-varying conditions. On this basis, given the principle of avoiding high-risk transportation paths, a comprehensive method of integrating multiple algorithms is proposed to solve the model. Finally, taking a road network as an example, the practicability and effectiveness of the proposed method are verified. The method proposed takes both practicability and safety into account. Based on the experience path set, considering the time-varying characteristics, the decision-maker could choose the appropriate transportation path of dangerous goods according to different preferences, so as to better solve the problem of path selection for dangerous goods transportation.

Improved Floyd Route Mending Algorithm Based on Dynamic Travel Time Applied to the Estimation of Floating Car Origin-Destination Data

2013 ◽  
Vol 361-363 ◽  
pp. 2196-2200
Author(s):  
Hui Zhao
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Time Varying ◽  
Application Performance ◽  
The Road ◽  
Floating Car Data ◽  
Factors Influencing ◽  
The One ◽  
Corridor Network ◽  
Beijing China

The floating car data (FCD) is widely used to estimate the time-varying OD demands in recent years. The one of the most important factors influencing the application performance of FCD is the completeness of FCD route data. This paper is intended to develop Floyd route mending algorithm based on dynamic travel time for FCD. In this framework, the raw FCD and the processed FCD are used to identify the problem of data missing based on topological structure of the road network. Then, an approach is developed to mend route based on improved Floyd route mending algorithm based on the GIS map. The approach is designed in a way that takes full advantage of the dynamic characteristics of travel time and quick routes scan. The paper applies the proposed methodology to mend routes and derive OD demands of FCD for the Western 3rd Ring-Road corridor network in Beijing, China. It is shown from the statistical analysis that the approach is accurate and the OD demands of FCD can reflect the characteristics of OD demands of all vehicles in the road network.

Comparison of Second-Best and Third-Best Tolling Schemes on a Road Network

2005 ◽  
Vol 1932 (1) ◽  
pp. 89-96 ◽  
Author(s):  
André De Palma ◽  
Moez Kilani ◽  
Robin Lindsey
Keyword(s):  
Road Network ◽  
Road Pricing ◽  
Time Varying ◽  
Dynamic Traffic ◽  
Flow Curves ◽  
Second Best ◽  
The Road ◽  
Demand Elasticities ◽  
Speed Flow ◽  
Extensive Information

Much of the road pricing literature has focused on deriving second-best optimal tolls when only parts of a network can be tolled or tolling is constrained in other ways. A drawback of second-best tolling is that it requires extensive information on speed–flow curves and demand elasticities throughout the network. Such information is often not readily available, and errors in estimating key parameters could result in tolls that are nonoptimal or even welfare reducing. The purpose of this paper is to explore a simpler alternative policy, dubbed “no-queue” tolling, whereby time-varying tolls are imposed selectively on a road network with the objective of eliminating queuing on the tolled links. No-queue tolling is an example of third-best pricing because the effects of the tolls on other links are disregarded. To explore the merits of no-queue tolling, a dynamic traffic simulator (METROPOLIS) was used to compute no-queue tolls for individual links and cordon rings on a laboratory network. For comparison, second-best flat and time-varying tolls were also computed on the same sets of links. Two results stood out. First, even without accounting for the likely computational and acceptability advantages of no-queue tolling, it appeared to dominate flat tolling and performed relatively well compared to step tolling. Second, the benefits from no-queue tolling exhibited approximately constant returns with respect to the number of links that are tolled. This suggests that no-queue tolling could fruitfully be selectively implemented now, rather than waiting a decade or more for comprehensive road pricing to become feasible.

scholarly journals The Data-Driven Pattern for Healthy Behaviors of Car Drivers Based on Daily Records of Traffic Count Data From 2018 To 2019 Near Airports. A Functional Data Analysis

2020 ◽  
Author(s):  
Mohammad Fayaz ◽  
Alireza Abadi ◽  
Soheila Khodakarim ◽  
Mohammadreza Hoseini ◽  
Alireza Razzaghi
Keyword(s):  
Data Analysis ◽  
Functional Data Analysis ◽  
Count Data ◽  
Functional Data ◽  
Data Driven ◽  
Time Varying ◽  
Traffic Demand ◽  
The Road ◽  
Hourly Data ◽  
Traffic Count

The road traffic injuries risk factors such as driving offenses and average speed are concerns for health organizations to reduce the number of injuries. Without any comprehensive view of each road, one cannot decide about the effective policy. In this manner, the data-driven policy will help to improve and assess the decisions. The count data near the road of two airports is surveyed for investigating the time-varying speed zones. The descriptive statistics, ANOVA, and functional data analysis were used. The hourly data of traffic counts for four different locations at the entrance of the two airports, international and domestics, were collected for one the year 2018 to 2019.The hourly pattern of driving offenses for each road was assessed and the to and from airport roads had different peaks (<0.05). The hour, weekdays, type of airport, direction and their interactions were statistically significant (<0.05) for the chance of driving offenses. The speed average during the day was statistically different (<0.5) by the number of different types of vehicles. The traffic count data is a great resource for decision making in safe driving subjects such as driving offenses. With functional data analysis, we can analyze them to get the most of the characteristics of this data. The airports are public places with high traffic demand in all countries that yields the different pattern of traffic transportation, therefore we extract the factors that affect the driving offenses. Finally, we conclude that conducting a time-varying speed zone near the airports seems vital.

Seeking to uncover biology's chemical roots

2019 ◽  
Vol 3 (5) ◽  
pp. 435-443 ◽  
Author(s):  
Addy Pross
Keyword(s):  
Environmental Changes ◽  
Biological Systems ◽  
Significant Development ◽  
The Road ◽  
Physical Chemical ◽  
Systems Chemistry ◽  
Biological World ◽  
Inanimate Matter ◽  
The Origin Of Life ◽  
Opening Up

Despite the considerable advances in molecular biology over the past several decades, the nature of the physical–chemical process by which inanimate matter become transformed into simplest life remains elusive. In this review, we describe recent advances in a relatively new area of chemistry, systems chemistry, which attempts to uncover the physical–chemical principles underlying that remarkable transformation. A significant development has been the discovery that within the space of chemical potentiality there exists a largely unexplored kinetic domain which could be termed dynamic kinetic chemistry. Our analysis suggests that all biological systems and associated sub-systems belong to this distinct domain, thereby facilitating the placement of biological systems within a coherent physical/chemical framework. That discovery offers new insights into the origin of life process, as well as opening the door toward the preparation of active materials able to self-heal, adapt to environmental changes, even communicate, mimicking what transpires routinely in the biological world. The road to simplest proto-life appears to be opening up.

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