A dynamic evacuation model for pedestrian–vehicle mixed-flow networks

In urban emergency evacuation, a potentially large number of evacuees may depend either on transit or other modes, or need to walk a long distance, to access their passenger cars. In the process of approaching the designated pick-up points or parking areas for evacuation, the massive number of pedestrians may cause tremendous burden to vehicles in the roadway network. Responsible agencies often need to contend with congestion incurred by massive vehicles emanating from parking garages, evacuation buses generated from bus stops, and the conflicts between evacuees and vehicles at intersections. Hence, an effective plan for such evacuation needs to concurrently address both the multi-modal traffic route assignment and the optimization of network signal controls for mixed traffic flows. This paper presents an integrated model to produce the optimal distribution of vehicle and pedestrian flows, and the responsive network signal plan for massive mixed pedestrian–vehicle flows within the evacuation zone. The proposed model features its effectiveness in accounting for multiple types of evacuation vehicles, the interdependent relations between pedestrian and vehicle flows via some conversion locations, and the inevitable conflicts between intersection turning vehicle and pedestrian flows. An illustrating example concerning an evacuation around the M&T stadium area has been presented, and the results indicate the promising properties of our proposed model, especially on reflecting the complex interactions between vehicle and pedestrian flows and the favorable use of high-occupancy vehicles for evacuation operations.     

Addendum to “a comparison of heuristics for a school bus scheduling problem”

Given a group of one or more schools, each with a specific arrival time window, and the bus routes serving these schools, the problem is to create an optimum set of combinations of routes to be served by a single bus, where optimality is defined in terms of fleet size and deadhead travel distance. We present the results of a computational study comparing ten heuristics, adapted from procedures which have appeared in the literature, on a set of 30 test problems derived from actual school data. This study is a follow on to that reported in Graham and Nuttle (1986).     

Simulation–optimization model for location of a public electric vehicle charging infrastructure

The paper develops a simulation–optimization model that determines where to locate electric vehicle chargers to maximize their use by privately owned electric vehicles. Applying this model to the central-Ohio region, we demonstrate that a combination of level-one and -two chargers is preferable to level-two chargers only. We further explore interactions between the optimization criterion used and the budget available. We finally show that although the optimal location is sensitive to the specific optimization criterion considered, overall service levels are less sensitive to the optimization strategy.     

Financial appraisals of a microcomputer‐based referencing system for a local bus travel telephone enquiry service

Abstract

Solution of current and future transportation problems requires a more consistent and complete realization of the principles of socioeconomic motivation in research and practical work. With this aim it is suggested that a transport‐communication model (TCM) of society should be constructed as a projection of all the social processes into the space of artificial flows of matter, energy and information. A simplified example of a transport‐communication systems model in terms of mathematical systems theory is reviewed, demonstrating the constructs of such an approach, and a critical analysis is made of scientific paradigms, used in the transportation theory. The author suggests an iterative procedure for the formation of a hierarchic theory of transportation systems based on simulation concepts and experiments, and formulates a hypothesis of its feasibility in the construction of present‐day transportation theory as a realistic basis for solving transportation problems.     

Exact and grid-free solutions to the Lighthill–Whitham–Richards traffic flow model with bounded acceleration for a class of fundamental diagrams

In this article, we propose a new exact and grid-free numerical scheme for computing solutions associated with an hybrid traffic flow model based on the Lighthill–Whitham–Richards (LWR) partial differential equation, for a class of fundamental diagrams. In this hybrid flow model, the vehicles satisfy the LWR equation whenever possible, and have a constant acceleration otherwise. We first propose a mathematical definition of the solution as a minimization problem. We use this formulation to build a grid-free solution method for this model based on the minimization of component function. We then derive these component functions analytically for triangular fundamental diagrams, which are commonly used to model traffic flow. We also show that the proposed computational method can handle fixed or moving bottlenecks. A toolbox implementation of the resulting algorithm is briefly discussed, and posted at https://dl.dropbox.com/u/1318701/Toolbox.zip.     

A generalized sensor location model for the estimation of network origin–destination matrices

This study examined the network sensor location problem by using heterogeneous sensor information to estimate link-based network origin–destination (O–D) demands. The proposed generalized sensor location model enables different sensors’ traffic monitoring capabilities to be used efficiently and the optimal number and deployment locations of both passive- and active-type sensors to be determined simultaneously without path enumeration. The proposed sensor location model was applied to solve the network O–D demand estimation problem. One unique aspect of the proposed model and solution algorithms is that they provide satisfactory network O–D demand estimates without requiring unreasonable assumptions of known prior information on O–D demands, turning proportions, or route choice probabilities. Therefore, the proposed model and solution algorithms can be practically used in numerous offline transportation planning and online traffic operation applications.     

