While transport research has shown that individual attitudes and subjective norms affect travel behavior, most studies overlook how household-level travel socialization processes (i.e., how attitudes and behaviors are transmitted between members) affect these patterns over time. The current study examines socialization processes in two household types, two-partner and family households, focusing on how fathers (or male partners), mothers (or female partners), and children influence each other's travel attitudes and behaviors over time. Using a two-wave cross-lagged panel model from the Netherlands Mobility Panel, we test the directionality of these effects. Results indicate that (i) in two-partner households, sustainable modes show more bidirectional effects between partners, though train use remains asymmetrical; (ii) in family households, the socialization process is largely parent-driven, with mothers playing a central role in influencing sustainable travel attitudes/behaviors of both children and partners; (iii) car use shows bidirectional effects between children and parents; and (iv) in both household types, individual travel behaviors are also highly stable over time, indicating the importance of behavioral consistency in addition to socialization processes. Mode-specific strategies targeting influential household members; mothers for cycling, parents for train use, and children for car reduction; can more effectively promote sustainable travel.

Numerous studies have found influential factors of perceived accessibility levels in recent years. What is less well understood is the effect of perceived accessibility on travel, activities, and well-being. This is a significant omission in the respective body of literature as the primary goal of the transport system is to provide users with the necessary opportunities and possibilities to reach destinations and to participate in activities. Arguably, studying perceived accessibility and its determinants is only relevant if these perceptions in turn influence aspects such as travel behaviour, activity participation, satisfaction, and well-being. To fill this gap, this paper systematically identifies and analyses outcomes of perceived accessibility in terms of travel, activity participation, and well-being. For this purpose, we first identify links with outcomes of perceived accessibility in the literature. We then offer a conceptualisation based on the relations identified in the literature, which is empirically validated using a structural equation modelling approach. We find significant relations with activity participation and travel behaviour, but also with daily travel satisfaction, residential satisfaction, and overall life satisfaction. Finally, implications for policy and science as well as a research agenda with possible avenues for future research are presented. The most important lesson is that policies that consider ‘calculated’ accessibility only may fail to enhance satisfaction with life and to reduce (transport-related) social exclusion. Still, more research is needed to understand what other impacts of perceived accessibility are and how these outcomes of perceived accessibility, in turn, reinforce levels of perceived accessibility over time.

Noise pollution negatively affects health and well-being, making its monitoring important for effective mitigation strategies. Sensor systems such as sound level meters have long been used for this purpose. Nevertheless, dependence on grid power, restricted metrics beyond loudness, and high costs per unit limit current solutions. This paper presents an open hardware, off-grid sound sensor to measure loudness and complementary noise metrics. The sensor detects eleven common urban sound events, calculates acoustic sharpness, and the intermittency ratio of the acoustic environment. The sensor is based on an ESP32-S3 microcontroller on a customized printed circuit board, optimized to address the current limitations. The board includes a battery management circuit for solar charging, a real-time clock for accurate time keeping, and supports LoRaWAN to send aggregated metrics. The latter allows remote monitoring, while more detailed metrics are stored on a microSD card. A solar panel and up to two 18650 Li-Ion or LiFePo4 batteries allow the sensor to be deployed independently of mains power. The open hardware is accompanied by open firmware, which has been organized into multiple components to allow easy changes and extensions for other use cases. A lab validation showed a deviation below 2 dB for a 1 kHz test tone compared to a calibrated sound level meter.

Eliciting the weights of attributes is a key step in multi-attribute decision-making methods. The weights usually represent the relative importance of the attributes or the tradeoffs among them in forming a decision. Various weight elicitation methods exist, each based on different assumptions and procedures. Still, many of these methods do not explicitly account for the potential influence of cognitive biases in their design. This study examines the anchoring bias, a well-known cognitive bias, in the weight elicitation step (the Tradeoff procedure) of multi-attribute value theory (MAVT). We developed the following three hypotheses: (i) Using the most important (best) attribute to construct the indifference pairs in the Tradeoff procedure leads to higher weights for the best and worst attributes and lower weights for the other attributes, (ii) using the least important (worst) attribute to construct the indifference pairs in the Tradeoff procedure leads to lower weights for the best and worst attributes and higher weights for the other attributes, and (iii) using both best and worst attributes to construct the indifference pairs (i.e., the best–worst tradeoff: BWT) mitigates the anchoring bias. To test the hypotheses, we conducted an experiment by designing a questionnaire based on MAVT and collected data from 336 participants for a decision problem. The findings indicate that the anchoring bias has a significant impact on the Tradeoff procedure and that the BWT is effective in mitigating this bias.

