Michiel C.J. Bliemer

Constructing Efficient Stated Choice Experimental Designs

Abstract Stated choice (SC) experiments are often used in transportation studies for estimating and forecasting behaviour of travellers, road authorities, etc. This kind of experiment relies on underlying experimental designs. Whilst orthogonal designs are mainstream for practitioners, many researchers now realize that so‐called efficient designs are able to produce more efficient data in the sense that more reliable parameter estimates can be achieved with an equal or lower sample size. This paper describes several processes for generating SC experiments and is intended to give an overview of the current state‐of‐the‐art. Different methods are described.

Approximation of Bayesian efficiency in experimental choice designs

This paper compares different types of simulated draws over a range of number of draws in generating Bayesian efficient designs for stated choice (SC) studies. The paper examines how closely pseudo Monte Carlo, quasi Monte Carlo and Gaussian quadrature methods are able to replicate the true levels of Bayesian efficiency for SC designs of various dimensions. The authors conclude that the predominantly employed method of using pseudo Monte Carlo draws is unlikely to result in leading to truly Bayesian efficient SC designs. The quasi Monte Carlo methods analysed here (Halton, Sobol, and Modified Latin Hypercube Sampling) all clearly outperform the pseudo Monte Carlo draws. However, the Gaussian quadrature method examined in this paper, incremental Gaussian quadrature, outperforms all, and is therefore the recommended approximation method for the calculation of Bayesian efficiency of SC designs.

Quasi-variational inequality formulation of the multiclass dynamic traffic assignment problem ☆

We consider the extension of a single user-class macroscopic dynamic traffic assignment model to include multiple user-classes. The distinction between user-classes is typically based on vehicle characteristics, e.g. cars and trucks. Interactions between the user-classes sharing the same road infrastructure are taken into account. To deal with various different asymmetries that may occur, such as interuser-class interaction, interspatial and intertemporal asymmetries, the model is specified as a (quasi) variational inequality problem. A nested modified projection method is proposed to solve the assignment problem. The solution of the problem depends heavily on the choice of some very important input: the multiclass link travel time functions. Under mild restrictions there exists a solution, which needs however not be unique. A case study illustrates the model.

Dynamic Queuing and Spillback in Analytical Multiclass Dynamic Network Loading Model

A new analytical multiclass dynamic network loading (DNL) model is proposed as part of a simulation-based dynamic traffic assignment (DTA) model. In contrast to many other proposed DNL models, this model explicitly deals with queuing and spillback without relying on link travel time functions as input. Different vehicle types (e.g., cars and trucks) are considered with different speeds. Use of link travel times is likely to under-or overestimate the true travel times in a dynamic model if queues are considered. The proposed DNL model consists of a link model and a node model. The link model computes queue inflows and potential outflows, whereas the node model determines the actual outflows depending on the node structure. In the end, the link travel times are computed backward in time for each vehicle type separately. The model has been implemented in the Indy DTA software, and an application shows that the approach is viable in real-life networks.

Optimal Toll Design Problem in Dynamic Traffic Networks with Joint Route and Departure Time Choice

Road pricing is one of the market-based traffic control measures that can influence travel behavior to alleviate congestion on roads. This paper addresses the effects of uniform (constant, fixed) and time-varying (step) tolls on the travel behavior of users on the road network. The problem of determining optimal prices in a dynamic traffic network is considered by applying second-best tolling scenarios imposing tolls only to a subset of links on the network and considering elastic demand. The optimal toll design problem is formulated as a bilevel optimization problem with the road authority (on the upper level) setting the tolls and the travelers (on the lower level) who respond by changing their travel decisions (route and departure time choice). To formulate the optimal toll design problem, the so-called mathematical program with equilibrium constraints (MPEC) formulation was used, considering the dynamic nature of traffic flows on the one hand and dynamic pricing on the other. Until now, the MPEC formu...

Impact of Route Choice Set on Route Choice Probabilities

Predictions of route flows in networks are sensitive to the route choice model applied as well as to the route choice sets on which the choice models operate. Studies have shown that there is a significant impact of size and composition of route sets on estimation performance of route choice models in terms of estimated parameter values and model quality. These studies have looked at an aggregate level of modeling quality, but a better insight into the causes of the impacts requires a more detailed analysis of modeling quality at the level of choice prediction of individual routes. This paper addresses the issue of prediction quality of route choice in networks at a very detailed level in dependence of the size and composition of predefined route sets. For better control of experimental conditions, a small hypothetical network and generated trip data were used in combination with a systematic variation of size and composition of route sets so that all relevant properties of routes and route sets are known. A range of well-known route choice models was applied to study in a comparative way their sensitivity in predicting route choice probabilities as a function of the choice set properties. Most route choice models do not appear to have sufficient robustness of choice prediction at the level of individual routes.

