Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.     

Validation of an extended discrete first-order model with variable speed limits

This paper validates the prediction model embedded in a model predictive controller (MPC) of variable speed limits (VSLs). The MPC controller was designed based on an extended discrete first-order model with a triangular fundamental diagram. In our previous work, the extended discrete first-order model was designed to reproduce the capacity drop and the propagation of jam waves, and it was validated with reasonable accuracy without the presence of VSLs. As VSLs influence traffic dynamics, the dynamics including VSLs needs to be validated, before it can be applied as a prediction model in MPC. For conceptual illustrations, we use two synthetic examples to show how the model reproduces the key mechanisms of VSLs that are applied by existing VSL control approaches. Furthermore, the model is calibrated by use of real traffic data from Dutch freeway A12, where the field test of a speed limit control algorithm (SPECIALIST) was conducted. In the calibration, the original model is extended by using a quadrangular fundamental diagram which keeps the linear feature of the model and represents traffic states at the under-critical branch more accurately. The resulting model is validated using various traffic data sets. The accuracy of the model is compared with a second-order traffic flow model. The performance of two models is comparable: both models reproduce accurate results matching with real data. Flow errors of the calibration and validation are around 10%. The extended discrete first-order model-based MPC controller has been demonstrated to resolve freeway jam waves efficiently by synthetic cases. It has a higher computation speed comparing to the second-order model-based MPC.     

爆破排淤填石法处理软基的设计与应用

爆破排淤填石法是利用爆破法达到软土置换目的的一种新的换填方法．近年来在港口工程处理软基中得到越来越广泛的应用,而且处理软基的厚度也越来越大。结合几项具体工程的设计,介绍结构设计中一些参数的选取以及质量检测方法等。     

港口门机司机绩效考核系统设计

针对某港口企业下属门机队现行绩效考核和管理相对落后的状况提出了有效的改进策略。基于门机作业实时记录,采用Microsoft SQL2005数据库、VC＋＋6．0和水晶报表技术设计了一套司机作业绩效考核软件,实现了对现场采集数据的转换和存储,并结合作业票数据考核门机司机的作业量,自动生成每月的机械队员工工资报表,同时,港口企业通过司机绩效考核软件完成对生产数据的科学、有效的管理。     

广西交通科技资源共享平台建设探讨

文章针对广西交通科技项目管理系统现状,分析了建设交通科技资源共享平台的必要性,阐述了交通科技资源共享平台建设的关键技术、创新点及主要内容,指出该共享平台的建设可改善和提高交通运输科技项目质量及监管水平。     

深入实施科技强交战略 为发展现代交通运输业提供支撑和保障

全国交通运输科技大会全面回顾总结了＂十一五＂交通运输科技工作,研究分析交通运输科技发展面临的新形势、新要求,部署＂十二五＂科技工作。文章基于交通运输科技大会的部署与要求,介绍了＂十一五＂交通运输科技工作取得的成绩与经验,分析了＂十二五＂交通运输科技发展的总体思路和重点任务,提出了做好＂十二五＂交通运输科技工作的具体要求。     

编制国省道改建项目可研报告的几点心得体会

通过对近年来山东省国省道改建可研报告编制工作中常见问题及设计对策的总结,用工作实例提出了解决问题的思路和方法。     

城市轨道交通设施安全智能监测预警系统设计

城市轨道交通线网规模和客运量的日益增加对城市轨道交通安全运营的要求越来越高,城市轨道交通设施安全智能监测是轨道交通系统安全运营的重要保障.设计了一种城市轨道交通设施安全智能监测预警系统,实现轨道交通设施监测数据采集、数据传输、数据保存、智能预警功能,对系统功能及布局提出具体的设计要求,同时根据安全性的需求划分预警级别.     

深圳轨道交通投融资模式回顾及再创新探索

深圳轨道交通已进入高质量发展时期,政府的财政压力加大,需要再次创新投融资模式.深圳轨道交通前四期经历了一元、多元化的投融资创新,五期将实施轨道与土地一体化发展的思路,而上盖物业开发是轨道交通投融资再创新的基石.基于深圳利用先行先试、引领示范政策的大好机遇,提出两种创新的投融资模式:"轨道交通PPP项目+上盖物业规划+浮...     

动车组位置追踪系统常见问题影响分析及解决方法

从动车组位置追踪系统的系统原理、系统接口等方面出发,分析了系统日常应用过程中常见问题的影响,并给出了相应的解决方法,为动车段/所位置追踪系统的设计、应用和维护提供了积极的思路。