Evaluation Of Transport Policies Research Articles

Synthetic Generation of Trip Data: The Case of Smart Card

While individual data are key for epidemiology, social simulation, economics, and various other fields, data owners are increasingly required to protect the personally identifiable information from data. Simple data de-identification or ‘data masking’ measures are limited, because they both reduce the utility of the dataset and are not sufficient to protect individual confidentiality. This paper provides detail on the creation of a synthetic trip data in transportation, with the Smart Card data as the case study. It discusses and compares two machine learning methods, a Generative Adversarial Network and a Bayesian Network for modelling and generating this dataset. The synthetic data retain important utility of the real dataset, e.g., the origin, destination, and time of travel, while each data point does not represent a real trip in the original dataset. The synthetic dataset can be used in various applications, including microsimulation of public transport systems, analysing travel behaviours, model predictive control of transit flows, or evaluation of transport policies.

How to translate justice theory into urban transport metrics? Synchronic assessment of Latin American cities based on equality, priority and sufficiency

This article seeks to carry out a study on the measurement of justice in transportation through the introduction of original metrics of justice that consider different currencies (travel time, energy consumption, PM emissions and NOₓ emissions) and principles of justice (Equality, Priority and Sufficiency), relying on available data from five metropolitan regions in Latin America. Based on available data from five metropolitan regions in Latin America (Brasília, Ciudad de México, Montevideo, Santiago, and São Paulo), this manuscript seeks to reduce the theoretical gap in the transport literature through the development of metrics of distributive justice based on existing Origin-Destination transport surveys, which is expected to identify the characteristics that seem to govern a fairer transport system, as well as to inform practitioners and policy makers about the conditions driving fairer urban environments. In addition to contributions to the evaluation of transport policies with data from developing countries, the discussions presented in this paper intend to provide insights into the major role of selecting the principles of justice and the distributed resources to evaluate the degrees of fairness in transportation systems.

Debiased Machine Learning for Estimating the Causal Effect of Urban Traffic on Pedestrian Crossing Behavior

Before the transition of automated vehicles (AVs) to urban roads and subsequently unprecedented changes in traffic conditions, the evaluation of transportation policies and futuristic road design related to pedestrian crossing behavior is of vital importance. Recent studies analyzed the non-causal impact of various variables on pedestrian waiting time in the presence of AVs. However, we mainly investigate the causal effect of traffic density on pedestrian waiting time. We develop a double/debiased machine learning (DML) model in which the impact of the confounders variable influencing both a policy and an outcome of interest is addressed, resulting in unbiased policy evaluation. Furthermore, we try to analyze the effect of traffic density by developing a copula-based joint model of the two main components of pedestrian crossing behavior, pedestrian stress level and waiting time. The copula approach has been widely used in the literature for addressing self-selection problems, which can be classified as a causality analysis in travel behavior modeling. The results obtained from copula approach and DML are compared based on the effect of traffic density. In the DML model structure, the standard error term of the density parameter is lower than that of the copula approach and the confidence interval is considerably more reliable. In addition, despite the similar sign of effect, the copula approach estimates the effect of traffic density lower than DML, because of the spurious effect of the confounders. In short, the DML model structure can flexibly adjust the impact of confounders by using machine learning algorithms and is more reliable for planning future policies.

Exploring the interactions between modal options, destination access, and travel mood

A good understanding of subjectively experienced well-being in daily travel is critical for the design and evaluation of transportation policies and programs. Numerous studies have examined the relationship between how we travel and how we feel during travel. However, people’s travel mood is not only determined by their trip characteristics but also their potential mobility—the capacity of being mobile.Using the data collected via a smartphone application in Minneapolis-St. Paul area, we measure potential mobility in two aspects—modal options and destination access and reveal that people in households with better access to cars and alternative transportation modes are, all else equal, more likely to report more positive moods and fewer negative moods during travel. In addition, people living in neighborhoods with greater access to destinations are less likely to feel stress when traveling. We also find that associations between mode and mood are moderated by modal options and destination access. These findings confirm the importance of explicitly considering modal options and destination access in policy debates and planning initiatives addressing transportation and well-being. In doing so, they demonstrate the relevance of Sen’s Capabilities Approach to transportation planning.

