Multi‐objective highway alignment optimization using a genetic algorithm

The available highway alignment optimization algorithms use the total cost as the objective function. This is a single objective optimization process. In this process, travel‐time, vehicle operation accident earthwork land acquisition and pavement construction costs are the basic components of the total cost. This single objective highway alignment optimization process has limited capability in handling the cost components separately. Moreover, this process cannot yield a set of alternative solutions from a single run. This paper presents a multi‐objective approach to overcome these shortcomings. Some of the cost components of highway alignments are conflicting in nature. Minimizing some of them will yield a straighter alignment; whereas, minimizing others would make the alignment circuitous. Therefore, the goal of the multiobjective optimization approach is to handle the trade‐off amongst the highway alignment design objectives and present a set of near optimal solutions. The highway alignment objectives, i.e., cost functions, are not continuous in nature. Hence, a special genetic algorithm based multi‐objective optimization algorithm is suggested The proposed methodology is demonstrated via a case study at the end.     

Sociocultural Effects of a Market-Based Fishery Management Program in the Florida Keys

Spiny lobster (Panulirus argus) represents one of the most lucrative fisheries in the State of Florida, and a majority of the catch is landed in the Florida Keys. Over the past three decades, the industry grew significantly, and by the end of the 1980s, state fishery managers agreed that the fishery was overextended. In 1991, the Florida Legislature passed the Spiny Lobster Trap Certificate Program (LTC), created to stabilize the industry by reducing the total number of traps while allowing fishers to transfer trap certificates in a market-based system akin to individual transferable quotas. Data from a survey study suggest that a majority of the respondents are dissatisfied with the LTC, which they view as transitory and unsustainable. The fishers' negative views are motivated by sociocultural changes in the fishing community. Managers need to consider modifications to the LTC and other such marketbased programs to minimize sociocultural impacts and retain small-scale fisher participation in such fisheries.     

Performance indicators for public transit connectivity in multi-modal transportation networks

Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.     

Activity based travel demand models as a tool for evaluating sustainable transportation policies

India is in the course of an economic transition. The economic growth nurtured the life in the cities and cities have become a major livelihood destination for everyone. This migration of people contributed to the increased urbanization of Indian cities. The booming economy fostered the well-being and shaped the lifestyle of people in such a way that the dependency on private vehicle has become an unavoidable affair. Along with population growth, the increased vehicle ownership gave rise to overall spurt in travel demand. But the supply side lagged behind the demand adding to many of the transport related externalities such as accidents, congestion, pollution, inequity etc. The importance of sustainability is understood in the current urban transport scenario leading to the development and promotion of sustainable transport polices. The core agenda of these polices is to target the travel behavior of people and change the way they travel by creating a different travel environment. However, the impacts of many such policies are either unknown or complex. Hence, before adopting and implementing such policies, it is important for the decision makers to be aware of the impacts of them. The role of travel demand models comes here as they predict the future travel demand under different policy scenarios. This paper reviews the ability of travel demand models applied in India in analyzing the sustainable transport policies. The study found that the conventional model system in India, which is trip based four step aggregate methodology, is inadequate in analyzing the sustainable transport policies. A review of alternative approach, known as activity based travel demand modeling found that they are capable of handling such policies better than conventional models and are assistive to the decision makers in arriving at right mix of polices specific to the situations. Since there is no operational activity based travel demand model system developed in India, the study at the end envisaged a conceptual framework of an integrated activity based travel demand model based on the requirements identified from the review. This can potentially replace the existing travel demand models and can be used for planning applications once the modification & validation have been done according to the existing activity-travel behavior of individuals.     

Quantification of surrogate safety measure to predict severity of road crashes at median openings

Traffic safety assessment is an integral part of transportation engineering. In a developing country like India, it is observed that in every four second, one person gets injured in road crashes. Moreover, at median openings which are usually uncontrolled in India, the severity of road crashes increase many fold. This is due to the fact that neither lane discipline nor priority rule is followed at the median openings. Conventionally, road crash data reports were used to study and analyze traffic safety. However, the drawback of this traditional method is that a lot of accidents need to be recorded for analysis and to draw any conclusions and take necessary corrective measures. In developing countries like India, available accident data are based on reports submitted by the police department of respective state governments. The accuracy of these accident data details is highly questionable. Therefore, in the recent times surrogate traffic safety measures are being used to analyze traffic safety. Various surrogate traffic measures like Deceleration Time (DT), Time to Collision (TTC), Post Encroachment Time (PET), etc. are being used to examine road safety. These values are based on the temporal and spatial proximity between road-users during possible conflict situation. Among all the traffic safety measures, PET is regarded as the most reliable and most commonly used indicator. Therefore, in this study, PET across different traffic volume levels at median opening area is calculated. A critical safe ratio has been introduced to better analyze the traffic safety at median opening based on minimum stopping sight distance (SSD) as per IRC: 66–1976 and speed to PET ratio. Finally clustering technique has been used to define various severity indices for probable road crashes at median opening area. For this study, data has been collected from different median openings located on six-lane divided urban roads.     