A merging–giveway interaction model of cars in a merging section: a game theoretic analysis

In many past studies dealing with traffic phenomena in merging or weaving sections, only the influence of through traffic on the behavior of a merging car is considered in the analysis. It is, however, often seen that a through car, which runs on the most outside lane, takes a cooperative motion for the merging car called “giving way” by moving to the adjacent lane. That is, both the merging car and the through car affect one another. Because their influence is not independent from one another, it should be jointly treated in the analysis as “interaction”. This behavior is typical in merging sections, and is a dominant factor forming the traffic phenomena in a section of this type. This study develops a game theoretical model to describe the traffic behavior of a pair of merging and through cars, while explicitly considering the interaction between them. Both the merging and through cars attempt to take the best actions for themselves by forecasting the other’s action, respectively. Such a behavior is modeled as a two-person non-zero-sum non-cooperative game. Through a case study with data analysis of videotaped observation, the proposed model can be used to obtain an understanding of traffic behavior at on-ramp merging sections. ©     

A model of managers’ preferences for location of freight facilities

The paper reviews the need for a better understanding of the factors which affect the location of freight facilities, such as depots, terminals, freight forwarding centres, distribution centres, etc. The development of an Elimination by Aspects (EBA) model to analyse such location decisions by the managers of freight firms is described. The results are shown to be comparable (perhaps even superior to) those obtained with a logit model. Conclusions are drawn with respect to both the use of the EBA model to analyse freight facility location preference, and the factors which affect such preference. Five factors were found to be significant: closeness to existing customers, closeness to arterial roads, availability of suitable sites, cost of truck fleet operation, and closeness to labor.     

Comparative effects of eco-driving initiatives aimed at urban bus drivers – Results from a field trial

A field trial is used to investigate effects of two programmes aimed at encouraging bus drivers to develop and maintain ecological driving behaviour. Drivers on one bus line were divided into three groups, one received feedback from an in-vehicle system, the second received the same feedback coupled with personal training sessions, and the third acting as a control. A 6.8% fuel saving and large decreases in instances of harsh deceleration and speeding were found, but with no difference in the effect of the two eco-driving strategies. The drivers reported perceived gains in theoretical knowledge of eco-driving, but found it more difficult to put that knowledge into practice. Several contextual factors were found to limit drivers’ to eco-driving, most noticeably shaped by their work tasks, but also the commitment of the company where they were employed.     

A bi-level model for GHG emission charge based on a continuous distribution of travelers’ value of time (VOT)

Transportation is an important source of greenhouse gas (GHG) emissions. In this paper, we develop a bi-level model for GHG emission charge based on continuous distribution of the value of time (VOT) for travelers. In the bi-level model framework, a policy maker (as the leader) seeks an optimal emission charge scheme, with tolls differentiated across travel modes (e.g., bus, motorcycles, and cars), to achieve a given GHG reduction target by shifting the proportions of travelers taking different modes. In response, travelers (as followers) will adjust their travel modes to minimize their total travel cost. The resulting mode shift, hence the outcome of the emission charge policy, depends on travelers’ VOT distribution. For the solution of the bi-level model, we integrate a differential evolution algorithm for the upper level and the “all or nothing” traffic assignment for the lower level. Numerical results from our analysis suggest important policy implications: (1) in setting the optimal GHG emission charge scheme for the design of transportation GHG emission reduction targets, policy makers need to be equipped with rigorous understanding of travelers’ VOT distribution and the tradeoffs between emission reduction and system efficiency; and (2) the optimal emission charge scheme in a city depends significantly on the average value of travelers’ VOT distribution—the optimal emission charge can be designed and implemented in consistency with rational travel flows. Further sensitivity analysis considering various GHG reduction targets and different VOT distributions indicate that plausible emission toll schemes that encourage travelers to choose greener transportation modes can be explored as an efficient policy instrument for both transportation network performance improvement and GHG reduction.     

A network‐based model for estimating the market share of a new high‐speed rail system

This paper presents a novel application of static traffic assignment methods, but with a variable time value, for estimating the market share of high‐speed rail (HSR) in the northwest–southeast (NW–SE) corridor of Korea currently served by air, conventional rail and highway modes. The proposed model employs a time–space network structure to capture the interrelations among competing transportation modes, and to reflect their supply‐ and demand‐side constraints as well as interactions through properly formulated link‐node structures. The embedded cost function for each network link offers the flexibility for incorporating all associated factors, such as travel time and fare, in the model computation, and enables the use of a distribution rather than a constant to represent the time–value variation among all transportation mode users. To capture the value‐of‐time (VOT) of tripmakers along the target corridor realistically, this study has developed a calibration method with aggregate demand information and key system performance data from the NW–SE corridor.     

Understanding the effects of travel demand management on metro commuters’ behavioural loyalty: a hybrid choice modelling approach

Transportation - As part of efforts to promote sustainable mobility, many cities are currently experiencing the rapid expansion of their metro network. The consequent growth in ridership motivates...     