A biased preference for the status quo could explain the increased support for policies following their implementation. However, the influence of status quo bias on support for transport policies has been analysed to a limited extent only. The counterfactual test serves as a potential method to empirically explore this influence by framing policies as the existing or alternative situation. This paper employs the counterfactual test to ascertain whether individuals disproportionately favour the status quo. To this end, we have designed separate experiments focusing on three transport policies: road pricing, speed limits, and train ticket fare differentiation. The results indicate that status quo bias does indeed influence support for transport policies. Participants prefer each policy option when framed as the status quo. In contrast, support for the same policy option declines when presented as the alternative situation. These findings underscore the irrational tendency to adhere to the status quo, which may stem from psychological commitments or cognitive misperceptions. Therefore, politicians, policymakers, and practitioners should anticipate a bias towards the status quo when introducing controversial transport policies.

To address transport injustice and social exclusion, the needs and perceptions of different groups of individuals seem indispensable. Consequently, perceived accessibility has received a growing interest in recent years. While it is well established that transport and social disadvantages cause transport poverty and perceived inaccessibility, only recently the relevance of geographical disadvantages has been addressed. This paper explores the idea that an individual is more likely to experience inaccessibility if they face transport, social, or geographical disadvantages in at least two of these dimensions of transport poverty. For instance, while living in a rural area or lacking the ownership of a car may not translate into low perceived access on themselves, the combination of the two might lower perceived access. To empirically assess whether and which disadvantages indeed lower perceived accessibility further, the effect of combinations of disadvantages on perceived accessibility in rural and urban areas of the Netherlands are systematically explored using a regression analysis. Data is retrieved from the Dutch National Travel Survey. This survey includes a 1-day travel diary, measures both objective and subjective accessibility, and is administered among a representative sample of the Dutch population. In total, a large and representative sample of 22,742 participants is included in the analysis. Results highlight that rural-living individuals only perceive inaccessibility if they indeed encounter one or more transport and/or social disadvantages as well. Also, not possessing a driver's license determines perceived inaccessibility to a larger extent than a lack of car ownership. Lastly, possessing an e-bike is beneficial for the elderly in both rural and urban Dutch areas. The research findings may support policymakers and practitioners in tailoring policy interventions towards the needs of individuals who suffer from multiple disadvantages.

BACKGROUND: Long-term noise annoyance can be expected to have worse outcomes than short-term annoyance. This study investigates noise annoyance over time, its association with personality traits and potential reciprocal effects between health outcomes and noise annoyance. METHODS: Firstly, we conducted a Longitudinal Latent Class Analysis to identify noise annoyance profiles. We further analysed the effect of Big Five personality traits on the likelihood of belonging to these annoyance profiles. Secondly, we used Cross-lagged Panel Models to analyse whether changes in noise annoyance precede changes in health outcomes or vice versa. For both analyses, we used 8 years of data from the Dutch Longitudinal Internet Studies for the Social Sciences (LISS) panel. Between 2708 and 11,068 subjects were included (this varies between models). RESULTS: We found three profiles of noise annoyance, namely, chronically, occasionally and never annoyed. Among all participants, 12% were chronically annoyed by neighbour noise and 6% by street noise. Extraversion and emotional stability decreased the chance of belonging to the cluster of chronically annoyed, while openness had the opposite effect. Chronic noise annoyance showed a significant effect on self-reported heart complaints and sleeping problems, while the effects of noise annoyance profiles on high blood pressure and heart attacks were insignificant. Some potential indications for a reverse effect from health outcomes on noise annoyance were found. CONCLUSION: Noise annoyance was relatively stable over time possibly because of its correlation with personality traits. Noise had a small negative effect on health outcomes, and some health outcomes affected noise annoyance. Further research should be conducted to collect dedicated panel data.

