Hybrid route choice model incorporating latent cognitive effects of real-time travel information using physiological data

The proliferation of information systems is enabling drivers to receive en route real-time travel information, often from multiple sources, for making informed routing decisions. A robust understanding of route choice behavior under information provision can be leveraged by traffic operators to design information and its delivery systems for managing network-wide traffic. However, most existing route choice models lack the ability to consider the latent cognitive effects of information on drivers and their implications on route choice decisions. This paper presents a hybrid route choice modeling framework that incorporates the latent cognitive effects of real-time information and the effects of several explanatory variables that can be measured directly (i.e., route characteristics, information characteristics, driver attributes, and situational factors). The latent cognitive effects are estimated by analyzing drivers’ physiological data (i.e., brain electrical activity patterns) measured using an electroencephalogram (EEG). Data was collected for 95 participants in driving simulator experiments designed to elicit realistic route choices using a network-level setup featuring routes with different characteristics (in terms of travel time and driving environment complexity) and dynamic ambient traffic. Averaged EEG band powers in multiple brain regions were used to extract two latent cognitive variables that capture driver’s cognitive effort during and immediately after the information provision, and cognitive inattention before implementing the route choice decision. A Multiple Indicators Multiple Causes model was used to test the effects of several explanatory factors on the latent cognitive variables, and their combined impacts on route choice decisions. The study results highlight the significant effects of driver attributes and information characteristics on latent cognitive effort and of route characteristics on latent cognitive inattention. They also indicate that drivers who are more attentive and exert more cognitive effort are more likely to switch from their current route by complying with the information provided. The study insights can aid traffic operators and information service providers to incorporate human factors and cognitive aspects while devising strategies for designing and disseminating real-time travel information to influence drivers’ route choices.     

Developing a Brief Sensation Seeking Scale for Children: Establishing Concurrent Validity With Video Game Use and Rule-Breaking Behavior

Despite the importance of life-cycle models to sensation seeking research, past studies have typically focused on adolescents and adults. This is especially problematic for researchers studying the role of media use in the development of risky behaviors (e.g., violent video game consumption and aggressive behavior). To facilitate research with child populations, a brief sensation seeking scale for children (BSSS-C) is developed and validated with a sample of fourth, fifth, and sixth graders (N = 136). The BSSS-C is found to be internally reliable (α = .82) as well as a strong predictor of several risky child behaviors. Higher sensation seeking children were more likely to play video games, including violent subgenres (e.g., shooters), and to enjoy playing video games that contained specific acts of violence (e.g., weapon use). Higher sensation seekers were also more likely to engage in rule-breaking behavior, such as bringing prohibited cell phones to school. The results suggest that sensation seeking may be related to risky behavior at a very young age.     

Staying on or getting off the sidewalk? Testing the Mehrabian-Russell Model on pedestrian behavior

Social and environmental psychology provide a variety of models based on which to understand how built environments can elicit people’s behavioral responses. The Mehrabian-Russell model (MRM), initially presented in 1974, provides a framework that explains avoid–approach behavior towards a place based on a primary emotional response (PER) and affective states elicited by the perceived stimuli from the environment. However, despite the potential applications of the MRM in travel behavior studies, traditional models (e.g., discrete choice models and integrated choice latent variable) do not incorporate this specific psychological process that converts environmental stimuli into behavioral responses. Hence, this paper aims to test the applicability of MRM to urban sidewalks. To fulfill this objective, we developed a two-level structural equation model using latent variables (LV) identified from a confirmatory factor analysis (CFA) based on 1056 in-person surveys on 30 different sidewalks in Bogotá, Colombia. We then evaluated the effect of the PER on declared avoidance as a proxy of behavioral intention. The CFA uncovered three LV equivalent to the three affective dimensions of the MRM—arousal, pleasure, and dominance—followed by a fourth LV, representing the PER, which explains the three previous LVs. This confirms the applicability of these kinds of psychological and environmental models in pedestrian behavior evaluation. We found that PER can explain the declared intention of avoidance towards the sidewalk in an urban setting. Proving that this kind of model can explain the way in which the built environment can elicit pedestrians’ emotional responses and subsequent behaviors, provides information that can be used as input in travel behavior studies focusing on the promotion of active traveling and mode change.     

