Does a carbon tax affect the feasibility of Arctic shipping?

The Arctic route has huge potential for shipping between Europe and Northeast Asia with significant savings in transit time and distance. However, GHG emissions from shipping would harm the environment of Arctic area. Potential Market Based Measures of GHG emission reduction (such as carbon tax) are under consideration but they may affect the economic viability of Northern Sea Route (NSR) for containerships. This paper investigates the economic viability of NSR against Suez Canal Route (SCR) under 2 proposed carbon tax schemes (fixed vs. progressive). Three different fuel oil types (Heavy Fuel Oil, Light Fuel Oil, Liquified Natural Gas) are used as main bunker fuel for the calculation of economic feasibility. Our result reveals that when there is no carbon tax on NSR nor SCR, or both routes are under a carbon tax scheme, no matter fixed or progressive, NSR is more economically viable, regardless of fuel type choice. When only NSR is under a carbon tax scheme, the viability depends on specific carbon tax scheme and fuel choice, but for the majority of containership sizes, NSR has lower unit cost. The result also suggests that for a given route, a progressive scheme in preferable than a fixed one and LNG would be an appealing fuel with lower unit cost.     

Specification of the cross-nested logit model with sampling of alternatives for route choice models

We present an operational estimation procedure for the estimation of route choice multivariate extreme value (MEV) models based on sampling of alternatives. The procedure builds on the state-of-the-art literature, and in particular on recent methodological developments proposed by Flötteröd and Bierlaire (2013) and Guevara and Ben-Akiva (2013b). Case studies on both synthetic data and a real network demonstrate that the new method is valid and practical.     

长昆客运专线(湖南段)综合选线设计研究

长昆客运专线湖南段是国家"四纵四横"客运专线沪昆客专的一部分,沿线所经区域环境敏感点多,地形、地质困难,岩溶、地下水系发育,选线设计方案复杂。通过对长昆客运专线湖南段选线设计中一些典型选线案例进行分析及施工运营验证,线路方案设计满足规划要求,同时防范重大工程风险、满足环保要求,做到工程经济合理。提出选线设计应符合通道内路网规划、功能定位,遵循环保选线、地质选线、规划选线、经济选线等综合选线理念,重视施工运营安全。     

An impact analysis of traffic image information system on driver travel choice

A driver is one of the main components in a transportation system that influences the effectiveness of any active demand management (ADM) strategies. As such, the understanding on driver behavior and their travel choice is crucial to ensure the successful implementation of ADM strategies in alleviating traffic congestion, especially in city centres. This study aims to investigate the impact of traffic information dissemination via traffic images on driver travel choice and decision. A relationship of driver travel choice with respect to their perceived congestion level is developed by an integrated framework of genetic algorithm–fuzzy logic, being a new attempt in driver behavior modeling. Results show that drivers consider changing their travel choice when the perceived congestion level is medium, in which changing departure time and diverting to alternative roads are two popular choices. If traffic congestion escalates further, drivers are likely to cancel their trip. Shifting to public transport system is the least likely choice for drivers in an auto-dependent city. These findings are important and useful to engineers as they are required to fully understand driver (user) sensitivity to traffic conditions so that relevant active travel demand management strategies could be implemented successfully. In addition, engineers could use the relationships established in this study to predict drivers’ response under various traffic conditions when carrying out modeling and impact studies.     

A discounted recursive logit model for dynamic gridlock network analysis

Emerging sensing technologies such as probe vehicles equipped with Global Positioning System (GPS) devices on board provide us real-time vehicle trajectories. They are helpful for the understanding of the cases that are significant but difficult to observe because of the infrequency, such as gridlock networks. On the premise of this type of emerging technology, this paper propose a sequential route choice model that describes route choice behavior, both in ordinary networks, where drivers acquire spatial knowledge of networks through their experiences, and in extraordinary networks, which are situations that drivers rarely experience, and applicable to real-time traffic simulations. In extraordinary networks, drivers do not have any experience or appropriate information. In such a context, drivers have little spatial knowledge of networks and choose routes based on dynamic decision making, which is sequential and somewhat forward-looking. In order to model these decision-making dynamics, we propose a discounted recursive logit model, which is a sequential route choice model with the discount factor of expected future utility. Through illustrative examples, we show that the discount factor reflects drivers’ decision-making dynamics, and myopic decisions can confound the network congestion level. We also estimate the parameters of the proposed model using a probe taxis’ trajectory data collected on March 4, 2011 and on March 11, 2011, when the Great East Japan Earthquake occurred in the Tokyo Metropolitan area. The results show that the discount factor has a lower value in gridlock networks than in ordinary networks.     

