Impact analysis of cordon-based congestion pricing on mode-split for a bimodal transportation network

This paper investigates the impact of cordon-based congestion pricing scheme on the mode-split of a bimodal transportation network with auto and rail travel modes. For any given toll-charge pattern, its impact on the mode-split can be estimated by solving a combined mode-split and traffic-assignment problem. Using a binary logit model for the mode-split, the combined problem is converted into a traffic-assignment problem with elastic demand. Probit-based stochastic user equilibrium (SUE) principle is adopted for this traffic-assignment problem, and a continuously distributed value of time (VOT) is assumed to convert the toll charges and transit fares into time-units. This combined mode-split and traffic-assignment problem is then formulated as a fixed-point model, which can be solved by a convergent Cost Averaging method. The combined mode-split and traffic-assignment problem is then used to analyze a multimodal toll design problem for cordon-based congestion pricing scheme, with the aim of increasing the mode-share of public transport system to a targeted level. Taking the fixed-point model as a constraint, the multimodal toll design problem is thus formulated as a mathematical programming with equilibrium constraints (MPEC) model. A genetic algorithm (GA) is employed to solve this MPEC model, which is then numerical validated by a network example.     

TRESIS: A transportation,land use and environmental strategy impact simulator for urban areas

The Institute of Transport Studies has developed a Transportation and Environment Strategy Impact Simulator (TRESIS) as a decision support system to assist planners to predict the impact of transport strategies and to make recommendations based on those predictions. A key focus of the simulator is the richness of policy instruments such as new public transport, new toll roads, congestion pricing, gas guzzler taxes, changing residential densities, introducing designated bus lanes, implementing fare changes, altering parking policy, introducing more flexible work practices, and the introduction of more fuel efficient vehicles. The appropriateness of mixtures of policy instruments is gauged in terms of a series of performance indicators such as impacts on greenhouse gas emissions, accessibility, equity, air quality and household consumer surplus. In this paper we introduce TRESIS to the research community, focussing on the structure of the system and the diversity of applications. Applications are presented to illustrate the diversity and richness of TRESIS as a policy advisory tool.     

Preliminary results from an integrated transportation and land use models package

This paper describes the results, to date, of an effort to integrate a land use model with a transportation network model for the purpose of analyzing the interrelationships of transportation facility development and land development. In the system which has been developed each model provides input to, and receives feedbacks from, each other model. To the author's knowledge, the effort described here represents the first successful attempt to develop and test an integrated model package involving these reciprocal relationships. The results obtained from preliminary runs of this package should be of considerable interest to both transportation planners and land use planners. With this integrated system it has been possible to observe the interrelationships, and in particular the feedbacks, between land use and levels of traffic on the networks. Preliminary results indicate that congested networks produce tendencies toward metropolitan centralization. Attempts to relieve congestion seem to produce metropolitan decentralization and increased travel which lead, in turn, to metropolitan sprawl and increased spread of congestion.     

Towards integrated land use and transportation: A dynamic disequilibrium based microsimulation framework for built space markets

Investigating the factors and processes that influence the spatiotemporal distribution of built space and population in an urban area, plays an extremely important role in our greater understanding of the urban travel behaviour. Existing location of activity centres, especially home and work, strongly influences the short-term individual-level decisions such as mode of transportation, and long-term household-level decisions such as change in job and residential location. Conditions in the built space market also affect households’ and firms’ location and relocation decisions, and hence influence the general travel patterns in an urban area. In this context, this paper addresses a very important, but at the same time, not very widely investigated dimension that plays a key role in the evolution of built space and population distribution: Market. A disequilibrium based microsimulation modelling framework is developed for the built space markets. This framework is then used to operationalize the Greater Toronto and Hamilton Area’s owner-occupied housing market within Integrated Land Use Transportation and Environment (ILUTE) modelling system. Simulation results captured heterogeneity in the transaction prices, due to type of dwellings and different market conditions, in a very disaggregate fashion. The proposed methodology is validated by running the simulation from 1986 to 2006 and comparing the results with the historic data.     

A discrete-convex programming approach to the simultaneous optimization of land use and transportation

Three design problems are discussed in this article. First, it is shown that the network design problem with congestion reduces to an all-or nothing traffic assignment problem under some assumptions on the congestion function and the investment cost function. Second, the land use design problem is formulated as an extension of the Koopmans-Beckmann problem and a heuristic is proposed to solve this problem. Third, it is shown that the seemingly more complex problem of designing jointly a land-use plan and a transportation network reduces to a pure land-use design problem. All that is needed to solve the joint optimization problem is a shortest path algorithm and a heuristic to solve the land use design problem. Computational experience is reported for each algorithm.     

