公路网规划环境影响评价内容、程序和方法体系研究

在总结研究目前国内已有公路网规划环境影响评价工作的基础上,根据规划环境评价的目标要求和公路网规划的实际,提出了包括内容、程序和方法等的公路网规划环境影响评价体系,提高现有公路网规划环境评价能力和未来公路网规划环境评价质量。     

Validation of a schedule‐based capacity restraint transit assignment model for a large‐scale network

This paper describes the application of a capacity restraint trip assignment algorithm to a real, large‐scale transit network and the validation of the results. Unlike the conventional frequency‐based approach, the network formulation of the proposed model is dynamic and schedule‐based. Transit vehicles are assumed to operate to a set of pre‐determined schedules. Passengers are assumed to select paths based on a generalized cost function including in‐vehicle and out‐of‐vehicle time and line change penalty. The time‐varying passenger demand is loaded onto the network by a time increment simulation method, which ensures that the capacity restraint of each vehicle during passenger boarding is strictly observed. The optimal‐path and path‐loading algorithms are applied iteratively by the method of successive averages until the network converges to the predictive dynamic user equilibrium. The Hong Kong Mass Transit Railway network is used to validate the model results. The potential applications of the model are also discussed.     

Measuring production and consumption efficiencies using the slack‐based measure network data envelopment analysis approach: the case of low‐cost carriers

One of the most important outcomes of the deregulation of air transportation policy is the emergence of low‐cost carriers (LCCs) around the world. Although LCC airlines have been in operation for more than 30 years, not every LCC is successful. In order to reduce the inefficiencies of LCCs, this paper measures the performance of LCCs by using slack‐based measure network data envelopment analysis. This model combines both the production process with input orientation and the consumption process with output orientation into a unified model. Furthermore, envelopment map analysis LCCs are performed to determine the reasons for the LCCs' inefficiency and how improvements can be made. A sample of 16 low‐cost airlines from Europe, the USA, and Asia were selected for operational performance analysis. The results show that the main reason for easyJet's, US Airways', and Virgin Blue's inefficiency is production inefficiency, so these LCCs should reduce their input quantities to increase efficiency. Jet2, Aer Lingus, and JetBlue were, by contrast, found to be consumption inefficient; these LCCs should increase their output quantities in order to enhance performance. Copyright © 2012 John Wiley & Sons, Ltd.     

Transport network criticality metrics: a comparative analysis and a guideline for selection

ABSTRACT

Transport network criticality analysis aims at ranking transport infrastructure elements based on their contribution to the performance of the overall infrastructure network. Despite the wide variety of transport network criticality metrics, little guidance is available on selecting metrics that are fit for the specific purpose of a study. To address this gap, this study reviews, evaluates and compares seventeen criticality metrics. First, we conceptually evaluate these metrics in terms of the functionality of the transport system that the metrics try to represent (either maintaining connectivity, reducing travel cost, or improving accessibility), the underlying ethical principles (either utilitarianism or egalitarianism), and the spatial aggregation considered by the metrics (either network-wide or localised). Next, we empirically compare the metrics by calculating them for eight transport networks. We define the empirical similarity between two metrics as the degree to which they yield similar rankings of infrastructure elements. Pairs of metrics that have high empirical similarity highlight the same set of transport infrastructure elements as critical. We find that empirical similarity is partly dependent on the network’s topology. We also observe that metrics that are conceptually similar do not necessarily have high empirical similarity. Based on the insights from the conceptual and empirical comparison, we propose a five-step guideline for transport authorities and analysts to identify the set of criticality metrics to use which best aligns with the nature of their policy questions.     

Assessment of economic impacts from unexpected events with an interregional commodity flow and multimodal transportation network model

Loss and damage caused by unscheduled events, especially earthquakes, have sudden and significant impacts not only on the region’s economy where the event occurs but also on other regions. The New Madrid Seismic Zone, located in the center of the United States, could have great impacts on economic activities related to this area, if a major earthquake occurred. Based on the 1993 US Commodity Flow Survey [US Commodity Flow Survey, 1993. Available from: <http://www.bts.gov/ntda/cfs/prod.html>], more than 42% of total commodity flows in the US are related to the greater Midwest, which includes the New Madrid Seismic Zone. If a catastrophic earthquake occurred in this area, the indirect damages could spread far beyond the region, and could have sizable impacts on other regions. A model of interregional commodity flows, incorporating regional input–output relationships, and the corresponding transportation network flows, was applied to assess the economic impacts of such an unexpected event. The economic impacts from the event are described for three hypothetical scenarios, analyzing the magnitude and the extent of the direct and indirect impacts. These analytical results may be used to propose strategic management of the recovery and reconstruction efforts after the event.     