Patients’ and urologists’ preferences for prostate cancer treatment: a discrete choice experiment

Background:Patients’ preferences are important for shared decision making. Therefore, we investigated patients’ and urologists’ preferences for treatment alternatives for early prostate cancer (PC).Methods:A discrete choice experiment was conducted among 150 patients who were waiting for their biopsy results, and 150 urologists. Regression analysis was used to determine patients’ and urologists’ stated preferences using scenarios based on PC treatment modality (radiotherapy, surgery, and active surveillance (AS)), and risks of urinary incontinence and erectile dysfunction.Results:The response rate was 110 out of 150 (73%) for patients and 50 out of 150 (33%) for urologists. Risk of urinary incontinence was an important determinant of both patients’ and urologists’ stated preferences for PC treatment (P<0.05). Treatment modality also influenced patients’ stated preferences (P<0.05), whereas the risk of erectile dysfunction due to radiotherapy was mainly important to urologists (P<0.05). Both patients and urologists preferred AS to radical treatment, with the exception of patients with anxious/depressed feelings who preferred radical treatment to AS.Conclusion:Although patients and urologists generally may prefer similar treatments for PC, they showed different trade-offs between various specific treatment aspects. This implies that urologists need to be aware of potential differences compared with the patient’s perspective on treatment decisions in shared decision making on PC treatment.

EVAQ: A New Analytical Model for Voluntary and Mandatory Evacuation Strategies on Time-varying Networks

The analytical evacuation network model EVAQ enables forecasting traffic flow conditions on a road network for a wide range of emergency situations, such as hurricanes, bushfires and floods. The proposed model is innovative as it combines voluntary evacuation, with possible pre-trip and enroute decisions, and mandatory evacuation, with prescribed destinations, routes and departure times, within a single generic model framework. Furthermore, we introduce dynamic road infrastructure, in which characteristics such as speed limits, capacity and flow direction can be time-varying due to the hazards progress in space and time and prevailing traffic regulations and control measures. The evacuation model can function as a decision support system for regional authorities and emergency services supervising an evacuation or constructing an evacuation strategy for planning purposes.

Dynamic road pricing for optimizing network performance with heterogeneous users

In transport networks, travelers individually make route and departure time choice decisions that may not be optimal for the whole network. By introducing (time-dependent) tolls the network performance may be optimized. In the paper, the effects of time-dependent tolls on the network performance are analyzed using a dynamic traffic model. The network design problem is formulated as a bi-level optimization problem in which the upper level describes the network performance with chosen toll levels while the lower level describes the dynamic network model including user-specific route and departure time choice and the dynamic network loading. In case studies on a simple hypothetical network it is shown that network improvements can be obtained by introducing tolls. It is also shown that finding a global solution to the network design problem is complex as it is non-linear and non-convex.

Modelling Externalities using Dynamic Traffic Assignment Models: A Review

Recently, there has been a growing interest in externalities in our society, mainly in the context of climate and air quality, which are of importance when policy decisions are made. For the assessment of externalities in transport, often the output of static traffic assignment models is used in combination with so-called effect models. Due to the rapidly increasing possibilities of using dynamic traffic assignment (DTA) models for large-scale transportation networks and the application of traffic measures, already several models have been developed to assess the externalities using DTA models more precisely. Different research projects have shown that there is a proven relation between the traffic dynamics and externalities, such as emissions of pollutants and traffic safety. This means that the assessment of external effects can be improved by using temporal information about flow, speed and density, which is the output of DTA models. In this paper, the modelling of traffic safety, emissions and noise in conjunction with DTA models is reviewed based on an extensive literature survey. This review shows that there are still gaps in knowledge in assessing traffic safety, much research is available concerning emissions, and although little research has been conducted concerning the assessment of noise using DTA models, the methods available can be used to assess the effects. Most research so far has focused on the use of microscopic models, while mesoscopic or macroscopic models may have a high potential for improving the assessment of these effects for larger networks.