Characterization and evolution of spatial density patterns in urban areas

This paper examines the spatial patterns of population density, household automobile ownership and other socio-demographic variables that affect urban travel, as a function of distance from the central city core. Spatial density functions provide a useful characterization of urban structure, and of its evolution when taken at different time intervals. Analysis of the data from four case cities (Austin, Atlanta, Dallas, Phoenix) for 1960, 1970 and 1980 reveals continuing overall dispersion away from the traditional central core, accompanied by the densification of formerly low-density suburbs. This presents implications for high congestion levels in the densifying suburban communities, comparable to those typically associated with the CBD. In addition, the analysis has captured the continuing growth of average household automobile ownership and revealed a distinct spatial pattern that seems to be robust across the case areas considered, as well as within radial corridors in the one case that was so analyzed (Austin).List of symbols Y gross population density in census tractt - X _t distance in miles from the center of tract to the CBD - parameter representing the central business district density - y density gradient parameter - X₀, X₁, X2, and X3 locations of the knots in a three segment division of the x-axis - D_i dummy variable defined for thei-th segment - ₁ normally distributed disturbance term,a _i,b _i,c _i,d _i,i = 1, 2, 3 — parameters to be estimated - A _t area of census tractt     

Linking land use and transportation in a rapidly urbanizing context: A study in Delhi,India

Cities in developing countries like India are facing some of the same concerns that North American cities are: congestion and urban growth. However, there is a sense of urgency in cities like Delhi, India in that this growth is far more rapid as both urbanization and motorization are ongoing processes that have not yet peaked. In this paper, we examine land use change and its relationship with transportation infrastructure and other planning related variables in a spatial context. We estimate land use change models at two different scales from separate data. Cellular automation and Markov models were used to understand change at the regional scale and discrete choice models to predict change at the local level. The results suggest that land use in the Delhi metropolitan area is rapidly intensifying while losing variety. These changes are affected by industrial, commercial and infrastructure location and planners and policy-makers need to better understand the implications of location decisions. We also examine these results in the context of a policy framework for data-based planning that links land use and transportation models for Delhi.     

The optimal dispatching of taxis under congestion: A rolling horizon approach

Taxis make an important contribution to transport in many parts of the world, offering demand‐responsive, door‐to‐door transport. In larger cities, taxis may be hailed on‐street or taken from taxi ranks. Elsewhere, taxis are usually ordered by phone. The objective of a taxi dispatcher is to maximize the efficiency of fleet utilization. While the spatial and temporal distribution of taxi requests has in general a high degree of predictability, real time traffic congestion information can be collected and disseminated to taxis by communication technologies. The efficiency of taxi dispatching may be significantly improved through the anticipation of future requests and traffic conditions. A rolling horizon approach to the optimisation of taxi dispatching is formulated, which takes the stochastic and dynamic nature of the problem into account. Numerical experiments are presented to illustrate the performances of the heuristics, taking the time dependency of travel times and passenger arrivals into account.     

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     

The congestion multiplier: Variations in motorists’ valuations of travel time with traffic conditions

The value of travel time savings in part depends upon the disutility of the travel time that is saved and partly on the use to which the time saved is put. It has long been recognised that the disutility of the time spent travelling also depends upon a wide range of factors such as the journey length or the effort, comfort and safety associated with travelling.Hence we might expect the value of motorists’ travel time to vary with the traffic conditions as represented by the degree of congestion, in part to reflect the more difficult driving environment when there are more vehicles, but also a higher sense of frustration, similar to that associated with waiting time and contributing to its premium valuation.In this context, and despite the predominance of car travel in developed countries, the empirical evidence specifically relating to car values of travel time tends to fail to distinguish between different types of time according to the degree of congestion. Thus we are often left unclear as to precisely what type of time has been valued. Moreover, when a distinction is made, it tends to be into a simple dichotomy of congested and uncongested traffic.This paper provides new evidence on the variation in the valuation of motorists’ travel time savings across a finer gradation of types of time than has been hitherto attempted. This is obtained from the same Stated Choice exercise conducted in the United Kingdom and the United States. The paper also provides an extensive account of previous research into how congestion impacts on motorists’ values of time.     

Impacts of commuting efficiency on congestion and emissions: case of the Hamilton CMA, Canada

This study uses IMULATE (Integrated Model of Urban LAnd use, Transportation, energy and Emissions) to examine the impacts of commuting efficiency on congestion and automobile emissions—specifically, non-methane hydrocarbons, carbon monoxide and nitrogen oxides—in the Hamilton Census Metropolitan Area. Estimates of these externalities are compared for two commuting scenarios: a base scenario of estimated commuting flows for 1991 and an optimal scenario in which the mean commuting time for all workers is minimized. The findings indicate that significant reductions in congestion and automobile emissions are possible by advocating policies that encourage greater commuting efficiency in the locational choices of workers. The analysis of jobs–housing balance as one such means suggests that a considerable proportion of commuting cannot be explained by geographical imbalances in the distributions of jobs and housing, and that workers consider many factors besides commuting costs in their locational choices. It is concluded that policies promoting jobs–housing balance as the principal strategy for facilitating more efficient commuting may not meet the expectations of policy-makers.     

