A system dynamics approach to land use/transportation system performance modeling Part I: Methodology

This paper presents a system dynamics approach to simultaneous land use/transportation system performance modeling. A model is designed based on the causality functions and feedback loop structure between a large number of physical, socioeconomic, and policy variables. The model consists of 7 sub‐models: population, migration of population, household, job growth‐employment‐land availability, housing development, travel demand, and traffic congestion level. The model is formulated in DYNAMO simulation language, and tested on a data set from Montgomery County, MD. In Part I: Methodology, the overall approach and the structure of the model system is discussed and the causal‐loop diagrams and major equations are presented. In Part II: Application, the model is calibrated and tested with data from Montgomery County, MD. Least square method and overall system behavior are used to estimate the model parameters. The model is fitted with the 1970–80 data and validated with the 1980–1990 data. Robustness and sensitivities with respect to input parameters such as birth rate or regional economy growth are analyzed. The model performance as a policy analysis tool is examined by predicting the year by year impacts of highway capacity expansion on land use and transportation system performance. While this is a first attempt in using dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions, and model development and application are limited due to data availability, the results indicate that the proposed method is a promising approach in dealing with complex urban land use/transportation modeling.     

A system dynamics approach to land use / transportation system performance modeling Part II: Application

This paper presents a system dynamics approach to simultaneous land use/transportation system performance modeling. A model is designed based on the causality functions and feedback loop structure between a large number of physical, socioeconomic, and policy variables. The model system consists of 7 sub‐models: population, migration of population, household, job growth‐employment‐land availability, housing development, travel demand, and traffic congestion level. The model is formulated in DYNAMO simulation language, and tested on a data set from Montgomery County, MD. In Part I: Methodology, the overall approach and the structure of the model system is discussed and the causal‐loop diagrams and major equations are presented. In Part II: Application, the model is calibrated and tested with data from Montgomery County, MD. Least square method and overall system behavior are used to estimate the model parameters. The model is fitted with the 1970–80 data and validated with the 1980–1990 data. Robustness and sensitivities with respect to input parameters such as birth rate or regional economy growth are analyzed. The model performance as a policy analysis tool is also examined by predicting the year by year impacts of highway capacity expansion on land use and transportation system performance. While this is a first attempt in using dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions, and model development and application are limited to some extent due to data availability, the results clearly indicate that the proposed method is a promising approach in dealing with complex urban land use/transportation modeling     

A land use and transportation integration method for land use allocation and transportation strategies in China

In this paper, we will first review literature of the land use and transportation interaction and then develop a new land use allocation methodology called Three Stages-Two-Feedback Method (Integration Method) for both land use allocation and the transportation policy options with a practical implementation. Then we apply this method in an urban general planning project in China with more than 1.2 million populations. In this project, we evaluated three land use allocation strategies and three transportation policy options using two application tools (with and without feedbacks) using this method implemented in a land use planning system UPlan and a transportation planning system Emme. The results show that the use of the feedback method (Application Two) results in a vehicle distance reduction and the increase in the service coverage area of transit bus stops at the same time. Due to the use of transportation accessibility and the congestion measures with a MSA implementation, the accessibility measure shows a convergent process over iterations. This nice feature can be used for alternative comparisons. Future research subjects are also discussed.     

Transportation mode detection – an in-depth review of applicability and reliability

The wide adoption of location-enabled devices, together with the acceptance of services that leverage (personal) data as payment, allows scientists to push through some of the previous barriers imposed by data insufficiency, ethics and privacy skepticism. The research problems whose study require hard-to-obtain data (e.g. transportation mode detection, service contextualisation, etc.) have now become more accessible to scientists because of the availability of data collecting outlets. One such problem is the detection of a user's transportation mode. Different fields have approached the problem of transportation mode detection with different aims: Location-Based Services (LBS) is a field that focuses on understanding the transportation mode in real-time, Transportation Science is a field that focuses on measuring the daily travel patterns of individuals or groups of individuals, and Human Geography is a field that focuses on enriching a trajectory by adding domain-specific semantics. While different fields providing solutions to the same problem could be viewed as a positive outcome, it is difficult to compare these solutions because the reported performance indicators depend on the type of approach and its aim (e.g. the real-time availability of LBS requires the performance to be computed on each classified location). The contributions of this paper are three fold. First, the paper reviews the critical aspects desired by each research field when providing solutions to the transportation mode detection problem. Second, it proposes three dimensions that separate three branches of science based on their main interest. Finally, it identifies important gaps in research and future directions, that is, proposing: widely accepted error measures meaningful for all disciplines, methods robust to new data sets and a benchmark data set for performance validation.     