Air transport and economic growth: a review of the impact mechanism and causal relationships

ABSTRACT

The impacts of air transport on the economy arise both directly, via activity in the aviation sector; and indirectly, via increased spending and wider economic benefits associated with improved access to resources, markets, technology and economic mass. Economic activity, in turn, supports and generates demand for air transport. Despite its potential importance, the reciprocal nature of the causal relationship between air transport and economic performance has remained somewhat understudied. This paper provides a synthesis review of the channels the aviation sector interacts with regional economy. The review focuses on quantitative studies that contribute to the state-of-the-art understandings of the causality. We find that the reciprocal causal relationship is more likely to prevail in less developed economies. For more developed economies, only one direction of the causality is recognised, which runs from air transport to economic growth. Especially substantial is the effect of airline enplanement on service-related employment. The reverse direction of the relationship is, however, not as significant as believed in a causal sense within the developed world. Therefore, cautions need to be taken when applying income elasticities (such as the elasticity of air passenger demand with respect to GDP) in air travel demand forecasting, which implicitly assumes that economic growth causally leads to air traffic increment. Based on the fundamental links between air transport and economic growth, some typical imperfections and inefficiencies in aviation markets are discussed and promising avenues for future research are proposed.     

The impact of high-speed rail investment on economic and environmental change in China: A dynamic CGE analysis

This study investigates the impact of high-speed rail investment on the economy and environment in China using a computable general equilibrium (CGE) model. The analysis is implemented in a dynamic recursive framework capturing long-run capital accumulation and labor market equilibrium. A national level impact was simulated through direct impact drivers including land use conversion, output expansion, cost reduction, productivity increase, transport demand substitution and induced demand. The results suggest that rail investment in China over the past decade has been a positive stimulus to the economy, while the effect on CO₂ emissions generation has been large. Overall, the economic impacts of rail investment are achieved primarily through induced demand and output expansion, whereas the contribution from a reduction of rail transportation costs and rail productivity increases were modest. In addition, negligible negative impacts were found from land use for rail development and the substitution effect among other modes. Emissions reduction from substitution of rail for other modes was small and offset by output expansion due to lowered rail transport costs and induced demand.     

A comparative study of a hybrid Logit–Fratar and neural network models for trip distribution: case of the city of Isfahan

This paper introduces a new procedure to forecast the future O/D demand. It is a hybrid of logit and Fratar model. The hybrid model has the long run, policy sensitive, characteristic of a logit model, calibrated at sector‐level with little/no zero O/D cells. This feature, joint with a Fratar‐type operation at zonal level within a sector, gives a better performance to this model than either of the two types of the models alone. The performance of the hybrid model is contrasted with a neural network model, and shows encouraging results in a real case. Copyright © 2010 John Wiley & Sons, Ltd.     

Validation of an agent based model using a participatory simulation gaming approach: The case of city logistics

Agent-based modeling is used for simulating the actions and interactions of autonomous entities aiming to assessing their effects on the system as a whole. At an abstract level, an agent-based model (ABM) is a representation of the many simple agents and interactions among them. The decision making of the agents is based on the rules given to them. In an ABM, the model output is the result of internal decision-making and may differ with alteration in the decision path. On the contrary, with the set of rules embedded in agents, their behavior is modeled to take a ‘certain action’ in a ‘certain situation’. It suggests that the internal decision making behavior of agents is truly responsible for the model output and thus it cannot be ignored while validating ABMs. This research article focuses on the validating agents’ behavior by evaluating decision-making processes of agents. For this purpose, we propose a validation framework based on a participatory simulation game. Using this framework we engage a human player (i.e. a domain stakeholder) to allow us to collect information about choices and validate the behavior of an individual agent. A proof-of-concept game is developed for a city logistics ABM to test the framework.     

Long-term impact of the Shinkansen on rail and air demand: analysis with data from Northeast Japan

This paper analyses how the high-speed rail construction in Northeast Japan (Tohoku) has affected total demand and interregional travel patterns. We use annual interregional passenger data from 1989 to 2012 and apply regression analysis with the demand between Tokyo and the Tohoku prefectures as the dependent variable. We distinguish particularly between the ‘Full-’ and the ‘Mini-’ Shinkansen, where the latter are branch services running with reduced speed. We find that the ‘Full-Shinkansen’ quickly increases rail and total public transport trips and generates additional rail demand year on year. The ‘Mini-Shinkansen’ impacts are less pronounced. Furthermore, our analysis shows that the Shinkansen has shifted some demand from air to rail once it started operation and increased rail share gradually. We therefore suggest that predictions of demand impacts should carefully distinguish immediate from gradual impacts. We also discuss differences in regional demand in that not all prefectures have gained equally from Shinkansen construction.     