Analysis of epimetamorphic rock slopes using soft computing

This article adopts three soft computing techniques including support vector machine （SVM）, least square support vector machine （LSSVM） and relevance vector machine （RVM） for prediction of status of epimetemorphic rock slope. The input variables of SVM, LSSVM and RVM are bulk density, height, inclination, cohesion and internal friction angle. There are 53 datasets which have been used to develop the SVM, LSSVM and RVM models. The developed SVM, LSSVM and RVM give equations for prediction of status of epimetemorphic rock slope. The performance of SVM, LSSVM and RVM is 100%. A comparative study has been presented between the developed SVM, LSSVM and RVM. The results confirm that the developed SVM, LSSVM and RVM are effective tools for prediction of status of epimetemorphic rock slope.     

运营盾构隧道结构安全评估方法研究

随着隧道运营时间的增加,隧道的结构安全问题日益突出,合理评价运营盾构隧道结构安全对保障隧道安全运营和科学养护具有重要意义。针对这一问题,根据隧道结构特点确定盾构隧道结构安全评价指标,通过理论分析确定评价指标的分级标准;确立运营盾构隧道结构安全评价指标体系;以模糊综合评价法、层次分析法为基础,综合考虑指标之间相关性和不可逆特性,建立修正的模糊综合评价法;利用该方法并结合现场检测数据,对实际隧道结构安全进行评价。修正后的模糊综合评价法,不仅能体现单一因素指标对评价结果影响的敏感性而且使综合评价结果更合理,能更科学地指导盾构隧道结构养护工作。     

Hydrodynamics study of a BCF mode bioinspired robotic-fish underwater vehicle using Lighthill’s slender body model

This paper investigates the hydrodynamic characteristics of the rectilinear motion of a robotic fish underwater vehicle. This 2-joint, 3-link multibody vehicle model is biologically inspired by a body caudal fin carangiform fish propulsion mechanism. Navier–Stokes equations are used to compute the unsteady flow fields generated due to the interaction between the vehicle and the surrounding incompressible and Newtonian fluid (water) environment. The NACA 0014 airfoil aerodynamic profile has been designed to boost the swimming efficiency by reducing drag as the vehicle undergoes an undulatory/oscillatory motion. Using the Lighthill slender body model, a traveling wave mathematical function is defined to undulate the robotic fish posterior (caudal) region while the motion tracking is carried out by dynamic meshing technique. The results obtained show that though the net lift force approaches to zero, the net thrust or negative drag coefficient maintains a finite value dependent on kinematic parameters like tail beat frequency (TBF) and amplitude span (AS) at a given propulsive wavelength and the forward velocity of the vehicle. The results reveal the effects of TBF and AS on the coefficient of drag friction and the thrust force. Drag coefficients obtained from the simulations are compared and validated with the experimental results. The hydrodynamic results are found to be similar to the kinematic study results and suggest that TBF and AS play the most effective roles in the bioinspired propulsion technique. Relation of these parameters with propelling thrust force and forward velocity is also in conjunction over a given range of TBF and AS values.     

Applicability of highway alignment optimization models

This paper presents an intelligent optimization tool that assists planners and designers in finding preferable highway alignments, connecting specified endpoints or zones. It integrates genetic algorithms with a geographic information system (GIS) for optimizing highway alignments and processes massive amounts of relevant data associated with highway design and alternative evaluation. To show the applicability of the proposed model to a real-world problem, two actual highway projects in the state of Maryland have been analyzed using the model. An extensive analysis of sensitivity to key model parameters is also conducted to describe the model capabilities. The analysis results show that the model can effectively optimize highway alignments in an area combining complex terrain and various types of natural and cultural land-use patterns, and provide detailed information of optimized alignments as a model output. It is also found that the alignments optimized by the model are quite similar to those obtained through conventional manual methods by a state agency, but the model can greatly reduce the time required for highway planning and design as well as produce lower cost solutions. Finally, the results confirm that all dominating and alignment-sensitive costs should be simultaneously evaluated in the alignment optimization process because many trade-off opportunities exist among those costs. The proposed model can greatly contribute to the productivity of highway planners as well as to the quality of the resulting infrastructure.