Emergence of resilience as a framework for state Departments of Transportation (DOTs) in the United States

State Departments of Transportation (DOTs) in the United States are responsible for a large portfolio of transportation modes and services, including passenger and freight systems. These responsibilities include operations under routine conditions and during incidents and events that result from various natural and human-caused hazards. During unexpected events, disruptions and reductions in service result in requiring the reallocation and reassignment of personnel, modal, and economic resources. To better prevent and respond to the effects of service disruptions, the concept of resilience has emerged as an important framework, within which, DOTs across the United States are using to plan for the occurrence of threats. In this paper, the key findings of recent reviews of literature and practice related to resilience among state DOTs in the United States are summarized. The review effort focused on a range of risks faced by transportation agencies including climate change, terrorism, cyber-attacks, and aging infrastructure and the ways in which DOTs are confronting them in practice. The topics of this paper range from the fundamental, including definitions of transportation resilience; to the more complex such as examinations of risk, vulnerability and threats; to the most sophisticated topics including administrative-level efforts to conceptualize evolving transportation planning and policies within a resilience framework.     

Optimization Of Headway,Vehicle Size and Route Choice for Minimum Cost Feeder Service

ABSTRACT

Many people use public transportation systems to reach their destination, while others use personal vehicles. Poor transportation systems do not attract ridership. Therefore, the usage of passenger cars increases, and traffic and environmental conditions deteriorate. Efficient public transportation has been recognized as one of the potential ways of mitigating air pollution, reducing energy consumption, improving mobility and alleviating traffic congestion. The objective of this study is to optimize a bus feeder service that provides the shuttle service between a recreation center (e.g. Sandy Hook, NJ) and a major public transportation facility, subject to site-specific constraints such as vehicle schedules, bus availability, service capacity and budget. The decision variables include bus headway, vehicle size and route choice. The solution methodology integrating both analytical and numerical techniques is developed, which optimizes the decision variables. Finally, the proposed solution methodology is applied to a case study. Numerical results, including optimal solutions and sensitivity analyses, are presented while the level of coordination between the feeder service and a major transportation service is discussed.     

Big data in public transportation: a review of sources and methods

ABSTRACT

The collection of big data, as an alternative to traditional resource-intensive manual data collection approaches, has become significantly more feasible over the past decade. The availability of such data, coupled with more sophisticated predictive statistical techniques, has contributed to an increase in attention towards the application of these data, particularly for transportation analysis. Within the transportation literature, there is a growing emphasis on developing sources of commonly collected public transportation data into more powerful analytical tools. A commonly held belief is that application of big data to transportation problems will yield new insights previously unattainable through traditional transportation data sets. However, there exist many ambiguities related to what constitutes big data, the ethical implications of big data collection and application, and how to best utilize the emerging data sets. The existing literature exploring big data provides no clear and consistent definition. While the collection of big data has grown and its application in both research and practice continues to expand, there is a significant disparity between methods of analysis applied to such data. This paper summarizes the recent literature on sources of big data and commonly applied methods used in its application to public transportation problems. We assess predominant big data sources, most frequently studied topics, and methodologies employed. The literature suggests smart card and automated data are the two big data sources most frequently used by researchers to conduct public transit analyses. The studies reviewed indicate that big data has largely been used to understand transit users’ travel behavior and to assess public transit service quality. The techniques reported in the literature largely mirror those used with smaller data sets. The application of more advanced statistical methods, commonly associated with big data, has been limited to a small number of studies. In order to fully capture the value of big data, new approaches to analysis will be necessary.     