Towards a microeconomic framework for modelling the joint choice of activity–travel behaviour and ICT use

The rapid development of information and communication technologies (ICT) has been argued to affect time use patterns in a variety of ways, with consequent impacts on travel behaviour. While there exists a significant body of empirical studies documenting these effects, theoretical developments have lagged this empirical work and in particular, microeconomic time allocation models have not to date been fully extended to accommodate the implications of an increasingly digitised society. To address this gap, we present a modelling framework, grounded in time allocation theories and the goods–leisure framework, for joint modelling of the choice of mode of activity (physical versus tele-activity), travel mode and route, and ICT bundle. By providing the expression for a conditional indirect utility function, we use hypothetical scenarios to demonstrate how our framework can conceptualise various activity–travel decision situations. In our scenarios we assume a variety of situations such as the implications of severe weather, the introduction of autonomous vehicles, and the interaction between multiple decision makers. Moreover, our approach lays the microeconomic foundations for deriving subjective values of ICT qualities such as broadband speed or connection reliability. Finally, we also demonstrate the means by which our framework could be linked to various data collection protocols (stated preference exercises, diaries of social interactions, laboratory experiments) and modelling approaches (discrete choice modelling, hazard-based duration models).     

On allowing a general form for unobserved heterogeneity in the multiple discrete–continuous probit model: Formulation and application to tourism travel

This paper proposes a new econometric formulation and an associated estimation method for a finite discrete mixture of normals (FDMN) version of the multiple discrete–continuous probit (MDCP) model. To our knowledge, this is the first such formulation and application of an MDCP model in the econometric literature. Using the New Zealand Domestic Travel Survey data set, the model is applied to analyze individual-level decisions regarding recreational destination locations and the number of trips to each destination. The results provide insights into the demographic and other factors that influence individuals’ preferences for different destinations, and show that the FDMN MDCP model is able to identify different segments of the sample, each one of them with different effects of the exogenous variables on destination choice.     

Nonlinear multivariate time–space threshold vector error correction model for short term traffic state prediction

We propose Time–Space Threshold Vector Error Correction (TS-TVEC) model for short term (hourly) traffic state prediction. The theory and method of cointegration with error correction mechanism is employed in the general design of the new statistical model TS-TVEC. An inherent connection between mathematical form of error correction model and traffic flow theory is revealed through the transformation of the well-known Fundamental Traffic Diagrams. A threshold regime switching framework is implemented to overcome any unknown structural changes in traffic time series. Spatial cross correlated information is incorporated with a piecewise linear vector error correction model. A Neural Network model is also constructed in parallel to comparatively test the effectiveness and robustness of the new statistical model. Our empirical study shows that the TS-TVEC model is an effective tool that is capable of modeling the complexity of stochastic traffic flow processes and potentially applicable to real time traffic state prediction.     

CO2 emissions: Are land-use changes enough for California to reduce VMT? Specification of a two-part model with instrumental variables

With vehicle miles of travel increasing at a faster pace than population, one strategy being actively pursued by both state and local governments is compact development. California recently passed legislation that aggressively promotes sustainability by endorsing and rewarding compact development. Likewise, the California Air Resources Board has set a statewide reduction target of 5MMT of greenhouse gas reductions from land use, based largely on achieving compact development patterns. In this paper, we use a multivariate two-part model with instrumental variables, which corrects for residential location self-selection bias. We use a much larger and more geographically representative travel survey on household travel patterns and socio-economic characteristics than represented in previous California studies; this allows us to robustly consider other influences on travel. Our results indicate that, all else equal, a 10% in residential density would reduce VMT by 1.9%. This elasticity is larger than the reported in previous econometric studies for the US, and specifically for California. However, as we show, the magnitude of this impact is still low considering reasonable ranges for policies aimed to increase residential density.     

Level of service design concept for airport passenger terminals—a European view

Drawing from the experiences of highway and pedestrian planning, the author suggests a method of improving the method of designing airport terminals. The improved technique would use the concept of level of service to indicate the interaction of time with space provision.     

Estimating origin‐destination matrices from link volume counts: a simple intercity auto travel demand model for Sri Lanka

The cost of nation wide travel surveys is high. Hence in many developing countries, planners have found it difficult to develop intercity transportation plans due to the non availability of origin‐destination trip matrices. This paper will describe a method for the intercity auto travel estimation for Sri Lanka with link traffic volume data.

The paper outlines the rationale of selecting the district capitals of Sri Lanka as its “cities,” the methodology for selecting the intercity road network, determination of link travel times from express bus schedules and the location of link volume counting positions.

Initially, the total auto travel demand model is formulated with various trip purpose sub‐models. This model is finally modified to a simple demand model with district urban population and travel times between city pairs as the exogenous variables, to overcome statistical estimation difficulties. The final demand model has statistics within the acceptable regions.

The advantages of a simple model are discussed and possible extensions are proposed.     

Origin–destination missing data estimation for freight transportation planning: a gravity model-based regression approach

This paper develops a log-linear regression approach to estimate missing data in a sparse origin–destination (O–D) matrix assuming the sampled or observed O–D trips follow a good gravity pattern. The approach is tested with randomly selected samples from the known portions of 1997, 2002, and 2007 US Commodity Flow Survey (CFS) O–D value and tonnage matrices and validated with 2007 US O–D tonnage matrix at the state level. The missing data are also estimated for the 2007 CFS tonnage matrix with the best intercept and coefficients obtained using all known entries of the matrix. The concept of the approach can be extended beyond the gravity model to any strong mathematical pattern embedded in the known set of a sparse O–D matrix to estimate its missing cells.