Analytical and grid-free solutions to the Lighthill-Whitham-Richards traffic flow model

In this article, we propose a computational method for solving the Lighthill-Whitham-Richards (LWR) partial differential equation (PDE) semi-analytically for arbitrary piecewise-constant initial and boundary conditions, and for arbitrary concave fundamental diagrams. With these assumptions, we show that the solution to the LWR PDE at any location and time can be computed exactly and semi-analytically for a very low computational cost using the cumulative number of vehicles formulation of the problem. We implement the proposed computational method on a representative traffic flow scenario to illustrate the exactness of the analytical solution. We also show that the proposed scheme can handle more complex scenarios including traffic lights or moving bottlenecks. The computational cost of the method is very favorable, and is compared with existing algorithms. A toolbox implementation available for public download is briefly described, and posted at http://traffic.berkeley.edu/project/downloads/lwrsolver.     

Capacity investment model for airport facilities under demand uncertainty

This paper addresses strategic airport facility planning under demand uncertainty. Existing studies are improved by (1) allowing capacity contraction and (2) adopting more flexible delay functions. A mixed‐integer nonlinear program, which incorporates scale economies in construction, time value of money, nonlinear congestion effect, and other factors, is proposed for optimizing the capacity expansion/contraction decisions over time for multiple airport components. The stochastic problem is converted into its deterministic equivalent because the number of demand scenarios considered is finite. A discrete approximation technique is used to remove the nonlinearities. Numerical studies are presented to demonstrate the capability of the proposed model and the computational efficiency of the solution method. The “Flaw of Averages” due to faulty decisions based on the average future condition is illustrated, and trade‐offs among various costs are discussed in the numerical analyses. Copyright © 2016 John Wiley & Sons, Ltd.     

Connection design for two-floating beam system for minimum hydroelastic response

This paper is concerned with the connection design for a two-floating beam system for minimum hydroelastic response. The frequency domain approach is used for the hydroelastic analysis. The fluid is modelled as an ideal fluid, and the floating beams are modelled by the Euler–Bernoulli beam theory. The boundary element method (BEM) and the finite element method (FEM) are applied to solve the governing equation of the fluid motion and the beam equation of motion, respectively. The study aims to investigate the optimum location and rotational stiffness of the connection for the two-floating beam system with the view to minimize the compliance. The study also investigates the effects of relative beam stiffnesses on the hydroelastic response of the two-floating beam system.     

Probability distributions of wave run-up on a TLP model

Wave run-up on multi-column compliant and rigid platforms both on the weather-side and beneath the platform deck is a complex wave–structure interaction problem. Predictions based upon higher order hydrodynamic design codes have been improved our understanding of this phenomena but have not appreciably reduced the reliance on model tests and statistical analyses. In this study a three parameter distribution model is developed based upon the inclusion of linear, second-order, and mean contributions to the wave run-up utilizing the method of L-moments. Explicit expressions are derived relating the L-moments and the input from experimental data. The sample L-moments are developed from a linear combination of ordered sequence of the data and consequently the high order L-moments, i.e. L-skewness and L-kurtosis, are less biased than the corresponding ordinary moments. The L-moment definitions of the variance, skewness and kurtosis are numerically compared with values obtained using the more standard definitions for these parameters. Rigid hull measurements are compared with the compliant hull configuration for a mini-TLP model. The sea-states investigated include the relatively benign sea conditions off of West Africa and the more extreme sea environments of Gulf of Mexico.     

Smooth motion control of the adaptive cruise control system by a virtual lead vehicle

The adaptive cruise control system maintains the appropriate distance to the lead vehicle when the lead vehicle exists and maintains the desired speed when no lead vehicle is detected. A virtual lead vehicle scheme is introduced to make the switching between the speed control algorithm and the distance control algorithm unnecessary and simplify the structure of the control system. The speed and the position of the virtual vehicle can be decided by the control system according to the current situation. Smoother responses are achieved by the virtual lead vehicle scheme compared to the conventional mode switching scheme. This method is also shown to provide a good reaction for when a lead vehicle cuts in or out. A linear quadratic controller with variable weights is suggested to control the virtual lead vehicle. This scheme shows improved performance in terms of passenger comfort and fuel efficiency of the host vehicle.     