Biofuel refinery location and supply chain planning under traffic congestion

This research focuses on planning biofuel refinery locations where the total system cost for refinery investment, feedstock and product transportation and public travel is minimized. Shipment routing of both feedstock and product in the biofuel supply chain and the resulting traffic congestion impact are incorporated into the model to decide optimal locations of biofuel refineries. A Lagrangian relaxation based heuristic algorithm is introduced to obtain near-optimum feasible solutions efficiently. To further improve optimality, a branch-and-bound framework (with linear programming relaxation and Lagrangian relaxation bounding procedures) is developed. Numerical experiments with several testing examples demonstrate that the proposed algorithms solve the problem effectively. An empirical Illinois case study and a series of sensitivity analyses are conducted to show the effects of highway congestion on refinery location design and total system costs.     

Total cost analysis: An alternative to benefit-cost analysis in evaluating transportation alternatives

This paper explains the theory in support of total cost analysis (TCA) to compare transportation system alternatives. The full costs of each alternative are first aggregated, including travel time costs and monetizable environmental and social costs. Many costs which are considered on the benefits side of the equation in benefit-cost analysis (BCA) as "cost savings" are brought over to the costs side. Total cost differences among alternatives are then traded off against their estimated non-monetized benefits or impacts, just as a consumer trades off product quality against cost before deciding which product he or she will buy. One advantage of TCA over traditional BCA is that the concept of "total cost" is more easily understood by the public and by political decision-makers than BCA concepts such as "net present worth", "benefit-cost ratio" and "internal rate of return". A second advantage is that there is no suggestion that all "benefits" have been considered; decision-makers are free to use their own value judgements to trade off total cost against non-monetizable social, environmental and economic impacts, just as they trade off quality and convenience against cost when purchasing goods and services in their roles as consumers. The TCA approach is demonstrated in this paper through a case study of two systemwide alternatives for the Baltimore, MD urban area.     

A logit-based model for measuring the effects of transportation infrastructure on land value

Mutual interactions between transportation and land use have long been debated. Despite progress made in computational technology, the study of these interactions is not adequately developed. The most important aspect of such interactions is given by the changes in land values due to changes in transportation infrastructures. We consider the behavioural features of these interactions along with the constraints on the land and/or zoning restrictions and propose a reliable model for the first time to predict land value changes with respect to changes in transportation facilities and accessibility. The proposed model is a logit-based mathematical programming methodology where the relative price of land is predicted with respect to transportation accessibility, neighbourhood amenities, location premium, availability of land, and zoning regulations. A real-world case study is used to exhibit the applicability of the proposed methodology and demonstrate the efficacy of the algorithms and procedures.     

Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips

This paper analyzes transportation mode choice for short home-based trips using a 1999 activity survey from the Puget Sound region of Washington State, U.S.A. Short trips are defined as those within the 95th percentile walking distance in the data, here 1.40 miles (2.25 km). The mean walking distance was 0.4 miles (0.6 km). The mode distribution was automobile (75%), walk (23%), bicycle (1%), and bus (1%). Walk and bicycle are found less likely as the individual’s age increases. People are more likely to drive if they can or are accustomed to. People in multi-person families are less likely to walk or use bus, especially families with children. An environment that attracts people’s interest and provides activity opportunities encourages people to walk on short trips. Influencing people’s choice of transport mode on short trips should be an important part of efforts encouraging the use of non-automobile alternatives.

Active transportation and physical activity: opportunities for collaboration on transportation and public health research

Physically inactive lifestyles are a major public health challenge, and research in the transportation field on influences on the choice to walk and bike may provide guidance toward solutions. In the interests of promoting effective collaboration among the transportation, planning, and health fields, the current paper was written to fulfill three purposes. The first purpose was to summarize the transportation and planning studies on the relation between community design and non-motorized (“active”) transport and to interpret these studies from a health perspective. The second purpose was to summarize studies from the health literature that examine the relation between physical environmental variables and leisure-time physical activity that have relevance for transportation research. The third purpose was to promote more collaboration among transportation, planning, and health investigators by identifying opportunities for transdisciplinary research.     

New highways and land use change: Results from a quasi-experimental research design

Understanding links from new highway construction or capacity expansion to regional growth patterns is crucial for transportation planners and policy makers. In this paper, we incorporate a lagged adjustment regional growth model into a quasi-experimental research design to examine the association between new highway investments and land use change in three California counties. Our study areas provide a mix of urban, small town, and exurban highway projects in order to explore the different effects across project types and geographic contexts. The central finding of this research is that while improvements in surface transportation infrastructure can have large impacts on growth patterns, the nature of the effect depends on the context of the highway investment.     

The relationship between land use and intrazonal trip making behaviors: Evidence and implications

This paper addresses the relationship between land use, destination selection, and travel mode choice. Specifically, it focuses on intrazonal trips, a sub-category of trip making where both trip origin and trip destination are contained in the same geographic unit of analysis, using data from the 1994 Household Activity and Travel Diary Survey conducted by Portland Metro. Using multinomial logit and binary logistic models to measure travel mode choice and decision to internalize trips, the evidence supports the conclusions that (1) intrazonal trips characteristics suggest mode choice for these trips might be influenced by urban form, which in turn affects regional trip distribution; (2) there is a threshold effect in the ability of economic diversity/mixed use to alter travel behavior; and (3) greater emphasis to destinations within the area where an individual’s home is located needs to be given in trip distribution models.