Optimal Eco-Approach Control With Traffic Prediction for Connected Vehicles

2018 ◽  
Author(s):  
Yunli Shao ◽  
Zongxuan Sun
Keyword(s):  
Robust Optimization ◽  
Optimization Problem ◽  
Traffic Prediction ◽  
Flow Density ◽  
Optimization Approach ◽  
Connected Vehicle ◽  
State Variables ◽  
Unified Framework ◽  
The Road ◽  
On The Road

This work proposes a unified framework for the eco-approach application that integrates traffic prediction, vehicle optimization, and implementation. The eco-approach application is formulated as either a car-following optimization problem or a single vehicle optimization problem, depending on whether a preceding vehicle exists. The traffic prediction scheme anticipates future traffic conditions and describes the traffic dynamics on the road segment of interest using state variables: traffic flow, density, and speed. With the information enabled by connectivity, the traffic state estimation is updated using an observer. Uncertainties in the traffic prediction are considered using a robust optimization approach. The robust optimization problem is discretized and solved by an efficient nonlinear programming solver. The proposed eco-approach framework is implemented to a single lane single intersection scenario for 12, 8, 4, and 1 connected vehicle scenarios. The fuel benefits vary from 11.0% to 6.7% as the penetration rates of connectivity decrease. The performance is satisfactory compared to the 12.0% fuel benefits with perfection traffic prediction.

Robust Optimization of an Accelerometer Considering Fabrication Errors

2009 ◽  
Vol 628-629 ◽  
pp. 353-356 ◽  
Author(s):  
Guang Jun Liu ◽  
Tao Jiang ◽  
An Lin Wang
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Sensitivity Analysis ◽  
Robust Optimization ◽  
Optimization Problem ◽  
Design Space ◽  
Optimization Approach ◽  
Objective Functions ◽  
Micro Fabrication ◽  
Fabrication Errors

A robust optimization approach of an accelerometer is presented to minimize the effect of variations from micro fabrication. The sensitivity analysis technology is employed to reduce design space and to find the key parameters that have greatest influence on the accelerometer. And then, the constraint conditions and objective functions for robust optimization and the corresponding mathematical model are presented. The optimization problem is solved by the Multiple-island Genetic Algorithm and the results show that an accelerometer with better performance is obtained.

Data dissemination for green-VANETs communication: an opportunistic optimization approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chandramohan D. ◽  
Ankur Dumka ◽  
Dhilipkumar V. ◽  
Jayakumar Loganathan
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Data Dissemination ◽  
Optimization Approach ◽  
Content Type ◽  
The Road ◽  
The People ◽  
Road Condition ◽  
Open Issue ◽  
On The Road

Purpose This paper aims to predict the traffic and helps to find a solution. Unpredictable traffic leads more vehicles on the road. The result of which is one of the factors that aggravate traffic congestion. Traffic congestion occurs when the available transport resources are less when compared to the number of vehicles that share the resource. As the number of vehicles increases the resources become scarce and congestion is more. Design/methodology/approach The population of the urban areas keeps increasing as the people move toward the cities in search of jobs and a better lifestyle. This leads to an increase in the number of vehicles on the road. However, the transport network, which is accessible to the citizens is less when compared to their demand. Findings The demand for resources is higher than the actual capacity of the roads and the streets. There are some circumstances, which will aggravate traffic congestion. The circumstances can be the road condition (pot holes and road repair), accidents and some natural calamities. Originality/value There is a lot of research being done to predict the traffic and model it to find a solution, which will make the condition better. However, still, it is an open issue. The accuracy of the predictions done is less.