Expanding transmission capacity of can systems using dual communication channels with kalman prediction

The controller area network (CAN) protocol is widely used for in-vehicle network (IVN) systems, and many automotive companies also use the CAN in chassis network systems. However, the increasing number of electronic control units (ECUs) dictated by the need for more intelligent and fuel-efficient functions requires an IVN system with a greater transmission capacity and less network delay. Automotive companies have tried several approaches such as segmenting CAN systems and developing time-triggered protocols. This paper presents a practical method for increasing the transmission capacity and reducing the network delay in CAN systems using dual communication channels with a traffic-balancing algorithm based on Kalman prediction to forecast the traffic on each channel and allocate frames to the one that is most appropriate. An experimental testbed using commercial microcontrollers with two or more CAN protocol controllers was used to demonstrate the feasibility of the Kalman traffic-balancing algorithm. Experimental results show that the traffic-balancing CAN system with Kalman prediction reduced the transmission delay of all priority messages compared to that of a simple method, such as a channel-switching CAN, without sacrificing the performance for high-priority messages.     

Cooling performance evaluation of height-downsized front end module for pedestrian protection

The front end module (FEM) needs enough space from hood to absorb the energy from any pedestrian collision. The FEM with downsized cooling module for pedestrian protection is important to reduce the severity of pedestrian injury. When a vehicle collision happens, the FEM with downsized cooling module is required to reduce the risk of injury to the upper legs of adults and the heads of children. In this study, the performance of cooling module to cool the engine was investigated under 25% height reduction. The heat dissipation and pressure drop characteristics have been experimentally studied with the variation of coolant flow rate, air inlet velocity and A/C operation (on/off) for the downsized cooling module. The results indicated that the cooling performance was about 94% level compared to that of the conventional cooling module. Therefore, we concluded that the cooling module had a good performance, and expected that the cooling module could meet the same cooling performance as conventional cooling module through optimization of components efficiency. This paper also deals with the development of FEM with downsized cooling module for the cooling performance level in vehicles. In the test of front end module??s heat dissipation performance, the prototype presented about 15% decrease under the conditions of all the vehicle speeds than that of conventional one.     

LOW-COST HIGH PERFORMANCE CLUSTER OF WORK-STATIONS BASED ON DYNAMIC LOAD BALANCING FOR PARALLEL DEPTH-FIRST SEARCH(DFS)

IntroductionTraditionally,supercomputers have been builtwith high performance processors,which use tech-niques to execute as many computations concur-rently as possible.This machine employs a numberof arithmetic units,and sufficient hardware to al-low them to be fed with data and instructions attheir peak rate. Supercomputers built as parallelprocessors have also contained special shared mem-ory or message passing hardware as an integralpart of the machines design. This special hard-ware,in co…     

Linear Quadratic Gaussian Control of a Quarter-Car Suspension

This paper presents a method for designing linear multivariable controllers in the frequency-domain for an intelligent controlled suspension system for a quarter-car model. The design methodology uses singular value inequalities and optimal control theory. The vehicle system is augmented with additional dynamics in the form of an integrator to affect the loop shapes of the system. The measurements are assumed to be obtained in a noisy state, and the optimal control gain and the Kalman filter gain are derived using system dynamics and noise statistics. A combination of singular value analysis, eigenvalue analysis, time response, and power spectral densities of random response is used to describe the performance of the active suspension systems.     

Drowsy behavior detection based on driving information

Drowsy behavior is more likely to occur in sleep-deprived drivers. Individuals’ drowsy behavior detection technology should be developed to prevent drowsiness related crashes. Driving information such as acceleration, steering angle and velocity, and physiological signals of drivers such as electroencephalogram (EEG), and eye tracking are adopted in present drowsy behavior detection technologies. However, it is difficult to measure physiological signal, and eye tracking requires complex experiment equipment. As a result, driving information is adopted for drowsy driving detection. In order to achieve this purpose, driving experiment is performed for obtaining driving information through driving simulator. Moreover, this paper investigates effects of using different input parameter combinations, which is consisted of lateral acceleration, longitudinal acceleration, and steering angles with different time window sizes (i.e. 4 s, 10 s, 20 s, 30 s, 60 s), on drowsy driving detection using random forest algorithm. 20 s-size datasets using parameter combination of accelerations in lateral and longitudinal directions, compared to the other combination cases of driving information such as steering angles combined with lateral and longitudinal acceleration, steering angles only, longitudinal acceleration only, and lateral acceleration only, is considered the most effective information for drivers’ drowsy behavior detection. Moreover, comparing to ANN algorithm, RF algorithm performs better on processing complex input data for drowsy behavior detection. The results, which reveal high accuracy 84.8 % on drowsy driving behavior detection, can be applied on condition of operating real vehicles.