Closing the gap between behavior and models in route choice: The role of spatiotemporal constraints and latent traits in choice set formation

A considerable gap exists between the behavioral paradigm of choice set formation in route choice and its representation in route choice modeling. While travelers form their viable choice set by retaining routes that satisfy spatiotemporal constraints, existing route generation techniques do not account for individual-related spatiotemporal constraints. This paper reduces the gap by proposing a route choice model incorporating spatiotemporal constraints and latent traits. The proposed approach combines stochastic route generation with a latent variable semi-compensatory model representing constraint-based choice set formation followed by compensatory choice. The model is applied to data focusing on habitual commuting route choice behavior in morning peak hours. Results show (i) the possibility of inferring spatiotemporal constraints from considered routes, (ii) the importance of incorporating spatiotemporal constraints and latent traits in route choice models, and (iii) the linkage between spatiotemporal constraints and time saving, spatial and mnemonic abilities.     

The trade-off between accuracy and precision in latent variable models of mediation processes

Social psychologists place high importance on understanding mechanisms and frequently employ mediation analyses to shed light on the process underlying an effect. Such analyses can be conducted with observed variables (e.g., a typical regression approach) or latent variables (e.g., a structural equation modeling approach), and choosing between these methods can be a more complex and consequential decision than researchers often realize. The present article adds to the literature on mediation by examining the relative trade-off between accuracy and precision in latent versus observed variable modeling. Whereas past work has shown that latent variable models tend to produce more accurate estimates, we demonstrate that this increase in accuracy comes at the cost of increased standard errors and reduced power, and examine this relative trade-off both theoretically and empirically in a typical 3-variable mediation model across varying levels of effect size and reliability. We discuss implications for social psychologists seeking to uncover mediating variables and provide 3 practical recommendations for maximizing both accuracy and precision in mediation analyses.     

Personality,dangerous driving,and involvement in accidents: Testing a contextual mediated model

The present study tested the role of various personality traits in explaining dangerous driving and involvement in accidents, using a contextual mediated model (N = 311). We initially found direct effects of personality traits on dangerous driving indicators (Big-5, Dark Triad, sensation seeking, aggression, and impulsivity). Subsequently, personality variables with predictive power were tested in the mediation model. Indirect effects of anger, psychopathy and sensation seeking on the history of involvement in traffic accidents were found, which was predicted directly by risky driving. The results are discussed based on the characteristics of each trait. Overall, our research replicates and extends previous findings and highlights the importance of psychological evaluations (e.g., personality test) when prospective drivers are applying for a driver license.     

Delay or travel time information? The impact of advanced traveler information systems on drivers’ behavior before freeway work zones

Peak travel times contribute to congestion formation at freeway work zones. Advanced Traveler Information Systems (ATIS) can inform drivers in real-time about the delays and travel times en-route and can provide information about an alternative route to a destination. Different ATIS display strategies are available; however, road authorities lack insights into how time display methods and sign characteristics influence the driving behavior (decelerations, lateral position), the drivers’ attention allocation ability and the subsequent route choice before the freeway diversion. A driving simulator study was conducted with 80 drivers in the State of Qatar to investigate drivers' behavior and voluntary route choices when encountering total travel time (default setting) or delay time updates for two freeway routes on Variable Message Signs (VMS) and Graphical Route Information Panels (GRIP). The GRIPs are a graphical alternative to conventional VMS that can provide drivers with a visual map of the most direct route or an alternative less congested route to a destination using different color schemes. The time difference ratio between the two routes was kept constant to compare the effectiveness of the information designs and investigate the drivers’ attention towards the signs with an eye-tracker. The results showed that the display of zero delays for a detour did influence 74–83% of the drivers to take the alternative route when being displayed on a VMS and a GRIP with free flow attribute framing. When displaying equal total travel times, the GRIP did influence 25% more drivers to follow the alternative route than the VMS. Generally, displaying zero delays for the alternative route resulted in an efficient attention allocation to the first ATIS location and fewer mean decelerations before the repeated ATIS location nearing the diversion. Road authorities are advised to activate the display of delay times to support efficient route choices among freeway drivers.     

Shopping destination choice in Tehran: An integrated choice and latent variable approach

Integrated choice and latent variable (ICLV) models are increasingly considered in many fields as a means to gain a deeper understanding into the decision process of individuals as well as to potentially improve predictive ability. Literature has shown that the application of ICLV in context of shopping destination choice has not been conducted yet. This study uses data collected from the city of Tehran, Iran on shopping destination choice of 812 individuals. Then these attitudinal questions are used for the development of latent variables regarding the attitude and lifestyle of the participants. By including one latent variable (LV) reflecting the attitudes of clothing and lifestyle’s of grocery travelers the structural model reveals a sample distribution of this LV conditional on fundamental socio-economic characteristics. The results of our latent variable model clearly confirm that personal attitude toward clothing shopping center and lifestyle indeed impact destination choice. The results show that our experiment and the expanded hybrid choice model (HCM) allow appropriately identifying and investigating the effects of mixtures of latent attitudes on the intention shopping destination choice.     

