关于山区高速外业勘察中若干问题的探讨

近几年来,我国山区高速建设里程日益增加.因受复杂地形、地质条件的限制,山区高速的外业勘察具有其独有的关键技术难点,应在普通建设条件下的作业内容、作业方式的基础上,采取针对性的对策措施,确保外勘资料满足设计需求.     

Agent-based simulation framework for mixed traffic of cars,pedestrians and trams

In this paper, we report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support discussions about road management, signal control, and public transit. Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians. The car model, pedestrian model, and interaction rules implemented in the proposed framework were verified through simulations involving simple road environments. The resulting simulated values were in near agreement with the empirical data. We then used the proposed framework to assess the impact of a tramway extension plan for a real city. The simulation results showed that the impact of the proposed tramway on existing car traffic would not be serious, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that are satisfactory to both tram users and private car owners.     

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.     

Modeling real-time human mobility based on mobile phone and transportation data fusion

Even though a variety of human mobility models have been recently developed, models that can capture real-time human mobility of urban populations in a sustainable and economical manner are still lacking. Here, we propose a novel human mobility model that combines the advantages of mobile phone signaling data (i.e., comprehensive penetration in a population) and urban transportation data (i.e., continuous collection and high accuracy). Using the proposed human mobility model, travel demands during each 1-h time window were estimated for the city of Shenzhen, China. Significantly, the estimated travel demands not only preserved the distribution of travel demands, but also captured real-time bursts of mobility fluxes during large crowding events. Finally, based on the proposed human mobility model, a predictive model is deployed to predict crowd gatherings that usually cause severe traffic jams.     

Compliance with MARPOL Annex VI regulation 14 by ships in the Gulf of Guinea sub-region: Issues,challenges and opportunities

The negative environmental and health impacts association with high sulphur dioxide emissions from shipboard machineries have been raised by various stakeholders within the marine transportation sector. It is against this backdrop that the International Maritime Organisation under the MARPOL Annex VI regulation 14 has capped sulphur emission to 0.1% for Sulphur Emission Control Areas and 0.5% for the other shipping nations. However, ship owners in the Gulf of Guinea (GoG) sub-region are facing multitudes of challenges in meeting up with this new IMO regulation. This paper aims to identify the main barriers hampering effective compliance to this new regulation by ships operating in the GoG, rank the barriers, and then discuss the possible opportunities that may arise as a result of addressing the challenges. To identify the main barriers, experts with several years of experience in the maritime industry from Ghana and Cameroun were used while multi-criteria decision-making (MCDM) method combining analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) was employed to rank the barriers. Other methods such as fuzzy AHP (FAHP), rank-order centroid (ROC) and TOPSIS were combined to validate the result of the study. The findings indicate that lack of infrastructure, lack of comprehensive marine air pollution laws and high capital and operational costs of sulphur reduction solutions emerged as the top three ranked barriers. The findings of this study can be useful to ship owners and policy makers in dealing with the issues of marine air pollution.     

Large-scale dynamic transportation network simulation: A space-time-event parallel computing approach

This paper describes a computationally efficient parallel-computing framework for mesoscopic transportation simulation on large-scale networks. By introducing an overall data structure for mesoscopic dynamic transportation simulation, we discuss a set of implementation issues for enabling flexible parallel computing on a multi-core shared memory architecture. First, we embed an event-based simulation logic to implement a simplified kinematic wave model and reduce simulation overhead. Second, we present a space-time-event computing framework to decompose simulation steps to reduce communication overhead in parallel execution and an OpenMP-based space-time-processor implementation method that is used to automate task partition tasks. According to the spatial and temporal attributes, various types of simulation events are mapped to independent logical processes that can concurrently execute their procedures while maintaining good load balance. We propose a synchronous space-parallel simulation strategy to dynamically assign the logical processes to different threads. The proposed method is then applied to simulate large-scale, real-world networks to examine the computational efficiency under different numbers of CPU threads. Numerical experiments demonstrate that the implemented parallel computing algorithm can significantly improve the computational efficiency and it can reach up to a speedup of 10 on a workstation with 32 computing threads.     

Hardware-in-the-loop testbed for evaluating connected vehicle applications

Connected vehicle environment provides the groundwork of future road transportation. Researches in this area are gaining a lot of attention to improve not only traffic mobility and safety, but also vehicles’ fuel consumption and emissions. Energy optimization methods that combine traffic information are proposed, but actual testing in the field proves to be rather challenging largely due to safety and technical issues. In light of this, a Hardware-in-the-Loop-System (HiLS) testbed to evaluate the performance of connected vehicle applications is proposed. A laboratory powertrain research platform, which consists of a real engine, an engine-loading device (hydrostatic dynamometer) and a virtual powertrain model to represent a vehicle, is connected remotely to a microscopic traffic simulator (VISSIM). Vehicle dynamics and road conditions of a target vehicle in the VISSIM simulation are transmitted to the powertrain research platform through the internet, where the power demand can then be calculated. The engine then operates through an engine optimization procedure to minimize fuel consumption, while the dynamometer tracks the desired engine load based on the target vehicle information. Test results show fast data transfer at every 200 ms and good tracking of the optimized engine operating points and the desired vehicle speed. Actual fuel and emissions measurements, which otherwise could not be calculated precisely by fuel and emission maps in simulations, are achieved by the testbed. In addition, VISSIM simulation can be implemented remotely while connected to the powertrain research platform through the internet, allowing easy access to the laboratory setup.     

做好交通行业政务信息工作的研究

以山东省港航业政务信息工作为例，对如何做好交通行业政务信息工作进行研究。做好交通行业政务信息工作的关键是要根据交通行业的特点，构建交通政务信息网络；围绕港航行业管理内容，突出港航信息特色；同时也离不开领导的重视和支持。     

Studies on emergency evacuation management for maritime transportation

Marine transportation is a vital component of the world’s economy and transportation network. The number of people using passenger ships around the globe is increasing worldwide. Similar to other transportation systems, passenger safety is critical in maritime shipment. As emergency evacuation processes for ships are highly different from and more complicated than those for buildings and other vehicles, many researchers have published a vast range of documents related to this peculiar research area. However, there is a tangible lack of sufficient literature review studies that investigate marine emergency evacuation (MEE). That being the case, the potential of marine transportation and the effect of emergency evacuation operation on life safety have inspired the proposal of this study. This paper offers a review of the available literature on MEE modelling, analysis and planning during the period from 1973 to 2017 using a systematic approach. After reviewing relevant academic journals, peer-reviewed conference papers, and technical reports of agencies, relevant literature is analysed. In addition, the literature review is extended by means of proposing a framework methodology which considers different possible conditions and situations during MEE. Finally, insights for ship managers and policymakers are discussed and potential future research directions are identified.