MODELING TRAFFIC FLUCTUATIONS AND CONGESTION ON A ROAD NETWORK

2015 ◽  
Vol 18 (03n04) ◽  
pp. 1550009 ◽  
Author(s):  
E. ANDREOTTI ◽  
A. BAZZANI ◽  
S. RAMBALDI ◽  
N. GUGLIELMI ◽  
P. FREGUGLIA
Keyword(s):  
Numerical Simulations ◽  
Road Network ◽  
Statistical Physics ◽  
Transition Probabilities ◽  
Traffic Load ◽  
Flow Density ◽  
The Road ◽  
Random Transition ◽  
Emilia Romagna Region ◽  
On The Road

Statistical mechanics points out as fluctuations have a relevant role for systems near critical points. We study the effect of traffic fluctuations and the transition to congested states for a stochastic dynamical model of traffic on a road network. The model simulates a finite population that moves from one road to another according to random transition probabilities. In such a way, we mimic the traffic fluctuations due to the granular feature of traffic and the dynamics at the crossing points. Then the amplitude of traffic flow fluctuations is proportional to the average flow as suggested by empirical observations. Assuming a parabolic shaped flow-density relation, there exists an unstable critical point for the road dynamics and the system can perform a phase transition to a congested state, where some roads reach their maximal capacity. We apply a statistical physics approach to study the onset congestion and we characterize analytically the relation between the fluctuations amplitude and the appearance of congested nodes. We verify the results by means of numerical simulations on a Manhattan-like road network. Moreover we point out the existence of oscillating regimes, where traffic oscillations back propagate on the road network, whose onset depend sensitively from the traffic fluctuations and that have a strong influence on the hysteresis cycles of the systems when the traffic load is modulated. The comparison between the numerical simulations and the empirical traffic data recorded by an inductive-loop traffic detector system (MTS system) on the county roads of the Emilia Romagna region in Italy is shortly discussed.

scholarly journals Conic reformulations for Kullback-Leibler divergence constrained distributionally robust optimization and applications

2021 ◽  
Vol 11 (2) ◽  
pp. 139-151
Author(s):  
Burak Kocuk
Keyword(s):  
Robust Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Empirical Distribution ◽  
Computational Study ◽  
Facility Location Problem ◽  
Optimization Approach ◽  
Distributionally Robust Optimization ◽  
Leibler Divergence ◽  
Distributionally Robust

In this paper, we consider a Kullback-Leibler divergence constrained distributionally robust optimization model. This model considers an ambiguity set that consists of all distributions whose Kullback-Leibler divergence to an empirical distribution is bounded. Utilizing the fact that this divergence measure has an exponential cone representation, we obtain the robust counterpart of the Kullback-Leibler divergence constrained distributionally robust optimization problem as a dual exponential cone constrained program under mild assumptions on the underlying optimization problem. The resulting conic reformulation of the original optimization problem can be directly solved by a commercial conic programming solver. We specialize our generic formulation to two classical optimization problems, namely, the Newsvendor Problem and the Uncapacitated Facility Location Problem. Our computational study in an out-of-sample analysis shows that the solutions obtained via the distributionally robust optimization approach yield significantly better performance in terms of the dispersion of the cost realizations while the central tendency deteriorates only slightly compared to the solutions obtained by stochastic programming.

scholarly journals Warning System Using Multicast Transmission for Pedestrian and Pedal-Cyclist Safety Against the Electric-Powered Driving Means in CVCN Network

2018 ◽  
Vol 7 (3.33) ◽  
pp. 139
Author(s):  
Bachyun Kim ◽  
Yoseop Woo ◽  
Iksoo Kim
Keyword(s):  
New Technology ◽  
Warning System ◽  
Artificial Noise ◽  
Connected Vehicle ◽  
Multicast Transmission ◽  
Vehicle Accidents ◽  
The Road ◽  
Vehicle Communication ◽  
Safety Warning ◽  
On The Road

