Road characteristics and environment factors associated with motorcycle fatal crashes in Malaysia

This study aims to determine risk factors contributing to traffic crashes in 9,176 fatal cases involving motorcycle in Malaysia between 2010 and 2012. For this purpose, both multinomial and mixed models of motorcycle fatal crash outcome based on the number of vehicle involved are estimated. The corresponding model predicts the probability of three fatal crash outcomes: motorcycle single-vehicle fatal crash, motorcycle fatal crash involving another vehicle and motorcycle fatal crash involving two or more vehicles. Several road characteristic and environmental factors are considered including type of road in the hierarchy, location, road geometry, posted speed limit, road marking type, lighting, time of day and weather conditions during the fatal crash. The estimation results suggest that curve road sections, no road marking, smooth, rut and corrugation of road surface and wee hours, i.e. between 00.00 am to 6 am, increase the probability of motorcycle single-vehicle fatal crashes. As for the motorcycle fatal crashes involving multiple vehicles, factors such as expressway, primary and secondary roads, speed limit more than 70 km/h, roads with non-permissible marking, i.e. double lane line and daylight condition are found to cause an increase the probability of their occurrence. The estimation results also suggest that time of day (between 7 pm to 12 pm) has an increasing impact on the probability of motorcycle single-vehicle fatal crashes and motorcycle fatal crashes involving two or more vehicles. Whilst the multinomial logit model was found as more parsimonious, the mixed logit model is likely to capture the unobserved heterogeneity in fatal motorcycle crashes based on the number of vehicles involved due to the underreporting data with two random effect parameters including 70 km/h speed limit and double lane line road marking.     

Robustness of autonomous underwater vehicle control in variable working conditions

The performance of the control systems of autonomous underwater vehicles (AUVs) in the presence of parameter variations was studied. With an AUV working at different operating speeds and in different ocean environments, the physical parameters such as speed, hydrodynamic coefficients, or inertias may be perturbed from their nominal values. The vehicle control systems can be modeled as systems with parameter uncertainty. An existing robust control method, which uses the robustness properties of polynomials, was used for this system to calculate the permissible ranges of variation in the parameters. The method was applied to the Naval Postgraduate School AUV II and the results were verified by simulating the motion control of the vehicle under the influence of parameter perturbations.     

Normal and risky driving patterns identification in clear and rainy weather on freeway segments using vehicle kinematics trajectories and time series cluster analysis

Enhancing traffic safety on freeways is the main goal for all transportation agencies. However, to achieve this goal, many analysis protocols of network screening models need to be improved through considering human factors while analyzing traffic data. This paper introduces one on the new analysis protocol of identifying and discriminating between normal and risky driving in clear and rainy weather. The introduced analysis protocol will consider the effect of human factors on updating the networking screening process of identifying hotspots of crash risk. This paper employs the Second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) data to investigate the behavior of normal and risky driving under both rainy and clear weather conditions. Near-crash events on freeways, which were used as Surrogate Measure of Safety (SMoS) for crash risk, were identified based on the changes in vehicle kinematics, including speed, longitudinal and lateral acceleration and deceleration rates, and yaw rates. Through a trajectory-level data analysis, there were significant differences in driving patterns between rainy and clear weather conditions; factors that affected crash risk mainly included driver reaction and response time, their evasive maneuvers such as changes in acceleration rates and yaw rates, and lane-changing maneuvers. A cluster analysis method was employed to classify driving patterns into two clusters: normal and risky driving condition patterns, respectively. Statistical results showed that risky driving patterns started on average one second earlier in rainy weather conditions than in clear weather conditions. Furthermore, risky driving patterns extended in average three seconds in rainy weather conditions, while it was two seconds in clear weather conditions. The identification of these patterns is considered as a primary step towards an automated development that would distinguish between different driving patterns in a Connected Vehicle CV environment using Basic Safety Messages (BSM) and to enhance the network screening analysis for increased crash risk hotspots.     

Developing a chaotic pattern of dynamic Hazmat routing problem

The present paper proposes an iterative procedure based on chaos theory on dynamic risk definition to determine the best route for transporting hazardous materials (Hazmat). In the case of possible natural disasters, the safety of roads may be seriously affected. So the main objective of this paper is to simultaneously improve the travel time and risk to satisfy the local and national authorities in the transportation network. Based on the proposed procedure, four important risk components including accident information, population, environment, and infrastructure aspects have been presented under linguistic variables. Furthermore, the extent analysis method was utilized to convert them to crisp values. To apply the proposed procedure, a road network that consists of fifty nine nodes and eighty two-way edges with a pre-specified affected area has been considered. The results indicate that applying the dynamic risk is more appropriate than having a constant risk. The application of the proposed model indicates that, while chaotic variables depend on the initial conditions, the most frequent path will remain independent. The points that would help authorities to come to the better decision when they are dealing with Hazmat transportation route selection.     