Job Seeking Among Retirees Seeking Bridge Employment

Using a sample of recent retirees, the study described here sought to test the general propositions of the Wanberg, Watt, and Rumsey (1996) model by (a) including specific variables that are likely to be relevant to older adults seeking work after retirement (bridge employment) and (b) integrating more recent variable groups (e.g., situational constraints) suggested by recent research (e.g., Wanberg, Kanfer, & Rotundo (1999) and Kanfer, Wanberg, & Kantrowitz (2001) . Generally, the results support the efficacy of the Wanberg et al. model to predict job seeking among this group. Biographical variables such as older worker job search constraints, self-evaluations (e.g., job seeking self-efficacy), and motive/social variables (e.g., social support) were related to job seeking. Some of these, however, were not in the expected direction. Similarities and differences between "regular" job seeking and bridge employment job seeking are discussed.     

Examining human attitudes toward shared mobility options and autonomous vehicles

This paper presents a comprehensive analysis of people’s attitudes toward shared mobility options and autonomous vehicles (AVs), with a focus on the underlying patterns and potential determinants. A stated preference (SP) survey was designed and implemented in the U.S. Four sets of questions were included in the questionnaire, each focused on one unique aspect of user attitudes, including a) preferences for mobility options and lifestyle (such as overall view of driving, factors in mode choice decisions and technology engagement), b) perceived benefits and concerns of shared mobility option, c) reasons toward or against private vehicle ownership, and d) motivations for and desired features of AVs. A structural equations model was developed to identify latent attitudinal factors and examine the correlations between the latent attitudes (as the endogenous variables) and the observed covariates (including the socio-economic and demographic characteristics, and users’ current mobility profile, such as mode use frequency, travel distance, and trip fare). The model identified eleven latent factors that represent various aspects of attitudes toward AVs and shared mobility options. The findings could be used by policymakers and Transportation Network Companies (TNCs) to a) recognize the users’ latent attitudes, b) understand the underlying patterns of attitudes, c) implement plans and policies more efficiently, d) guide or influence users’ perceptions, and e) enhance travel behavior models. This study lays the foundation for further analysis on understanding user acceptance and adoption of these emerging mobility options, which is essential to estimate the likelihood and magnitude of behavior shifts in the era of automated, connected and shared mobility.     

Using a three-stage model of change to understand people’s use of bicycle,public transport,and car

More active ways of travelling (e.g., walking, cycling, and public transport) would benefit both individuals and society. To encourage people’s transition to more active travelling, it is important to understand the decision-making process regarding modal choice. The first aim of this study is therefore to combine a three-stage version of the transtheoretical model of change (TTM; Prochaska & DiClemente, 1983) with the theory of planned behaviour (TPB; Ajzen, 1991) to advance our understanding of the nature of the TTM stages. The second aim is to examine certain characteristics (i.e., age, gender, importance of everyday exercise, importance of environmental issues, perceived accessibility, and satisfaction with travel) of these three stages of change. The study used a web-based questionnaire, an app-based questionnaire, and an app-based travel diary completed by 306 people in the Stockholm area. The observed behaviour measured using the app-based travel diary showed that the three-stage model used in this study was consistent with the participants’ self-reported travel behaviour in using bicycles, public transport, and cars. Interventions focusing on attitude, subjective norm, and perceived behavioural control appear to have potential to move people from one stage to another regardless of initial stage. To make interventions as effective as possible, the stage of change as well as the behavioural, normative, and control beliefs underpinning attitude, subjective norm, and perceived behavioural control must be considered. Finally, more research is needed to advance our knowledge of the relationship between the three stages of change and other variables.     

THE PAST,PRESENT, AND FUTURE ALL MATTER: HOW TIME PERSPECTIVE IS ASSOCIATED WITH OPTIMISM AND SENSATION SEEKING AMONG YOUNG ADULTS

We used a multidimensional model of time perspective to examine how feelings and thoughts about the past, present, and future were related to optimism and sensation seeking among young adults. The dimensions of time perspective assessed were time feelings, the positive and negative emotions one has about the past, present, and future; time frequency, the amount of thinking about each time period; and time orientation, the relative emphases toward the time periods. Optimism and sensation seeking were self-reported and participants included 463 young adults. Variable-based analyses indicated that reporting more positive and less negative feelings about the time periods or emphasizing the present and future simultaneously were associated with greater optimism. For sensation seeking, boredom susceptibility was especially associated with the time perspective dimensions. Person-centered analyses based on time feelings and time frequency yielded four profiles (i.e., Mindful, Discontent, Bleak, and Indifferent) that were associated with both optimism and sensation seeking.     