This paper deals with a warning system for the safety of pedestrians/pedal-cyclists against electric-powered driving means including hybrid/PHEV/EV/FCEV and electric wheel on minor roads. These roads are a subset of connected-vehicle communication network(CVCN). The fatalities of pedestrians/pedal-cyclists declined recently compared to the early 2000s, but fatality rate of vehicle accidents is increasing. Clearly, this phenomenon will continue because of the increasing number of virtually silent hybrid/PHEV/EV/FCEV and electric wheels on the road.The hybrid/PHEV/EV/FCEV such as green electric-powered ones that can reduce environmental pollution are much more dangerous than traditional vehicles to pedestrians/pedal-cyclists on minor roads. The main risk factor of the electric-powered vehicles is that they are very quiet on the road because of the use of electric motor instead of engine. Thus, the safety warning system that can notify pedestrians/pedal-cyclists the dangerous approaches of vehicles from their behind have to be provided on minor roads.The proposed framework for safety warning system using multicast informs pedestrians/pedal-cyclists through smartphone when electric powered driving means are closing from their behind on minor roads. This is a new technology that uses vibration or sound of smartphone instead of artificial noise generation which is equipped to the electric powered driving means recently.  

MODELS OF TRAFFIC FLOW DYNAMICS ON HIGHWAYS

2021 ◽  
Vol 116 (1) ◽  
pp. 236-241
Author(s):  
Diana Assankhankyzy Otegen
Keyword(s):  
Transport Infrastructure ◽  
Macroscopic Model ◽  
Flow Density ◽  
Traffic Flows ◽  
Macroscopic Models ◽  
The Road ◽  
Advantages And Disadvantages ◽  
Space And Time ◽  
Microscopic Models ◽  
On The Road

The paper is an analytical review of the currently existing methods of traffic flows modeling. The movement of vehicles on the road can be modeled in different ways. Mathematical models as tools that allow us to study complex processes in the real world, including transport infrastructure, without capital expenditures, are a popular tool for solving many problems in various spheres of the national economy. There are several approaches to mathematical modeling of traffic flows. In microscopic models, the law of motion of each car is set, depending on its current position, speed, characteristics of the movement of neighboring cars, and other factors. Microscopic models, in turn, can be divided into models that are continuous in space and time, and into models that are discrete in space and time, the so-called cellular automata. In macroscopic models, the transport flow is considered as a fluid flow with special properties. The equations of the macroscopic model establish the relationship between the flow, density, speed of movement, possibly acceleration, and so on. Macroscopic models can also be continuous or discrete. In continuous models, the change in the state of a road section without branches and intersections is usually described by partial differential equations. Modeling traffic flows is necessary because active experiments in the existing transport network are fraught with unpredictable consequences, and in many cases are not feasible at all. The work presents a description and analysis of the models, and of their advantages and disadvantages.

Optimal Lane Management in Heterogeneous Traffic Network

2019 ◽  
Author(s):  
Pouria Karimi Shahri ◽  
Shubhankar Chintamani Shindgikar ◽  
Baisravan HomChaudhuri ◽  
Amir H. Ghasemi
Keyword(s):  
Autonomous Vehicles ◽  
Optimization Problem ◽  
Optimal Allocation ◽  
Penetration Rate ◽  
Heterogeneous Traffic ◽  
Design Parameters ◽  
Optimization Approach ◽  
Traffic Network ◽  
The Road ◽  
Search Optimization

Abstract This paper aims to determine an optimal allocation of autonomous vehicles in a multi-lane heterogeneous traffic network where the road is shared between autonomous and human-driven vehicles. The fundamental traffic diagram for such heterogeneous traffic networks is developed wherein the capacity of the road is determined as a function of the penetration rate and the headways of autonomous and human-driven vehicles. In this paper, we define two cost functions to maximize the throughput of the network and minimize the variation between flow rates. To solve the proposed optimization problem, an exhaustive search optimization approach is performed. Several numerical examples are presented to highlight the different influence of different design parameters on the allocation of autonomous vehicles.

Community Colleges: Vital Partners on the Road to Diversity

ASHA Leader ◽  
2006 ◽  
Vol 11 (5) ◽  
pp. 14-17 ◽  
Author(s):  
Shelly S. Chabon ◽  
Ruth E. Cain
Keyword(s):  
Community Colleges ◽  
The Road ◽  
On The Road
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