Transportation Systems and Service Policy: A Project-Based Introduction

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For example, parental concern about traffic safety is especially important for children traveling as pedestrians or cyclists Johansson, ; Ewing et al. Also, infrastructure can indirectly influence the decision of the parents through the perception of neighborhood safety and traffic, and also about transportation options available at home, as seen in Nevelsteen et al. This is corroborated in some works that initially did not consider the perception of safety but ultimately recommended the need to include this variable to improve the performance of the models and the analyses derived from them.

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For example, Tam et al. There are several works that consider latent variables related to safety, but did not prove these variables statistically significant in all cases. For example, Vredin Johansson et al. They further stated that mixing public safety indicators with traffic safety could not have contributed to the significance of the variable. Also, Yang et al.

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However, as explained, it does not mean that safety considerations are not important in the choice of mode. Indicators of safety perception. Latent variables represent characteristics of individuals Walker, ; Ashok et al. Indicators are introduced to characterize latent and unobserved variables and, econometrically, allow their identification, providing, in addition, greater efficiency in estimating the full model Kim et al.

Thus, indicators of latent variables are proposed in the surveys as questions or statements about attitudes, perceptions and memory. Statistically, indicators have the particularity of being endogenous to the choice process and therefore are not used by the model in the predictive mode Walker, ; Rungie et al. Perhaps, for that reason, sufficient attention has not been paid to the design of indicators in the contexts of transport choice. In fact, it is common to construct indicators of latent variables based on open questions or satisfaction surveys, which sometimes accompany stated preference surveys, without further consideration of the appropriateness or not of such questions.

Another work that has built indicators from complementary questions to the stated preference surveys, without considering a previous design, can be seen in Marquez et al. The concern of how the measurement methods of indicators affect the analysis of the choice process was manifested by Ben-Akiva et al. It must not forget that the estimation of the models depends on the indicators used as process causal variables Walker, ; therefore, the selection of indicators should not be a trivial task.

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Not all studies report the indicators used to measure perceptions of safety. For example, the work of Yang et al. However, some studies have stated the construction of indicators based on questions on the use of safety equipment Vredin Johansson et al. Studies such as Tsirimpa et al. In general, indicators are formulated as statements in terms of: "For me, using a car to go to work is It could be seen that the systems of measurement indicators almost always include one of three types: rating scales, hierarchy and discrete choice.

Specifically, the indicators used to measure the perception of safety have changed as follows: 5 points, from not important to very important Daziano, It can show that there is no standard to measure perceptions, although some outstanding patterns can be identified, for example, it is more common to use 5-point scales. It can also be seen that three types of indicators have typically been used: quality bad It is necessary to take into account that when studying the consequences of the type of indicator chosen, Raya found that although initial assessments showed no significant differences, the effects on the variables can be very important because each indicator has specific characteristics, concluding that the use of an unsuitable indicator can be misleading.

Another important issue regarding the indicators is associated with standardization. In this regard, McFadden et al. McFadden et al. Objective factors. While socioeconomic variables and attributes of transportation alternatives have been key elements in most of the models used by transportation planners and support decision-making Shiftan et al.

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Glerum et al. According to the tenets of Manheim , changes in the transport system have impacts on travel patterns. However, in the context of hybrid choice models such impacts are not typically modeled as generally specifying structural equations usually considered economic characteristics of individuals, but not objective factors.

In general, there is enough literature regarding forecast based on latent variable models that consider only socioeconomic variables see for example Vredin Johansson et al. However, not much progress has been made with respect to the problem of studying those cases where a policy changed perceptions; this is an issue that has not received adequate attention so far. To explore the methods used in the analysis of transport policies, Di Ciommo et al.

Clearly, the second method is aimed at assessing the acceptability of the measure either before or after application through stated preference surveys or revealed. More recently, in the context of bike trips, Habib et al. They found that it is important consider the perceptions of people in developing programs to promote cycling and to formulate strategies to maximize the effectiveness of such programs. Specifically, they concluded that greater provision of infrastructure for bike lanes in neighborhoods can increase the perception of safety, resulting in a greater likelihood that residents choose this transportation alternative.

In the same vein, Maldonado-Hinarejos et al. Also, it is used to compare the impact of "hard" policies, such as providing parking facilities; with respect to "soft" policies, such as programs promoting the use of bicycles. Influence of other latent variables on the safety perception. It has been shown that the perception of information influences the behavior of individuals.

For example, Tsirimpa et al. McFadden had suggested that the main cognitive abnormalities in the framework of utility theory came from the way individuals store, retrieve and process information.

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In this sense, it is well known that the utility of choice of an individual is based on socioeconomic characteristics and psychological factors Ben-Akiva et al. Another factor that influences the perception of safety has not been studied sufficiently and is related to traffic threats that may concern e. Specific situations such as serious traffic problems are perceived by individuals as a threat that could affect the perception of safety and consequently transportation choices. The review of the state of the art has identified three gaps.

First, although it is possible to estimate hybrid models based on questions of any kind as indicators, research is needed to determine the most appropriate indicators to study the perceptions of safety in transport choices. It is relevant to assess the influence that indicators and the chosen scale have in assessing the safety perception. Secondly, there is still a gap in the use of hybrid models for predictive purposes for the evaluation of policies related to safety. What is common has been to specify socioeconomic variables, with the limitation that such specification would only assess situations which produce changes in the In this context, it would be desirable to construct a methodological framework for the econometric modeling of the influence that safety perceptions have on the behavior of transport users regarding measuring instruments, including objective factors and the effect of the information.

To this end, it is considered that in addition the development of studies in specific contexts of choice, it will be possible to build and validate this methodological framework. In any case, it will be necessary to at least develop the following activities: study of the behavior assumptions underlying the choices; development of econometric modeling framework involving perceptions and the influence that it has on the characteristics of individuals and objective factors; design of appropriate tools to assess the influence of the perception of safety; calibration of choice models, latent variables and categories or latent classes, and drawing conclusions from the modeling.

References Abou-Zeid, M. The effect of social comparisons on commute well-beling. Adams, J. Evaluating the effectiveness of road safety measures.

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Traffic Engineering and Control, 21 6 , Akaateba, M. Traffic safety violations in relation to drivers' educational attainment, training and experience in Kumasi, Ghana. Safety science , 75 , Ashok, K.

Extending discrete choice models to incorporate attitudinal and other latent variables. Journal of Marketing Research , 39 1 , Bacon, L. Augmenting discrete-choice data to identify common preference scales for inter-subject analyses. Quant Mark Econ, 10 4 , Ben-Akiva, M.

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Extended Framework for Modeling Choice Behavior. Marketing Letters, 10 3 , Hybrid Choice Models: Progress and Challenges. Marketing Letters , 13 3 , Bolduc, D. Hybrid choice models with logit kernel: applicability to large scale models. In, M. Lee-Gosselin, S. Doherty Eds. Hybrid choice modelling of new technologies for car choice in Canada.