Behavior of taxi customers in hailing vacant taxis: a nested logit model for policy analysis

This study models and examines the taxi customers' preferences for hailing vacant taxis on streets. A stated preference survey was conducted to randomly select and interview 1242 taxi customers at taxi stands and pedestrians on streets, who had experiences of taking taxis recently, about their choices under different given hypothetical scenarios. In total, 4968 observations were collected and used for developing the discrete choice models for the analysis. To account for the potential correlations among alternatives, two nested logit models are developed, calibrated, and compared with a standard multinomial logit model in the investigation. The results of likelihood ratio test demonstrate that one of the developed nested logit models is better than the standard multinomial logit model to describe the search behavior of taxi customers. The model results also show that the walking time to and the waiting time at the location for hailing taxis, the extra travel time to the destination because of local circulation for finding a way from the pickup location heading to a passenger's destination, as well as the taxi customers' perceptions for walking to and waiting at taxi stands were found as significant factors to influence their decisions. In addition, the results of market segmentation analysis illustrate the variations in taxi‐search strategies of taxi customers in different districts and regions. Some policy implications on introducing more taxi stands and improving the utilization rates of taxi stands are also discussed. We believe that the proposed models, findings, and discussion are useful for developing micro‐simulation models to evaluate the performance of road traffic networks with taxi services and developing simulation‐based optimization models to answer policy questions related to taxi services. Copyright © 2015 John Wiley & Sons, Ltd.     

Development of a simulation platform for safety impact analysis considering vehicle dynamics,sensor errors,and communication latencies: Assessing cooperative adaptive cruise control under cyber attack

While safety is one of the most critical contributions of Cooperative Adaptive Cruise Control (CACC), it is impractical to assess such impacts in a real world. Even with simulation, many factors including vehicle dynamics, sensor errors, automated vehicle control algorithms and crash severity need to be properly modeled. In this paper, a simulation platform is proposed which explicitly features: (i) vehicle dynamics; (ii) sensor errors and communication delays; (iii) compatibility with CACC controllers; (iv) state-of-the-art predecessor leader following (PLF) based cooperative adaptive cruise control (CACC) controller; and (v) ability to quantify crash severity and CACC stability. The proposed simulation platform evaluated the CACC performance under normal and cybersecurity attack scenarios using speed variation, headway ratio, and injury probability. The first two measures of effectiveness (MOEs) represent the stability of CACC platoon while the injury probability quantifies the severity of a crash. The proposed platform can evaluate the safety performance of CACC controllers of interest under various paroxysmal or extreme events. It is particularly useful when traditional empirical driver models are not applicable. Such situations include, but are not limited to, cyber-attacks, sensor failures, and heterogeneous traffic conditions. The proposed platform is validated against data collected from real field tests and tested under various cyber-attack scenarios.     

System optimal dynamic traffic assignment: Properties and solution procedures in the case of a many-to-one network

Thanks to its high dimensionality and a usually non-convex constraint set, system optimal dynamic traffic assignment remains one of the most challenging problems in transportation research. This paper identifies two fundamental properties of the problem and uses them to design an efficient solution procedure. We first show that the non-convexity of the problem can be circumvented by first solving a relaxed problem and then applying a traffic holding elimination procedure to obtain the solution(s) of the original problem. To efficiently solve the relaxed problem, we explore the relationship between the relaxed problems based on different traffic flow models (PQ, SQ, CTM) and a minimal cost flow (MCF) problem for a special space-expansion network. It is shown that all the four problem formulations produce the same minimal system cost and share one common solution which does not involve inside queues in the network. Efficient solution algorithms such as the network simplex method can be applied to solve the MCF problem and identify such an optimal traffic pattern. Numerical examples are also presented to demonstrate the efficiency of the proposed solution procedure.     

Sailing into a dilemma: An economic and legal analysis of an EU trading scheme for maritime emissions

On the basis of a joint economic and legal analysis, we evaluate the effects of a “regional” (European) emission trading scheme aiming at reducing emissions of international shipping. The focus lies on the question which share of emissions from maritime transport activities to and from the EU can and should be included in such a system. Our findings suggest that the attempt to implement an EU maritime ETS runs into a dilemma. It is not possible to design a system that achieves emission reductions in a cost efficient manner and is compatible with international law.     

Network impacts of a road capacity reduction: Empirical analysis and model predictions

In spite of their widespread use in policy design and evaluation, relatively little evidence has been reported on how well traffic equilibrium models predict real network impacts. Here we present what we believe to be the first paper that together analyses the explicit impacts on observed route choice of an actual network intervention and compares this with the before-and-after predictions of a network equilibrium model. The analysis is based on the findings of an empirical study of the travel time and route choice impacts of a road capacity reduction. Time-stamped, partial licence plates were recorded across a series of locations, over a period of days both with and without the capacity reduction, and the data were ‘matched’ between locations using special-purpose statistical methods. Hypothesis tests were used to identify statistically significant changes in travel times and route choice, between the periods of days with and without the capacity reduction. A traffic network equilibrium model was then independently applied to the same scenarios, and its predictions compared with the empirical findings. From a comparison of route choice patterns, a particularly influential spatial effect was revealed of the parameter specifying the relative values of distance and travel time assumed in the generalised cost equations. When this parameter was ‘fitted’ to the data without the capacity reduction, the network model broadly predicted the route choice impacts of the capacity reduction, but with other values it was seen to perform poorly. The paper concludes by discussing the wider practical and research implications of the study’s findings.     

