Impact of ICT access on personal activity space and greenhouse gas production: evidence from Quebec City, Canada

This paper presents an approach to investigating the impact of information and communication technologies (ICTs) on travel behaviour and its environmental effects. The paper focuses on the spatial dispersion of out-of-home activities and travel (activity space) and greenhouse gas emissions (GHGs) at the level of the individual. An original method, combining spatial analysis in a geographic information system with advanced regression techniques, is proposed to explore these potentially complex relationships in the case of access to mobile phones and the internet, while taking into account the influence of socio-economics and built environment factors. The proposed methodology is tested using a 7-day activity-based survey in Quebec City in 2003?C2004, a juncture of particular interest because these ICTs had recently crossed the threshold of 40?% (mobile phone) and 60?% (home-based internet) penetration at the time. The study period also largely pre-dates the era of mobile internet access. Among other results, socio-demographic factors were found to significantly affect both ICT access and travel out-comes. The built environment, represented by neighbourhood typologies, also played an important role. However, it was found that after controlling for the self-selection effect, built environment and socio-demographics, those who had a mobile phone available produced 30?% more GHGs during the observed week than those who did not. This higher level of GHG pro-duction was accompanied by a 12?% higher measure of activity dispersion. On the other hand, having internet access at home was associated with lower GHGs (?19?%) and lesser activity dispersion (?25?%). Possibly, mobile phones enable individuals to cover more space and produce more emissions, while the internet provides opportunities to stay at home or avoid motorized travel thus reducing emissions. The estimated effects of having a mobile phone were not only negative but also larger in magnitude from the environmental point of view than those of fixed internet access. However, the results of this study also suggest that access to mobile phones and internet may have substantial and compensatory effects at the individual level that are undetected when using model structures that do not take into account that unobserved factors may influence both ICT choices and travel outcomes.     

Spatiotemporal traffic forecasting: review and proposed directions

This paper systematically reviews studies that forecast short-term traffic conditions using spatial dependence between links. We extract and synthesise 130 research papers, considering two perspectives: (1) methodological framework and (2) methods for capturing spatial information. Spatial information boosts the accuracy of prediction, particularly in congested traffic regimes and for longer horizons. Machine learning methods, which have attracted more attention in recent years, outperform the naïve statistical methods such as historical average and exponential smoothing. However, there is no guarantee of superiority when machine learning methods are compared with advanced statistical methods such as spatiotemporal autoregressive integrated moving average. As for the spatial dependency detection, a large gulf exists between the realistic spatial dependence of traffic links on a real network and the studied networks as follows: (1) studies capture spatial dependency of either adjacent or distant upstream and downstream links with the study link, (2) the spatially relevant links are selected either by prejudgment or by correlation-coefficient analysis, and (3) studies develop forecasting methods in a corridor test sample, where all links are connected sequentially together, assume a similarity between the behaviour of both parallel and adjacent links, and overlook the competitive nature of traffic links.     

Effects of the ‘Belt and Road’ initiative on the wine import logistics of China

China’s Belt and Road (BR) initiative is expected to facilitate international trade between the countries involved. In this study, we review the special requirements of wine logistics and the market growth potential of wine consumption in China. A model minimizing generalized logistical costs is developed and applied to wine imports in China, so that the best candidate cities in which to locate transport gateways and distribution centers can be identified. Our analysis suggests that the most preferred gateways are Shanghai, Tianjin, Guangzhou, and Hong Kong, which all have similar delivery costs. In comparison, Beijing and Chongqing have much higher delivery costs, mainly because they do not have good access to marine transport and/or efficient domestic distribution networks. For long-distance intercontinental transport of large volumes of wine, marine shipping remains the only viable delivery mode. However, wine distribution within China extensively uses air, road, and water transport. Therefore, cities with excellent multi-modal transport services are better positioned to become wine logistics gateways. Our study also highlights the importance of value-added services and good government support, which are important factors that influence distribution costs and quality.     

Economic Outcomes for Harvesters under the West Coast Groundfish Trawl Catch Share Program: Have Goals and Objectives Been Met?

Abstract

The West Coast Groundfish Trawl Catch Share Program was designed to achieve multiple economic goals and objectives, including increasing net benefits, profitability, flexibility, and utilization of harvest allocations. In this article, we leverage seven years of comprehensive cost and earnings data to evaluate progress towards these goals with a focus on harvesters. Our assessment shows that five years post-implementation, net benefits to the nation have doubled, and indicators of productivity and profitability have increased. The fleet that targets Pacific whiting has seen the largest gains, due in part to increases in total allowable catch and the elimination of the race-to-fish. However, increased revenues have not been realized to the degree that was expected for harvesters targeting non-whiting groundfish, partly due to lower than predicted consolidation and relatively low quota utilization. Economic outcomes indicate that tradeoffs exist between certain objectives of the program, specifically between achieving full utilization and flexibility for harvesters. Results are discussed in the context of the design and evaluation of catch share programs for diverse, multispecies fisheries.     