Towards a health-conscious transportation planning: A framework for estimating health impacts of active transportation at local level

IntroductionThe inter-relationship between physical activity and health is well-documented in transportation and public health literature. Nevertheless, health impacts are rarely considered in transportation planning processes due to the lack of a robust mechanism to quantify such impacts. The Integrated Transport and Health Impact Modeling (ITHIM) framework provides an opportunity to systematically estimate health impacts of active travel as a result of variations in transportation infrastructure and policies that involve non-motorized modes. MethodsThis study applies ITHIM framework to Prince George's County, Maryland, to explore potential health impacts of improved active travel through hypothetical scenarios. ITHIM integrates data on travel behavior, health, demographics, road injuries and air quality. We constructed three What-If scenarios that reflect significant increases in walking and biking –a potential result of the ambitious infrastructure plans in place at the PG County – and decrease in personal vehicle miles. ResultsSignificant health and economic benefits are observed under three scenarios. We observed considerable health benefits in the scenarios where we made assumptions about increased active travel and reduced automobile usage, e.g. if everyone bikes 1.5 miles and drives 1.5 miles less per day, the county will save about 35 lives and 1,443 DALYs. We also observed significant monetary values of lifesaving in the economic analysis, indicating $117 million savings in the cost of illness (COI) for scenario1 (increased walking) and $34 million savings in COI as a result of scenario2 (increased biking) and scenario3 (increased biking and reduced driving). ConclusionThis study provides insight into a better understanding of the potential health impacts of various transportation planning scenarios and provides an example for including health impact estimates in evaluating transportation policies and plans at local level. It highlights the importance of policies that encourage people to walk and bike also need to adopt measures that increase safety.

Transport policy evaluation based on elasticity analysis with social interactions

Abstract The effects of social interactions on individual behaviour have been observed in many social phenomena, including travel-related behaviour involving direct or indirect contact with other agents. However, most formulations of urban transport policy assume that individual behaviour is independent of each other, which likely results in policy evaluation bias. Therefore, this study aimed at urban parking behaviour with frequent interactions among agents in Taiwan (1) to examine the influence of others’ behaviour on individuals by modelling parking location choice and introducing social utility and (2) to develop a modified elasticity analysis method that considers policy spillover effects driven by social interactions and then use it to conduct parking policy evaluation based on the choice model. A stated preference survey targeting scooter and bicycle users was performed through face-to-face interviews to simulate parking policy and reference-group behaviour levels. The pseudo panel where the observations of each respondent may be interdependent was addressed by a mixed logit model incorporating an error component to capture unobserved individual heterogeneity. The results of the model estimation supported the presence of social interactions among users and identified other influential determinants of parking location choice including travel characteristics (visit frequency and vehicle used), psychological heterogeneity (attitudes and personal norms), and parking policy (distance, fixed cost, and marginal cost). For policy evaluation, the proposed elasticity analysis method with social interactions illustrated that policy spillover effects (49.7%) were nearly as strong as direct policy effects (50.3%). Two-wheel vehicle parking policy measures containing soft measures based on attitudes and personal norms and hard measures considering social influences were presented for on-street parking mitigation.

Calibration of car-following model for Indian traffic conditions

In order to implement transport polices effectively and efficiently on the ground, it is prudent to evaluate such policies using high accurate techniques such as microscopic traffic simulation models. Car-following model is regarded as vital in representing individual vehicle behaviour and highly influences the accuracy of the simulation model predictions. Though, there are number of car-following models available especially for developed countries where the traffic conditions are highly homogeneous in nature. Adopting these car-following models for Indian traffic conditions would result inaccurate estimations and unrealistic evaluation of transport policies due to the existence of highly heterogeneous traffic conditions, different driver behaviour, no lane discipline etc. on the Indian roads. In view of this, an attempt has been made in this paper to develop car-following model for Indian traffic conditions. Accordingly, data of latitude, longitude positions and speed has been collected precisely for each one tenth of second time interval on both urban corridor and non-urban corridor using VBOX equipments which are fitted in both leader and following vehicles. To develop car-following models for Indian traffic conditions, the formulations of standard car-following models namely General Motors (GM) Model and Hidas Model have been considered and accordingly modified car-following models have been developed by calibrating the parameters using the collected data on both urban and non-urban corridors. By comparing the RMSE and MAE values from estimated and observed data, it can be inferred that the developed car-following models are able to estimate the following vehicle accelerations with fair amount of accuracy.