Consideration of different travel strategies and choice set sizes in transit path choice modelling

Transportation - Path choice modelling is typically conducted by considering a subset of paths, not the universal set of all feasible paths as this is computationally challenging. This study...     

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通行能力预测是公路设施规划、设计与运营中的基础环节.本文基于埃及曼努菲亚省12条农村双车道路段数据,研究了公路线形等几何特征对通行能力的影响以及线形由切线变为平曲线时通行能力的损失.所选取的路段线形包括直线和随后的平曲线.同时,采集了各路段上车流量及速度数据,利用基于基本图的外推法研究流量和密度关系.路段上不同车型的车辆均转换为小客车当量.此外,针对不同情形（切线、平曲线及对应流量损失）,分别建立了最佳回归模型.结果表明,切线型道路的关键自变量是路宽、肩宽以及切线长;平曲线道路的关键变量是曲线半径和路宽.通行能力和几何特征关系最佳模型的自变量为曲线半径.本文的模型可用于分析评价农村双车道道路的通行能力,尤其是评价文中所研究路段的通行能力.     

应用GA,PSO,ACO算法进行水下自主运载器路径规划(英文)

In this paper,an underwater vehicle was modeled with six dimensional nonlinear equations of motion,controlled by DC motors in all degrees of freedom.Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem(NOCP).An energy performance index as a cost function,which should be minimized,was defined.The resulting problem was a two-point boundary value problem(TPBVP).A genetic algorithm(GA),particle swarm optimization(PSO),and ant colony optimization(ACO) algorithms were applied to solve the resulting TPBVP.Applying an Euler-Lagrange equation to the NOCP,a conjugate gradient penalty method was also adopted to solve the TPBVP.The problem of energetic environments,involving some energy sources,was discussed.Some near-optimal paths were found using a GA,PSO,and ACO algorithms.Finally,the problem of collision avoidance in an energetic environment was also taken into account.     

采用耦合有限元、边界元方法的矩形储液舱中液体晃荡数值仿真(英文)

Sloshing of liquid can increase the dynamic pressure on the storage sidewalls and bottom in tanker ships and LNG careers. Different geometric shapes were suggested for storage tank to minimize the sloshing pressure on tank perimeter. In this research, a numerical code was developed to model liquid sloshing in a rectangular partially filled tank. Assuming the fluid to be inviscid, Laplace equation and nonlinear free surface boundary conditions are solved using coupled FEM-BEM. The code performance for sloshing modeling is validated against available data. To minimize the sloshing pressure on tank perimeter, rectangular tanks with specific volumes and different aspect ratios were investigated and the best aspect ratios were suggested. The results showed that the rectangular tank with suggested aspect ratios, not only has a maximum surrounded tank volume to the constant available volume, but also reduces the sloshing pressure efficiently.     

Robust aspects in dependable filter design for alignment of a submarine inertial navigation system

The strapdown inertial navigation system (SINS) is able to provide continuous estimates of a vehicle??s velocity, position and attitude. As a rule, the SIMS component known as a high accuracy strapdown inertial measurement unit (SIMU) is an exceptionally expensive system. Less expensive SIMUs comprised of low cost sensors suffer from degraded performance, but this can be compensated for, in part, by addition of a velocity data recorder (VDR) to accompany the SINS. In this configuration, the need frequently arises to align the SINS of a submarine to in order to avoid a long run-up of the inertial system before a start command is issued. This in-motion alignment (IMA) can be accomplished by integrating SINS data with some external aiding source, such as the VDR, by using some form of measurement matching method. Accordingly, this paper demonstrates a consistent IMA scheme for a low-cost SIMU using a robust Kalman/ $ H_{\infty } $ filter structure. An error model of the SINS is derived in which the state vector includes attitude, velocity, position and sensor errors. Velocity information from the VDR is used as a measurement to the proposed filter. All significant equations concerning navigation are presented in conjunction with argument. Results show the advantages of the approach and emphasize diverse aspects of the SINS.