Explaining the impact of policy information on policy-making

This article has called past studies into question as they relate to describing and explaining the impact of information on policy-making. More specifically, it attempts to empirically investigate the causality of the factors involved in the impact of information on governmental decision-making. Based on an integrated conceptual framework for when and how information helps to make policy decisions, a path model (or a covariance structure model without latent variables) is built and tested against the data in two areas of mental health policy (i.e., service provision and financing). Findings of the study demonstrate that how and when information influences governmental decision-making is directly and indirectly affected by a variety of factors and their linkages, not dominated by one set of factors (e.g., trustworthiness of information source or format of reports) defined by a single perspective (e.g., the organizational interest or the communications perspective). The most important paths in the model are those between factors related to information (e.g., the amount of information received or its use) and the impact of information on policy-making. Interestingly, these factors also play a major role in linking other variables (e.g., demographics or decision makers’ distrust of information) to the impact of information on policy-making. Furthermore, the general pattern of the findings indicates that policy areas make a difference in accounting for the impact of information on policy-making. Overall, the single most important lesson is that past perspectives are not alternative or competing tools for understanding the phenomena, and, thus, the theoretical and/or empirical task of explaining when and why information affects policy-making is equivalent to explaining why a certain set of factors is not appropriate or appropriate for a particular context and to identifying such a context.     

Testing between-family associations in within-family comparisons

Using behaviorally discordant siblings to test for gene-behavior associations is a common tool in molecular genetics, because the within-family contrast offers a research design that avoids confounds inevitable in all between-family comparisons of unrelated individuals. We propose a similar strategy to assess the behavior-behavior associations on which much of psychological science is built. Between-family correlations of personality test scores (e.g., sensation seeking) and behavioral outcomes (e.g., substance use) may be mediated by variables that differ between families (e.g., social class or religiosity) and correlate with both personality and outcome. Contrasting twin and nontwin siblings who were highly discordant for behavioral correlates of substance use, we tested whether between-family behavioral correlations replicated within families. Some, but not all, did. Within-family analyses of behaviorally discordant siblings may find wide application in efforts to clarify the meaning of correlational research data.     

Person-environment transactions in youth drinking and driving

Drinking and driving is a significant health risk behavior for adolescents. This study tested mechanisms by which disinhibited personality traits (impulsivity and sensation seeking) and aspects of the adolescent home/social environment (parental monitoring and alcohol accessibility) can influence changes in drinking and driving behavior over time. Two hundred two high school age youths were assessed at 2 time points, approximately 8 months apart. Zero-inflated Poisson regression analyses were used to test (a) an additive model, where personality and environmental variables uniquely predict drinking and driving engagement and frequency; (b) a mediation model, where Time 2 environmental variables mediate the influence of disinhibited personality; and (c) an interaction model, where environmental factors either facilitate or constrain the influence of disinhibited personality on drinking and driving. Results supported both the additive and interaction model but not the mediation model. Differences emerged between results for personal drinking and driving and riding with a drinking driver. Improving our understanding of how malleable environmental variables can affect the influence of disinhibited personality traits on drinking and driving behaviors can help target and improve prevention/intervention efforts.     

Predictors and outcomes of proactivity in the socialization process

This 3-wave longitudinal study aimed to extend current understanding of the predictors and outcomes of employee proactivity (involving information seeking, feedback seeking, relationship building, and positive framing) in the socialization process. Two personality variables, extraversion and openness to experience, were associated with higher levels of proactive socialization behavior. Of the proactive behaviors studied, feedback seeking and relationship building were highlighted in their importance because of their various relationships with the work-related outcomes assessed in this study (e.g., social integration, role clarity, job satisfaction, intention to turnover, and actual turnover). The results also highlighted the importance of 2 control variables (opportunity to interact with others on the job and skill level of the new job) in the experience of socialization into a new job.     