A disaggregate freight transport chain choice model for Europe

This paper presents the estimation of a discrete freight transport chain choice model for Europe, which was developed for the European Union as part of the Transtools 3 project. The model describes nine different multi- and single mode chain alternatives of which three can be either container or non-containerised, and it segments freight into dry bulk, liquid bulk, containers and general cargo. The model was estimated on the basis of disaggregate data at the shipment level (Swedish CFS and French ECHO data). Several transport costs specifications and nesting structures were tested and elasticities compared with reference literature. It was found that freight models are characterised by heterogeneity, non-linearity in transport costs and hence Value of Times and non-constant rates of substitution. Not taking these elements into account will have consequences for the evaluation of transport policies using the freight transport model.

Quantifying welfare loss due to longer commute times in Seoul: A two-stage hedonic price approach

The relationship between commute duration and commuter well-being is an essential component of transport policy evaluation and planning, but few studies have considered it. This study evaluates the degree of capitalization of commute time in the housing market and measures the welfare loss caused by longer commute times using the Seoul metropolitan area (SMA) in Korea as a case study. We estimate a demand function between the observed commute time and its implicit price and evaluate the welfare loss for the average increase in commute time in the SMA between 1995 and 2010. The empirical findings show that the documented 12.5% increase in commute time caused a welfare loss of $1.3 billion for employees in the SMA. This evidence clearly links longer commute times with declining commuter well-being.

2446 - Monitoring Daily Activities and Linking Physical Activity Levels Attributed to Transportation Mobility Choices

Background Transportation decisions impact human health at least in three ways, such as traffic crashes, environmental impact, and physical fitness. While there have been ample efforts in reducing traffic crashes and environmental impacts, less attention has been paid to their impacts on physical fitness. Recent efforts on the relationship between transportation and physical fitness were mostly from the context of active transportation. Potential benefits of active transportation include saving in mobility costs, benefits from related businesses, community savings in costs associated with health and environmental benefits. Although it is difficult to predict how a particular transportation planning decision affects physical fitness, total impacts are likely to be large. Diseases associated with inadequate physical fitness cause an order of magnitude of more deaths, and more than road crashes. Even modest reductions in these illnesses could provide significant health benefits. Therefore, there is a strong need for investigating how transportation options affect the physical activities and public health. Methods The research team developed a mobile application that collects individuals’ daily travel activities physical fitness activities. While the travel activity data are collected from the GPS information from individuals’ mobile phone, the fitness activity data are collected from Fitbit. Data collected from 200 subjects chosen in Michigan and Texas are transmitted to a server for further analysis. The data allows comparison of physical activity associated with transportation choices in different geographical areas and its seasonal variations. Results The data logged each minute were processed to determine daily activity (type, location, and duration), travel activity (transportation mode, travel time), and physical activity (heart rates and duration). The heart rates collected from Fitbit were useful in determining activity types and the transportation mode. The integrated approach allowed classification of various activity types and transportation modes. The amount of physical activity by activity type and travel mode was quantified by using the heart rate and the activity duration. The initial survey showed that those who were active in physical activity tend to choose active transportation options. Conclusion This study developed a mobile system that is able to collect daily activity, transportation choices, and the amount of physical activity. The data collected were analyzed to quantify the amount of physical activity by different transportation choice. This research is expected to help incorporate public health in evaluating transportation policies and alternatives by providing a method quantifying the amount of physical activities and associated health benefits.

Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain

Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patterns of this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990–2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.

Evaluating the long term impacts of transport policy: The case of bus deregulation revisited

In a previous paper in this journal, we suggested that the bus reforms that were implemented in Britain from the mid-1980s onwards were welfare positive for both London and for the rest of Great Britain outside London (Preston & Almutairi, 2013). However, we cautioned that this work was preliminary and likely to be sensitive to various assumptions made. In this paper, we have undertaken more detailed sensitivity analysis as follows. First, we have developed separate demand models for London and for the rest of Great Britain. Secondly, we have developed cost models to determine the extent to which costs are determined by external factors (such as fuel prices) or partially external factors (such as labour costs). Thirdly, we have developed fares models to assess the impact of changes in subsidy, in terms of both revenue support and concessionary fare reimbursements. We have also changed the measurements of consumer surplus so as to be more consistent with underlying economic theory. This work confirms the sensitivity of the long term evaluation of transport policy to assumptions concerning the counterfactual and trends in demand, supply and prices. Any policy lessons inferred from these long term evaluations need to take these sensitivities into account.

Multidimensional Indicator Analysis for Transport Policy Evaluation

The need for forecasting the direct and indirect effects of land use and transport policies on society, the environment, and the local economy has led to the development of integrated land use and transport (LUTI) models. The land use and transport policy evaluation is based on point estimators of economic sustainability indicators, usually computed at an aggregate level (e.g., social welfare) despite the fact that the models and simulation are based on the individual. A methodology based on the strength of microsimulation in three dimensions (space, time, and agents) is presented. By multiple simulation runs of the LUTI model UrbanSim, the distributions of inequality and accessibility indicators in space and time were generated, and their variance was measured. The methodology was first applied in a base case scenario (in which the then current trend existed) of the Limmattal region including Zurich, Switzerland, and then on a public transport investment scenario. The results of the two scenarios were then compared on the basis of actual distributions rather than the mean point values of the indicators. The proposed methodology differed from the point-based policy evaluation frameworks in terms of details and insightfulness that could better support the process of informed decision making.

Ethical Theories and the Cost–Benefit Analysis-Based Ex Ante Evaluation of Transport Policies and Plans

ABSTRACTIn the policy analysis community it is widely recognized that ‘sound’ policies meet three criteria: effectiveness, efficiency and equity. In most western countries, cost–benefit analysis (CBA) is currently the standard method to ex ante evaluate transport policy options. It scores high for effectiveness and efficiency, but generally ignores equity and other ethically important implications of policies. The CBA has its roots in the ethical theory of utilitarianism. However, both utilitarianism and CBA have faced many objections. We present alternative ethical theories, based on deontological theories and contractarianism. We discuss how these theories can inspire the ex ante evaluation of transport policy options. We argue that in order to come to a moral evaluation of transport policies we need a context-sensitive approach. According to such an approach, there is a plurality of morally relevant features that have to be balanced per situation. We argue that such a context-sensitive approach is more appropriate than a priori selecting one theory such as utilitarianism, as such a theory is not appropriate in all possibly relevant circumstances. Consequently, by being based on utilitarianism, CBA overlooks issues of justice, fairness, and autonomy that are morally relevant to an evaluation of transport policies.

Empirical assessment of urban traffic congestion

SUMMARYThis paper presents an empirical assessment of urban traffic congestion in Central London, UK. Compared with freeways or motorways, urban networks are relatively less studied because of its complexity and availability of required traffic data. This paper introduces the use of automatic number plate recognition technology to analyze the characteristic of urban traffic congestion in Central London. We also present the use of linear regression to diagnose the observed congestion and attribute them to different causes. In particular, we distinguish the observed congestion into two main components: one due to recurrent factors and the other due to nonrecurrent factors. The methodologies are illustrated through a case study of Central London Area. It is found that about 15% of the observed congestion in the region is due to nonrecurrent factors such as accidents, roadwork, special events, and strikes. Given the significance of London, the study will be valuable for transport policy evaluation and appraisal in other global cities. Copyright © 2013 John Wiley & Sons, Ltd.