峡谷地形隔震效应及减灾选线对策

在困难山区,峡谷是铁路、公路常利用的交通廊道,但峡谷往往也是震害集中的地段,目前有关峡谷地形对地震波传播特性的影响研究甚少。基于波动理论,分析得出峡谷切割深度越深,对Rayleigh波高频成分的屏蔽频率范围越广;峡谷越陡,对散射波的强度削减效应越显著;从而地震波的强度在峡谷两侧具有显著的差异,即在地震波入射一侧的振动强度大于另一侧。上述结论得到了芦山地震震害现象以及苏克拉峡谷地震记录仪观测资料的检验,可为减灾选线设计提供理论依据。     

基于GIS-AHP方法的危险品物流运输选线研究

文章针对地理信息系统（GIS）和层次分析法（AHP）在目标数据量化及综合评价方面的优点,提出了危险品运输选线GIS-AHP方法,阐述了GIS-AHP方法的具体实施步骤,并结合某跨地区危险品道路运输实例进行了选线分析。结果表明,该方法能显著提高危险品道路运输的风险综合评价水平,且所选路线科学、合理。     

An eco-routing model considering microscopic vehicle operating conditions

The eco-routing problem concerned in this paper addresses the optimal route choice of eco-drivers who aim to meet an emission standard imposed by regulators, while trying to find the path with the minimum total operating cost, which consists of both travel time and fuel costs. The paper first develops fuel consumption and greenhouse gas emissions estimation models that link emission rates to a vehicle’s physical and operational properties. Unlike most studies in the literature, the emission model developed in this paper retains as many microscopic characteristics as feasible in the context of route planning. Specifically, it is able to approximate the impacts of major acceleration events associated with link changes and intersection idling, and yet does not require detailed acceleration data as inputs. The proposed eco-routing model also explicitly captures delays at intersections and the emissions associated with them. Using a simple probabilistic model, the impacts of different turning movements on eco-routing are incorporated. The proposed model is formulated as a constrained shortest path problem and solved by off-the-shelf solvers. Numerical experiments confirm that vehicle characteristics, especially weight and engine displacement, may influence eco-routing. The results also suggest that ignoring the effects of turning movements and acceleration may lead to sub-optimal routes for eco-drivers.     

Controlling road congestion via a low-complexity route reservation approach

This work introduces a novel route reservation architecture to manage road traffic within an urban area. The developed routing architecture decomposes the road infrastructure into slots in the spatial and temporal domains and for every vehicle, it makes the appropriate route reservations to avoid traffic congestion while minimizing the traveling time. Under this architecture, any road segment is admissible to be traversed only during time-slots when the accumulated reservations do not exceed its critical density. A road-side unit keeps track of all reservations which are subsequently used to solve the routing problem for each vehicle. Through this routing mechanism, vehicles can either be delayed at their origin or are routed through longer but non-congested routes such that their traveling time is minimized. In this work, the proposed architecture is presented and the resulting route reservation problem is mathematically formulated. Through a complexity analysis of the routing problem, it is shown that for certain cases, the problem reduces to an NP-complete problem. A heuristic solution to the problem is also proposed and is used to conduct realistic simulations across a particular region of the San Francisco area, demonstrating the promising gains of the proposed solution to alleviate traffic congestion.     

A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance

The paper proposes a multi-class control scheme for freeway traffic networks. This control scheme combines two control strategies, i.e. ramp metering and route guidance, in order to reduce the total time spent and the total emissions in a balanced way. In particular, the ramp metering and route guidance controllers are feedback predictive controllers, i.e. they compute the control actions not only on the basis of the measured system state, but also on the basis of the prediction of the system evolution, in terms of traffic conditions and traffic emissions. Another important feature of the controllers is that they have a multi-class nature: different classes of vehicles are considered and specific control actions are computed for each class. Since the controllers are based on a set of parameters that need to be tuned, the overall control framework also includes a module to properly determine the gains of the controllers. The simulation analysis reported in the paper shows the effectiveness of the proposed control framework and, in particular, the possibility of implementing control policies that are specific for each vehicle type.