Many studies have investigated how digital engagement, new ways of working, and automated vehicles (AVs), are reshaping travel behaviour. However, their findings are frequently divergent or inconclusive. This work proposes that three emerging time-use patterns (TUPs) – multitasking, flexibility and fragmentation of activities – can help to explain the divergent results. To assess this notion, we systematically investigate the mediating role of TUPs in the relationship between digital engagement/telework/AVs and four key travel outcomes (trip frequency, travel distance, mode choice, and value of travel time). Using empirical data from 2019 to 2024, we find that TUPs can be seen as a mediator in shaping travel outcomes. For instance, when digital activities or telework increase activity fragmentation, they are associated with increased trip frequency. When digital activities or telework have been shown to increase flexibility, that has resulted in lower trip frequency. We notice that a potential reason for divergent results is that different configurations of digital engagement, telework, and AVs correspond to distinct TUPs, leading to opposite travel effects. We recommend that future studies integrate TUPs into assessments of travel behaviour change to better interpret causal relationships and address inconclusive findings.

Anchoring bias refers to the human tendency to rely heavily on an initial piece of information when making judgments. This bias has significant implications for decision analysis methods that rely on human judgments. This study examines the influence of anchoring bias in the value function elicitation step of the multiattribute value theory, specifically within the midvalue splitting procedure. We hypothesize that the starting point provided by the analyst during elicitation creates a bias in decision makers’ judgments, leading to distorted value functions and ultimately affecting decision outcomes. We also hypothesize that counter-anchoring and avoiding the use of anchors mitigate the effect of anchoring bias. To test the hypotheses, we designed an experiment and collected data from 320 subjects. The findings show that the starting point in the midvalue splitting procedure could change the attribute-specific value functions and, consequently, the overall value of the alternatives. Additionally, two debiasing strategies, counter-anchoring and avoiding the use of anchors, were found to be effective in reducing the effect of anchoring bias. The implications of this study can extend to other structured value function elicitation methods.

The last decade denoted a growing interest in perceived accessibility, yet the link between perceived and objective accessibility measures is understudied. This paper aims to address accessibility poverty by identifying groups with different levels of perceived accessibility. To achieve this aim, we develop a latent class model that relates perceived accessibility patterns to social, transport, and geographical conditions encountered by individuals. To support the specification of the latent class model, we develop a theoretical framework that links transport, social, and geographical conditions with perceived inaccessibility. Data is obtained from the Dutch National Travel Survey, which includes information on travel patterns and preferences. In total, 20,020 participants are included in the analysis. The latent class model identified six social groups with varying levels of perceived accessibility. Notably, while 89% of the individuals perceive excellent accessibility, a minority of 11% experiences different forms of inaccessibility. In addition, the latent class model showed that social rather than transport or spatial conditions encountered by individuals determine perceived inaccessibility. The results lend support to tailored policies aimed at reducing accessibility poverty and social exclusion for specific segments of the population.

Low-cost sensor networks have increasingly been used to monitor noise pollution as an alternative to certified sound level meters. Existing sensor networks monitor loudness and, in some cases, classify sound sources. Most sensors do not capture metrics that are more representative of the human perception of sound, require a permanent power supply, or are relatively expensive. We develop an energy-efficient soundscape sensor with the goal of recording metrics complementary to loudness. We have implemented metrics from psychoacoustics and metrics inspired by biodiversity research, such as sharpness, intermittency, and acoustic entropy. Furthermore, the sensor predicts the source of sound events. For privacy-preservation, all audio is processed directly on the sensor. The sensor is based on a low-power microcontroller (ESP32-S3), available for a fraction of the cost of a Raspberry Pi, which is often used for sound source prediction. Finally, the sensor is solar-powered and therefore easy to install for research purposes at places without direct access to the power grid. A temporary deployment of several sensors in Amsterdam, the Netherlands, is planned.