Quantification of Nonrecurrent Congestion Delay Caused by Freeway Accidents and Analysis of Causal Factors

The objectives of this study are twofold: to quantify nonrecurrent congestion delay caused by traffic accidents that occur on freeways and to analyze the causal factors by different types of accidents. Unlike previous studies, this study proposes an analytical procedure to estimate congestion impact by using the difference between speed reduced by a traffic accident and accident-free normal flow speed. The proposed method is demonstrated by a case study using accident data derived from 27 freeways in South Korea in 2008. Ultimately, the method can develop a performance measure for evaluating transportation policies and planning level analyses associated with the design of transportation systems and preparation of operating plans for safety, as well as for quantitatively evaluating deployed transportation projects or technologies. Moreover, the results from statistical analyses can potentially be useful in making strategic plans and formulating mitigation measures for reducing nonrecurrent congestion delay caused by accidents on the South Korean freeway system.

都市交通政策評価のためのファジィ理論に基づくミクロ交通流シミュレーションの構築

都市交通政策評価のためのファジィ理論に基づくミクロ交通流シミュレーションの構築

Transport policy evaluation in metropolitan areas: The role of modelling in decision-making

The adoption of Integrated Urban Models (IUMs) is increasingly being recognized as a tool to support transport policy appraisals in metropolitan areas. In Canada, the ILUTE (Integrated Land Use Transportation Environment) project is an IUM framework currently under development. While model development is undertaken by academics, the implementation of ILUTE is meant to occur within planning organizations thus rendering the success of model application dependent on available resources for modelling and planners’ attitudes towards the role of models. In an attempt to render the ILUTE modelling framework more “policy-sensitive”, a survey was conducted with planners and policy-makers pertaining to the three levels of government (municipal, provincial, and federal) in Canada. The survey collects information with respect to the current evaluation process of transport policy and its associated pitfalls as well as the desired state of policy appraisal and the need for more formal evaluation tools. Results show the presence of numerous challenges working against the proper development, adoption, and refining of models. The most notable of which include a general disbelief in the usefulness of models for decision-making, lack of resources for large-scale modelling exercises, and poor institutional integration among government departments. While local and national planning goals reflect the recent challenges of promoting environmental preservation, reducing social inequities, and improving the quality of life, modelling tools that can assess the impacts of proposed policies on these goals have lagged behind.

Institutional integration for sustainable transportation policy in Canada

In recent years, many Canadian urban areas have witnessed a rapid population and economic growth thereby putting sustainable transport and urban form at the forefront of planning initiatives. As a result, the development of strategic transport plans and long-range visioning exercises has become a priority for most cities. Still, proper appraisals of these plans along with funding and implementation have lagged behind. Reasons for this lag can be attributed to the lack of constructive interactions between actors in the decision-making process and of common grounds for policy evaluation. This paper proposes to assess the extent of institutional integration in the appraisal, funding, and implementation of transport policy. For this purpose, a survey was conducted with planners and policy-makers pertaining to the three levels of government (municipal, provincial, federal) in Canada. The survey discussed the existing process for funding and evaluation of transport policy and its associated pitfalls as well as the desired state of policy appraisal. Results show low institutional integration among the three levels of government and weakened regional visions within most urban areas in spite of an increased sensitization of decision-makers and the public regarding the importance of achieving society's goals of sustainability and equity.

The value of time and transport policies in a parallel road network

One of the key questions in the evaluation of transport policies and investment decisions is the valuation of the time savings or losses arising from such decisions. This paper uses the stated preference method to determine the value of time in a given traffic context characterised by a road parallel network. The values obtained are higher than usual in Spanish project evaluation which, among other things, points out the need for specific studies of all transport projects whenever possible. Finally, two cases are described which illustrate the relevance of the value of time. The first evaluates time savings related to the pricing policies of a motorway competing with a trunk road. The second establishes the minimum amount of traffic that justifies the replacement of a single carriageway by a dual carriageway.