Green vehicle technology to enhance the performance of a European port: A simulation model with a cost-benefit approach

In this paper, we study the impact of using a new intelligent vehicle technology on the performance and total cost of a European port, in comparison with existing vehicle systems like trucks. Intelligent autonomous vehicles (IAVs) are a new type of automated guided vehicles (AGVs) with better maneuverability and a special ability to pick up/drop off containers by themselves. To identify the most economical fleet size for each type of vehicle to satisfy the port’s performance target, and also to compare their impact on the performance/cost of container terminals, we developed a discrete-event simulation model to simulate all port activities in micro-level (low-level) details. We also developed a cost model to investigate the present values of using two types of vehicle, given the identified fleet size. Results of using the different types of vehicles are then compared based on the given performance measures such as the quay crane net moves per hour and average total discharging/loading time at berth. Besides successfully identifying the optimal fleet size for each type of vehicle, simulation results reveal two findings: first, even when not utilising their ability to pick up/drop off containers, the IAVs still have similar efficacy to regular trucks thanks to their better maneuverability. Second, enabling IAVs’ ability to pick up/drop off containers significantly improves the port performance. Given the best configuration and fleet size as identified by the simulation, we use the developed cost model to estimate the total cost needed for each type of vehicle to meet the performance target. Finally, we study the performance of the case study port with advanced real-time vehicle dispatching/scheduling and container placement strategies. This study reveals that the case study port can greatly benefit from upgrading its current vehicle dispatching/scheduling strategy to a more advanced one.     

Congestion-aware system optimal route choice for shared autonomous vehicles

We study the shared autonomous vehicle (SAV) routing problem while considering congestion. SAVs essentially provide a dial-a-ride service to travelers, but the large number of vehicles involved (tens of thousands of SAVs to replace personal vehicles) results in SAV routing causing significant congestion. We combine the dial-a-ride service constraints with the linear program for system optimal dynamic traffic assignment, resulting in a congestion-aware formulation of the SAV routing problem. Traffic flow is modeled through the link transmission model, an approximate solution to the kinematic wave theory of traffic flow. SAVs interact with travelers at origins and destinations. Due to the large number of vehicles involved, we use a continuous approximation of flow to formulate a linear program. Optimal solutions demonstrate that peak hour demand is likely to have greater waiting and in-vehicle travel times than off-peak demand due to congestion. SAV travel times were only slightly greater than system optimal personal vehicle route choice. In addition, solutions can determine the optimal fleet size to minimize congestion or maximize service.     

Evaluation of a model predictive control framework for motorway traffic involving conventional and automated vehicles

A Model Predictive Control (MPC) strategy for motorway traffic management, which takes into account both conventional control measures and control actions executed by vehicles equipped with Vehicle Automation and Communication Systems (VACS), is presented and evaluated using microscopic traffic simulation. A stretch of the motorway A20, which connects Rotterdam to Gouda in the Netherlands, is taken as a realistic test bed. In order to ensure the reliability of the application results, extensive speed and flow measurements, collected from the field, are used to calibrate the site’s microscopic traffic simulation model. The efficiency of the MPC framework, applied to this real sizable and complex network under realistic traffic conditions, is examined for different traffic conditions and different penetration rates of equipped vehicles. The adequacy of the control application when only VACS equipped vehicles are used as actuators, is also considered, and the related findings underline the significance of conventional control measures during a transition period or in case of increased future demand.     

Dynamic ride sharing using traditional taxis and shared autonomous taxis: A case study of NYC

This study analyzes the potential benefits and drawbacks of taxi sharing using agent-based modeling. New York City (NYC) taxis are examined as a case study to evaluate the advantages and disadvantages of ride sharing using both traditional taxis (with shifts) and shared autonomous taxis. Compared to existing studies analyzing ride sharing using NYC taxi data, our contributions are that (1) we proposed a model that incorporates individual heterogeneous preferences; (2) we compared traditional taxis to autonomous taxis; and (3) we examined the spatial change of service coverage due to ride sharing. Our results show that switching from traditional taxis to shared autonomous taxis can potentially reduce the fleet size by 59% while maintaining the service level and without significant increase in wait time for the riders. The benefit of ride sharing is significant with increased occupancy rate (from 1.2 to 3), decreased total travel distance (up to 55%), and reduced carbon emissions (up to 866 metric tonnes per day). Dynamic ride sharing, wich allows shared trips to be formed among many groups of riders, up to the taxi capacity, increases system flexibility. Constraining the sharing to be only between two groups limits the sharing participation to be at the 50–75% level. However, the reduced fleet from ride sharing and autonomous driving may cause taxis to focus on areas of higher demands and lower the service levels in the suburban regions of the city.     