Evaluating employer programs encouraging the use of alternate transportation modes: Two studies

Since 1976, major Denver metropolitan area firms have been required to encourage employees to use mass transit, carpooling, bicycling, and other alternate transportation modes to commute to work. The encouragement programs of 36 firms were clearly associated with greater use of alternate transportation modes, with the portion of variance in alternate transportation use explained by differences in employer programs of approximately 15%. The effects of the programs on deterring alternate mode users from returning to solo driving are consistently weaker than their effects on persuading drivers to try alternate transportation modes initially. Recommendations for the conduct of alternate transportation encouragement programs are made, based on these and other results. In addition, two recommendations are made concerning the evaluation of encouragement programs: that aggregate percentage change in alternate transportation use should not be used as the sole measure of success, and that environmental variables such as the availability of and pressure for use of alternate transportation modes should be measured and controlled.     

The meaning of car availability in mode choice decisions

The paper examines various definitions of car availability that have been used in the literature, and compares the results when applied to a common data set. It argues that car availability means different things to different people depending on their licence holding/car owning status. Using in‐depth interview data, the factors determining car allocation and transferability within a household, and subsequently mode choice, are discussed. An attempt is made to draw some general conclusions for research and modelling. This suggests that different approaches are required depending on whether or not there is competition for use of the car within a household. Also that in cases of competition, mode choice is not a two‐stage process depending on car availability and trip characteristics, but a concurrent decision based on both of these factors.     

Measuring the performance of airport resilience to severe weather events

The increased severe weather events in recent years as a result of global climate change has created a substantial challenge for aviation system operation. Although transportation engineers and planners have attempted to improve system resilience through the adaptation of new technologies and the implementation of various strategies to achieve effective risk management, it remains unclear how resilience performance (measured by the speed of recovery) of airports varies in different severe weather events and what factors may explain such variations. This paper addresses these fundamental questions using the aviation system in China as an example. A resilience metric, which reflects the speed of recovery (bounce back) from a shock, was developed to measure the performance of airport resilience under various severe weather conditions. In addition, an empirical econometric analysis was conducted based on a dataset that includes both detailed aviation performance and weather conditions for the period of October 2016 – September 2017. The research findings show that airport resilience to severe weather events does vary substantially based on factors, such as weather conditions, airport capacity, and the level of modal substitution. In particular, the recovery time of air services in central and south China tends to be relatively longer in thunderstorms than other weather conditions. The study also confirms that modal substitution is a very effective resilience tactic of the transportation system as the recovery speed of air service was found to be faster by 22.9% if an alternative mode, such as high-speed rail (HSR) service was also available in the city.     

Isolating high-priority metro and feeder bus transfers using smart card data

Fixed-rail metro (or ‘subway’) infrastructure is generally unable to provide access to all parts of the city grid. Consequently, feeder bus lines are an integral component of urban mass transit systems. While passengers prefer a seamless transfer between these two distinct transportation services, each service’s operations are subject to a different set of factors that contribute to metro-bus transfer delay. Previous attempts to understand transfer delay were limited by the availability of tools to measure the time and cost associated with passengers’ transfer experience. This paper uses data from smart card systems, an emerging technology that automatically collects passenger trip data, to understand transfer delay. The primary objective of this study is to use smart card data to derive a reproducible methodology that isolates high priority transfer points between the metro system and its feeder-bus systems. The paper outlines a methodology to identify transfer transactions in the smart card dataset, estimate bus headways without the aid of geographic location information, estimate three components of the total transfer time (walking time, waiting time, and delay time), and isolate high-priority transfer pairs. The paper uses smart card data from Nanjing, China as a case study. The results isolate eight high priority metro-bus transfer pairs in the Nanjing metro system and finally, offers several targeted measures to improve transfer efficiency.     