Predicting queue variability to enable analysis of overload risk

ABSTRACT

Predicting the risk of traffic demands and delays exceeding critical limits at road junctions, airports, hospitals, etc., requires knowing how both mean and variance of queue size vary over time. Microscopic simulation can explore variability but is computationally demanding and gives only sample results. A computationally efficient approximation to the mean is used in many modelling tools, but only empirical extensions for variance in particular situations have been available. The paper derives theoretical formulae for time-dependent and equilibrium variance, believed to be novel and to apply generally to queues covered by the Pollaczek–Khinchin mean formula, and offering possible structural insights. These are applied in an extended approximation giving mutually consistent mean and variance estimates with improved accuracy. Tests on oversaturated peak demand cases are compared with Markov probabilistic simulation, demonstrating accuracy (R^2?>?0.99) for typical random, priority-like (M/M/1) and traffic-signal-like (M/D/1) queues. Implications for risk analysis, planning and policy are considered.     

Development of railway station choice models to improve the representation of station catchments in rail demand models

ABSTRACT

This paper describes the development of railway station choice models suitable for defining probabilistic station catchments. These catchments can then be incorporated into the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins and destinations from incomplete address information and to automatically validate reported trips. A bespoke trip planner was used to derive mode-specific station access variables and train leg measures. The results from a number of multinomial logit and random parameter (mixed) logit models are presented and their predictive performance assessed. The models were found to have substantially superior predictive accuracy compared to the base model (which assumes the nearest station has a probability of one), indicating that their incorporation into passenger demand forecasting methods has the potential to significantly improve model predictive performance.     

Expertise in decision-making for large infrastructure projects: from UK trunk roads to High Speed Rail 2

At the decision-making stage, a large-scale infrastructure project is essentially a broad concept, and this means the expert analyses will differ from each other and become contested over time, leading to the emergence of rival narratives. It is only where there is a limited range of expert analyses that the bases for decision-making will remain relatively clear-cut. Over time the contested nature of expertise can significantly inhibit the construction of effective narratives, either for or against the project, and also make decision-making more complex and problematic. Decision makers may also seek greater clarification through the construction of narratives that rise above these disputed areas of expertise, and the scientific evidence becomes less important. This paper examines the changing nature of contested expertise through a comparative analysis of political decision-making between UK trunk roads policy and the case of High Speed Rail 2, through the framework of epistemic communities.     

Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data

We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object may have passed between, given known origin and destination points. This paper utilizes a new form of TGDE to investigate taxicab GPS traces over a specified time horizon with position ‘gaps’. To this end, we propose a new extension to the TGDE framework, TGDE-C, which is used to determine the cumulative TGDE values for a group of GPS traces, at a given location. These metrics are applied to multiple taxis and allow for time of day analysis. Additionally, we combine these new extensions with existing TGDE metrics that allow us to determine how accessible individual or groups of vehicles are to urban opportunities.     

Numerical Simulation of Advanced Geological Forecasting Based on Multi- Source Seismic Interferometry北大核心CSCD

For existing advanced geological forecasting, the forecast distance is short and the test frequency is high, increasing test and construction risks. Since various methods have different requirements for the test environ-ment, preparation work can be tedious and result in a long construction time thereby affecting normal construction.A new advanced geological forecast technique based on multi-source seismic interferometry for tunnels is proposed.This technique uses the blast at one end of tunnel as a centrum and receives the signal at the other end of the tun-nel, therefore allowing advanced geological forecasting of the unexcavated tunnel part by relative processing and im-aging. A numerical simulation of this kind of geological forecasting using the finite difference method to simulate two kinds of unfavorable geological bodies (karst and a fault) predicted them accurately and verified the effective-ness and accuracy of this geological forecasting method. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

Back-Calculation of Ground Stress Field and Rockburst Analysis for Wunvfeng Tunnel北大核心CSCD

Studying the in-situ stress distribution at a tunnel site is very important to determine surrounding rock characteristics, the engineering design and the construction scheme. By using the multiple linear regression method based on the least square algorithm, the initial geostress field is analyzed and the corresponding regression coefficients are obtained. The ground stress obtained from the proposed back analysis is reasonable and can meet the demands of the engineering applications. From the rockburst risk level distribution diagram, it is speculated that the Wunvfeng tunnel is in the high filed stress area. Field monitoring should be strengthened and emergency plans should be made to cope with the rockburst risks during the construction process. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.