Make this detour and be unselfish! Influencing urban route choice by explaining traffic management

Traffic management policies aim to improve traffic flow by influencing the route choice of drivers, therefore preventing traffic jams in crowded cities. With respect to a system-optimum of the traffic network, drivers might have to make small-scale detours. The aim of this article is to encourage unselfish route choice behaviour in an urban context by informing drivers in advance about the objectives of traffic management. Two studies were conducted: (1) an online survey (N = 244) and (2) a driving simulation study (N = 48). The first study focussed on the general effect of recommendations for routes with longer travel times (system-optimal routes) when traffic management is explained. Other route choice attributes (travel time, red-light duration, time pressure) were analysed as well. Drivers were randomly confronted with 35 route choice scenarios consisting of a main route with certain red-light duration and an alternative route without. Results showed that the compliance with system-optimal routes is increased by around 10 percentage points when comparing the group with recommendation to the group without. This effect occurred independently of the variation of other route choice attributes. The second study aimed to determine if the compliance can be increased even more if drivers receive in-depth information about traffic management and experience ‘good’ as well as ‘bad’ recommendations in a driving simulator. Results showed no further effect of these manipulations on route choice. Only decision-making times and subjective evaluation were influenced by in-depth information compared to basic information. Altruism was partly correlated with decision-making. This article shows a novel approach to encouraging drivers to select routes with longer travel times for the benefit of the common good. Drivers’ knowledge gap regarding traffic management needs to be closed in order to enhance their understanding of traffic regulations. Finally, results of this research should be transferred to driver models within traffic simulations to estimate the effects on traffic networks.     

Exploring the route choice decision-making process: A comparison of planned and observed routes obtained using person-based GPS

Trip decisions are complex and involve choosing the activity destination, mode and subsequently the route for travel. This paper presents detailed information on the planned and observed route choices for the home-to-work commute. Specifically, the study examines how people formulate their route plans and describe their attitudes and preferences for their selected routes. A geographic information system (GIS) records the planned route information with the route planning sequence. Observing route choice is a difficult procedure; however, through the use of the global positioning system (GPS), one can accurately record route choice. An automated activity–trip detection algorithm processes GPS data and displays results within an internet-based prompted recall diary. The diary is used to verify trip start and end times. This combination of GPS, GIS and diary responses provides great insight into the route choice decision-making process. Thirty-one individuals from Ontario, Canada participated in answering survey questions and the collection of person-based GPS data. Results indicate a preference to minimize travel time as stated by participants in deciding what route to travel. Participants also affirmed a desire to minimize the number of stop lights/signs, as well as, avoid congestion and maximize route directness. A comparison between planned and observed routes, reveals about one-fifth of participants deviated from their planned route. This study demonstrates the need for qualitative and quantitative survey methods for exploring planned and observed route choice.     

The time course of perceptual choice: the leaky, competing accumulator model

The time course of perceptual choice is discussed in a model of gradual, leaky, stochastic, and competitive information accumulation in nonlinear decision units. Special cases of the model match a classical diffusion process, but leakage and competition work together to address several challenges to existing diffusion, random walk, and accumulator models. The model accounts for data from choice tasks using both time-controlled (e.g., response signal) and standard reaction time paradigms and its adequacy compares favorably with other approaches. A new paradigm that controls the time of arrival of information supporting different choice alternatives provides further support. The model captures choice behavior regardless of the number of alternatives, accounting for the log-linear relation between reaction time and number of alternatives (Hick's law) and explains a complex pattern of visual and contextual priming in visual word identification.     

Genetically influenced change in sensation seeking drives the rise of delinquent behavior during adolescence

Sensation seeking is associated with an increased propensity for delinquency, and emerging research on personality change suggests that mean levels of sensation seeking increase substantially from childhood to adolescence. The current study tested whether individual differences in the rate of change of sensation seeking predicted within-person change in delinquent behavior and whether genetically influenced differences in rate of personality change accounted for this association. Sensation seeking and delinquent behavior were assessed biennially between ages 10-11 and 16-17 in a nationally representative sample of 7675 youths from the National Longitudinal Study of Youth: Children and Young Adults (CNLSY). Analyses using latent growth curve modeling found that within-person change in sensation seeking was significantly and positively correlated with within-person change in delinquency from childhood to adolescence. Furthermore, behavioral genetic analyses of a subset of 2562 sibling pairs indicated that there were substantial genetic influences on both initial levels of sensation seeking and change in sensation seeking during early adolescence, with over 80% of individual differences in change due to genetic factors. Finally, these genetically driven increases in sensation seeking were most important for predicting increases in delinquency, whereas environmental paths between sensation seeking and delinquency were not significant. These results suggest that developmental changes in delinquent behaviors during adolescence are driven by a genetically governed process of personality change.