Preferences for shared autonomous vehicles

Shared autonomous vehicles (SAVs) could provide inexpensive mobility on-demand services. In addition, the autonomous vehicle technology could facilitate the implementation of dynamic ride-sharing (DRS). The widespread adoption of SAVs could provide benefits to society, but also entail risks. For the design of effective policies aiming to realize the advantages of SAVs, a better understanding of how SAVs may be adopted is necessary. This article intends to advance future research about the travel behavior impacts of SAVs, by identifying the characteristics of users who are likely to adopt SAV services and by eliciting willingness to pay measures for service attributes. For this purpose, a stated choice survey was conducted and analyzed, using a mixed logit model. The results show that service attributes including travel cost, travel time and waiting time may be critical determinants of the use of SAVs and the acceptance of DRS. Differences in willingness to pay for service attributes indicate that SAVs with DRS and SAVs without DRS are perceived as two distinct mobility options. The results imply that the adoption of SAVs may differ across cohorts, whereby young individuals and individuals with multimodal travel patterns may be more likely to adopt SAVs. The methodological limitations of the study are also acknowledged. Despite a potential hypothetical bias, the results capture the directionality and relative importance of the attributes of interest.     

调度集中的体系结构与控制模式

调度集中是提高铁路运输效率、改善劳动条件,实现行车指挥自动化、遥控化的重要信号设备.介绍了调度集中技术的发展与控制模式的演变,调度集中体系结构与控制模式,调度集中控制模式与铁路运输组织管理模式.以揭示调度集中控制模式与体系结构的内在关系以及发展内涵.     

基于PSTN的远程分布式系统安全解决方案

针对分布式管理信息系统通过PSTN(公用电话交换网)互联时存在的带宽低、易受干扰和安全隐患等问题,结合现代密码技术,提出了一种基于自治系统(AutonomousSystem)和代理(Agent)技术的远程分布式安全应用方案。该方案采用RSA与DES相结合的加密和认证技术,并通过自治系统中代理的自动协作,有效解决了在PSTN下分布数据的同步及其完整性和机密性保护等问题。该方案已成功应用于分布式铁路建设物资管理系统中,运行效果良好。     

分布式卫星系统自主运行技术研究进展

随着微小卫星技术的不断发展,分布式卫星系统的概念应运而生。然而,由于分布式卫星系统本身的复杂性及其工作环境的动态不确定性,使得系统的测控与运行管理模式由传统的地面测控运营方式向智能化自主运行方式发展。从分布式卫星系统及其自主运行技术的研究进展上,重点讨论了分布式卫星系统自主运行的思想,综述国内外一些研究组织、学者的相关研究成果。最后探讨基于Multi-Agent分布式卫星系统自主运行未来所面临的技术挑战。     

水下直升机运动稳定性分析

文章分析一种新型超机动飞碟形的自主式潜水器—水下直升机的运动稳定性,以实现其在海底复杂的作业任务。采用AYASYS-CFX计算流体力学的仿真模拟技术,分析飞碟形的水下直升机在水平面的机动性和垂直面的运动稳定性等水动力关键技术问题。采用多种数值水池模拟的方法,包括直(斜)航运动和圆池旋臂运动等模拟方法,以计算水下直升机的水动力的稳定性导数、水动力(矩)、随攻角变化的压力中心和阻升比等。在设计航速1 kn的情况下,采用Routh线性水动力导数组成的运动稳定性数学模型,分析其水平及垂直面上的运动稳定性。计算结果说明,水下直升机在水平面上回转运动具有战术直径接近零的超机动能力,同时,在垂直面上具有优于传统鱼雷形潜水器的运动稳定性。     

无人走航式监测平台系统的构建

针对水质监测的需要,设计了一套无人走航式监测平台系统,硬件系统由无人走航式监测平台和岸基站组成,软件系统由无线通讯软件和控制软件组成。无人走航式监测平台可以实现自主导航、自主采样并检测、自诊断、将在线检测信息实时传回岸基站控制中心。岸基站可以对不能在线分析的数据如COD、BOD、营养盐等数据进行实验分析。测试证明无人走航式监测平台可以实现预期功能。