Telecommunications and travel demand and supply: Aggregate structural equation models for the US

Disaggregate studies of the impacts of telecommunications applications (e.g. telecommuting) on travel have generally found a net substitution effect. However, such studies have all been short-term and small-scale, and there is reason to believe that when more indirect and longer-term effects are accounted for, complementarity is the likely outcome. At least two aggregate studies have focused on the relationships between telecommunications and travel from economic perspectives (consumer and industry). However, both use the monetary value of consumption or transactions rather than actual activity measures (e.g. miles, number of calls), and neither fully explains the direct and indirect causal relationships between the two. The purpose of this study is to develop a conceptual model in a comprehensive framework, considering causal relationships among travel, telecommunications, land use, economic activity, and socio-demographics, and to explore the aggregate relationships between telecommunications and travel, using structural equation modeling of national time series data spanning 1950–2000 in the US. In this paper we focus on number of telephone calls as the measure of telecommunications, and passenger vehicle–miles traveled as the measure of transportation. Future research will investigate additional measures of these two constructs. Our empirical results strongly support the hypothesis that telecommunications and travel are complementary. That is, as telecommunications demand increases, travel demand increases, and vice versa. These results offer a more realistic picture to policy makers and transportation planners than has been available till now, and suggest useful directions for them to develop transportation or telecommunications strategies designed to reduce traffic congestion, air pollution, and energy consumption.     

Rail freight service productivity from the manager's perspective

To be beneficial to management, productivity concepts must be translated into terms that are meaningful to managers at all levels of the organization. Productivity per se is not nearly as important to these people as service quality and financial performance, especially since measured productivity can improve while profits or service levels decline. Productivity must, therefore, be related to an integrated set of performance measures that reflect costs, revenues, trip times and reliability, equipment availability and other matters of continuing concern to transportation companies. Planning and control are critical components of any program to improve productivity. The techniques required to measure and understand productivity are precisely those used in planning and in developing control systems. Furthermore, productivity is conceptually very close to cost analysis, which is a major focus of planning and control. Any transportation company has access to the data needed to develop a vast array of performance measures, including many productivity measures. This paper will illustrate the way that railroads can integrate productivity concepts within more global performance measurement systems. Specific attention will be given to terminal control systems, costing systems for origin-to-destination movements and life-cycle costing techniques for track maintenance planning.     

Efficiency and equity issues in special fees for financing transportation infrastructure

Theoretically, charges for building and operating facilities and services should be efficient (proportional to one's use of or benefit derived from the service) and equitable (proportional to one's ability to pay). A number of “innovative” financing techniques have been used recently, whereby the private sector (developers, property owners, businesses, and users) pays entirely or partially for the cost of building and operating transportation facilities or services. These techniques are particularly popular when the impact from the land use developments on the transportation system is such that substantial improvements are warranted in order to avoid serious congestion problems. The purpose of this paper is to investigate special fee assessments (a popular sub-set of “innovative” financing techniques) used for financing highway and mass transportation in order to determine their efficiency and equity implications. The need for such an investigation arises from the fact that everyone residing or doing business in a particular area does not benefit equally from a given transportation system, and neither is everyone able to contribute equally toward that system's building and operation. This paper presents some of the most commonly used special fee assessment techniques and suggests fee structures that are “optimal” on the basis of the benefits that contributors derive from the given transportation system, as well as their ability to pay for it.     

A comparison of the sustainability of public and private transportation systems: Study of the Greater Toronto Area

A macroscopic assessment of the impacts of private and public transportation systems on the sustainability of the Greater Toronto Area (GTA) is undertaken from economic, environmental and social perspectives. The methodology draws upon the urban metabolism and sustainability indicators approaches to assessing urban sustainability, but compares modes in terms of passenger-kms. In assessing the economic sustainability of a city, transportation should be recognized as a product, a driver and a cost. In 1993, the traded costs of automobile use in the GTA were approximately balanced by the value of the automobile parts and assembly industry. But local transit costs 1/3 to 1/6 of the auto costs per person-km, in traded dollars, mainly because local labour is the primary cost.Public transportation is more sustainable from an environmental perspective. Automobile emissions are a major contributor to air pollution, which is a serious contemporary environmental health problem in Toronto. Public transportation modes are less energy intensive (including indirect energy consumption) and produce CO₂ at an order of magnitude lower, although these benefits are partially undermined by under-utilization of transit capacity and the source of electricity generation.The social benefits of automobile use are likely more significant than costs in determining GTA residents' preferential mode choice. The speed and access of auto use provide important economic benefits, e.g. relating to employment and product choice. Nevertheless, offsetting the service attributes of private transportation are large social costs in terms of accidents. The costs of automobile insurance provide one tangible measure of such negative impacts.In order to improve the sustainability of the GTA, innovative approaches are required for improving the performance level of public transportation or substantially reducing the need for the service level provided by automobiles. Efforts such as greater integration of bicycles with public transit, or construction of light-rail systems in wide roadways, might be considered. But to be sustainable overall, a transportation system has to be flexible and adaptable and so must combine a mixture of modes.     