Evolution of latent modal captivity and mode choice patterns for commuting trips: A longitudinal analysis using repeated cross-sectional datasets

This paper presents an investigation of the temporal evolution of commuting mode choice preference structures. It contributes to two specific modelling issues: latent modal captivity and working with multiple repeated crossectional datasets. In this paper latent modal captivity refers to captive reliance on a specific mode rather than all feasible modes. Three household travel survey datasets collected in the Greater Toronto and Hamilton Area (GTHA) over a ten-year time period are used for empirical modelling. Datasets collected in different years are pooled and separate year-specific scale parameters and coefficients of key variables are estimated for different years. The empirical model clearly explains that there have been significant changes in latent modal captivity and the mode choice preference structures for commuting in the GTHA. Changes have occurred in the unexplained component of latent captivities, in transportation cost perceptions, and in the scales of commuting mode choice preferences. The empirical model also demonstrates that pooling multiple repeated cross-sectional datasets is an efficient way of capturing behavioural changes over time. Application of the proposed mode choice model for practical policy analysis and forecasting will ensure accurate forecasting and an enhanced understanding of policy impacts.     

Modelling users’ behaviour of a carsharing program: Application of a joint hazard and zero inflated dynamic ordered probability model

This paper presents an econometric model for the behaviour of carsharing users. The econometric model is developed to jointly forecast membership duration, the decision to become an active member in a particular month, and the frequency of monthly usage of active members. The model is estimated using the membership directory and monthly transaction data of a carsharing program, ‘Communauto Inc.’, based in Montréal, Canada. The model shows a high degree of fit to the observed dataset and provides many behavioural details of carsharing users. The results are instructive to carsharing planners in devising efficient policies.     

Examination of factors affecting freeway incident clearance times: a comparison of the generalized F model and several alternative nested models

Traffic incidents are a principal cause of congestion on urban freeways, reducing capacity and creating risks for both involved motorists and incident response personnel. As incident durations increase, the risk of secondary incidents or crashes also becomes problematic. In response to these issues, many road agencies in metropolitan areas have initiated incident management programs aimed at detecting, responding to, and clearing incidents to restore freeways to full capacity as quickly and safely as possible. This study examined those factors that impact the time required by the Michigan Department of Transportation Freeway Courtesy Patrol to clear incidents that occurred on the southeastern Michigan freeway network. These models were developed using traffic flow data, roadway geometry information, and an extensive incident inventory database. A series of parametric hazard duration models were developed, each assuming a different underlying probability distribution for the hazard function. Although each modeling framework provided results that were similar in terms of the direction of factor effects, there was significant variability in terms of the estimated magnitude of these impacts. The generalized F distribution was shown to provide the best fit to the incident clearance time data, and the use of poorer fitting distributions was shown to result in severe over‐estimation or under‐estimation of factor effects. Those factors that were found to impact incident clearance times included the time of day and month when the incident occurred, the geometric and traffic characteristics of the freeway segment, and the characteristics of each incident. Copyright © 2012 John Wiley & Sons, Ltd.     

Specification and calibration of a microscopic model for pedestrian dynamic simulation at signalized intersections: A hybrid approach

Macroscopic pedestrian models for bidirectional flow analysis encounter limitations in describing microscopic dynamics at crosswalks. Pedestrian behavior at crosswalks is typically characterized by the evasive effect with conflicting pedestrians and vehicles and the following effect with leading pedestrians. This study proposes a hybrid approach (i.e., route search and social force-based approach) for modeling of pedestrian movement at signalized crosswalks. The key influential factors, i.e., leading pedestrians, conflict with opposite pedestrians, collision avoidance with vehicles, and compromise with traffic lights, are considered. Aerial video data collected at one intersection in Beijing, China were recorded and extracted. A new calibration approach based on a genetic algorithm is proposed that enables optimization of the relative error of pedestrian trajectory in two dimensions, i.e., moving distance and angle. Model validation is conducted by comparison with the observed trajectories in five typical cases of pedestrian crossing with or without conflict between pedestrians and vehicles. The characteristics of pedestrian flow, speed, acceleration, pedestrian-vehicle conflict, and the lane formation phenomenon were compared with those from two competitive models, thus demonstrating the advantage of the proposed model.