The role of accessibility in basic transportation choice behavior

Accessibility measures reflect the level of service provided by transportation systems to various locations. Basic transportation choice behavior is defined to include those decisions of how many automobiles to own and how many trips to which destinations to make by automobile and by public transit. Here, these decisions are assumed to be made jointly by urban households and are conditional upon residential location decisions. It is the purpose of this paper to explore the role of accessibility as a causal factor in such basic transportation choice behavior.An economic utility theory model of choice behavior is postulated in which the benefits from making trips to specific destinations are reflected by measures of destination attraction. Through determination of utility-maximizing trip frequencies, indirect utility functions are developed which include accessibility concepts. Behavioral implications of these concepts are proposed and contrasts are drawn to accessibility measures used in conventional segregated models of trip distribution, modal choice, and automobile ownership.Sensitivity analyses of alternative empirical definitions of accessibility in the choice model are conducted using data from the Detroit Regional Transportation and Land Use Study — covering counties in southeastern Michigan. These analyses employ a multinomial logit estimation technique and focus on definitions of trip attraction. Results of these analyses indicate that more complicated attraction measures can be replaced by measures involving the proportion of either urban area population or urban area employment within a traffic analysis zone. Also, evidence is found that decision-makers in the case study area consider trips of up to 60 or even 90 minutes duration when evaluating accessibilities offered by alternative public and private transportation systems.     

Promoting Public Transport Using Marketing Techniques in Mobility Management and Verifying their Quantitative Effects

Mobility management (MM) is a transportation management policy that uses “soft” measures to attempt to reduce car use and promote sustainable transportation modes such as public transport, bicycles, and walking. Using communication and other means, MM induces voluntarily change towards more sustainable transportation modes. We implemented MM marketing to promote an experimental community bus service. This project had two components: a questionnaire conducted in the service area and a monthly newsletter. The questionnaire was more than a survey; it also communicated information about the bus and helped promote bus use. One month after the survey, we implemented a follow-up survey targeting the initial survey respondents. Results suggest that the MM program produced a general increase in bus use, as well as mouth-to-mouth advertising, that helped promote bus use.     

Measuring post-disaster transportation system performance: the 1995 Kobe earthquake in comparative perspective

Recent earthquake disasters have caused major damage to transportation networks, leading to significant economic disruption. While this suggests the need to evaluate total system performance in transportation risk assessment, in addition to examining the vulnerability of individual components such as bridges, no appropriate measures currently exist. This paper develops post-disaster system performance measures and applies them to the urban rail and highway transportation systems in the Kobe, Japan, region devastated by the 1995 Hyogoken–Nanbu earthquake. Performance is evaluated in terms of network coverage and transport accessibility. Performance degradation was much more severe for highways and railways than for other lifeline infrastructure systems. Both transportation systems fared poorly in the disaster but service restoration proceeded much more rapidly for rail. The restoration of highway system performance correlated closely with the recovery of highway traffic volumes. The paper further develops a measure of subarea transport accessibility and applies this to Kobe’s constituent city wards. Results indicate substantial spatial disparity that is maintained throughout the restoration period. Comparisons with the 1989 Loma Prieta and 1994 Northridge earthquakes in the US show that although these disasters caused notable damage to highway bridges, system performance degradation was small in comparison with the Kobe experience. The paper argues that explicitly measuring transportation system performance can greatly facilitate both understanding the effects of historic disasters and preparing for future hazard events.