Mobility Behavior Research Articles

Continuous Trajectory Generation Based on Two-Stage GAN

Simulating the human mobility and generating large-scale trajectories are of great use in many real-world applications, such as urban planning, epidemic spreading analysis, and geographic privacy protect. Although many previous works have studied the problem of trajectory generation, the continuity of the generated trajectories has been neglected, which makes these methods useless for practical urban simulation scenarios. To solve this problem, we propose a novel two-stage generative adversarial framework to generate the continuous trajectory on the road network, namely TS-TrajGen, which efficiently integrates prior domain knowledge of human mobility with model-free learning paradigm. Specifically, we build the generator under the human mobility hypothesis of the A* algorithm to learn the human mobility behavior. For the discriminator, we combine the sequential reward with the mobility yaw reward to enhance the effectiveness of the generator. Finally, we propose a novel two-stage generation process to overcome the weak point of the existing stochastic generation process. Extensive experiments on two real-world datasets and two case studies demonstrate that our framework yields significant improvements over the state-of-the-art methods.

Vacuum differential mobility spectrometry combined with column-switching liquid chromatography- mass spectrometry for the analysis of pyrrolizidine alkaloids in tea samples

The benefit of combining liquid chromatography (LC), supercritical fluid chromatography (SFC) and vacuum Differential Mobility Spectrometry – Mass Spectrometry (vDMS-MS) was investigated for the analysis of fourteen diastereomeric pyrrolizidine alkaloids (PA); intermedine, echinatine, lycopsamine, indicine, intermedine-N-oxide, echinatine-N-oxide, indicine-N-oxide, lycopsamine-N-oxide, senecivernine, senecionine, jacobine, senecivernine-N-oxide, senecionine-N-oxide, retrorsine. The mobile phase composition (15–100% MeOH and ACN), flow rate (8–100 µL/min), vDMS cell pressure, and F value showed an effect on the mobility behavior of the analytes. At 15% MeOH with a flow rate of 100 µL/min and 33 mbar vDMS pressure, 8 out 14 PA could be partially or totally separated by vDMS-MS. As well as providing an additional separation dimension vDMS improved the selectivity and a 5-minute assay method was developed for the quantification of 10 out of 14 single diastereomeric PA in tea samples, using a short LC column-switching and hyphenated to vDMS-MS in the selected ion monitoring mode. The performance of the method was found to be comparable with a 12-minute standard LC-MS/MS method using detection in the selected reaction monitoring mode. Additionally, the combination of vDMS and SFC-MS was investigated and suggests that the mixture of CO2/MeOH influences the CV shifting of the PA to more negative compensation voltage, and the signal-to-noise ratio is improved by a factor of three compared to SFC-MS without vDMS.

Meta-heuristic aggregate calibration of transport models exploiting data collected in mobility

The wide diffusion of data collected in mobility led to an unprecedented amount of information about people's mobility behavior. While on one hand the availability of big data from multiple sources enables to calibrate complex models with a high number of parameters, on the other hand, the dimension of the problem increases, and computational efficiency becomes an important issue. The paper presents a general methodology for the aggregate calibration of transport system models that exploits data collected in mobility jointly with other data sources within a multi-step optimization procedure based on metaheuristic algorithms. The methodology is applied to two real large-scale case studies in two different contexts. The first concerns the aggregate calibration updating a national strategic 4-step demand model in use in a big European Country; the second deals with the calibration of link and node performance functions implemented in a traffic network model of a town of around 3 million inhabitants. The results demonstrate the effectiveness of the aggregate calibration methodology in significantly improving earlier models’ estimations. The results also highlight that the errors are in the same order of magnitude as the intrinsic variation of the data collected in the field.

The Effects of Short-Term Exposure to pH Reduction on the Behavioral and Physiological Parameters of Juvenile Black Rockfish (Sebastes schlegelii).

Coastal areas are subject to greater pH fluctuation and more rapid pH decline as a result of both natural and anthropogenic influences in contrast to open ocean environments. Such variations in pH have the potential to pose a threat to the survival and physiological function of offshore fishes. With the aim of evaluating the impact of short-term pH reduction on the behavioral performance and physiological response of costal fish, the black rockfish (Sebastes schlegelii), one of the principal stock-enhanced species, was examined. In the present study, juveniles of the black rockfish with a mean body length of 6.9 ± 0.3 cm and weight of 8.5 ± 0.5 g were exposed to a series of pHs, 7.0, 7.2, 7.4, 7.6, 7.8, and normal seawater (pH 8.0) for 96 h. At the predetermined time points post-exposure (i.e., 0, 12, 24, 48, and 96 h), fish movement behavior was recorded and the specimens were sampled to assess their physiological responses. The results indicate that the lowered pH environment (pH 7.0-7.8) elicited a significant increase in highly mobile behavior, a decrease in immobile behavior, and a significant rise in the metabolic levels of the black rockfish juveniles. Specifically, carbohydrate metabolism was significantly elevated in the pH 7.2 and 7.4 treatments, while lipid metabolism was significantly increased in the pH 7.0, 7.4, and 7.8 treatments. The results of the present study indicate that short-term reductions in pH could ramp up boldness and boost energy expenditure in the black rockfish juveniles, leading to an increased metabolic cost. Additionally, the present investigation revealed that the black rockfish juveniles were capable of adapting to a short-term pH reduction. The findings may provide insight into the underlying physiological mechanisms that govern fish responses to potential decreases in seawater pH in the future.

The impact of COVID-19 lockdown measures on gendered mobility patterns in France

The COVID-19 crisis has upset the way of life of our society. The objective of this study was to apprehend the consequences of public health policies on mobility through the lens of gender. The analyses are based on a representative sample of 3000 people living in France. Travel behaviour was quantified using three mobility indicators (number of daily trips, daily distance travelled and daily travel time) that we regressed on individual and contextual explanatory variables. Two periods were studied: lockdown (March 17, 2020 until May 11, 2020), and post-lockdown (a curfew period: January–February 2021). For the lockdown period, our results show: (i) a statistically significant gender difference for the three mobility indicators. On average, women made 1.19 daily trips versus 1.46 for men, travelled 12 km whereas versus 17 km for men and spent less time on travel (23 min) than men (30 min); (ii) the degree of mobility was particularly sensitive to access to a car, according to a gender difference. For the post-lockdown period, our results reveal that: (i) women were more likely than men to make a higher number of daily trips (OR = 1.10, 95% CI = [1.04–1.17]); (ii) having only one or no car in the household impacted the mobility of women during the post-lockdown period; (iii) women regained some mobility but without reaching the pre-lockdown level. A better understanding of the factors influencing mobility behaviour, in lockdown and curfew periods, can provide some pathways to improve transport planning and help public authorities while tackling gender inequalites.

Consideration of Altered Anthropogenic Behavior during the First Lockdown and Its Effects on Air Pollutants and Land Surface Temperature in European Cities

Substantial reductions in human and economic activities such as road traffic for several months in 2020 were one of the consequences of the Coronavirus pandemic. This unprecedented change in urban metabolism also affected temperature and air pollutants. This study investigates the effects of the first COVID-19 lockdown across 43 cities in Europe. It determines the influence of anthropogenic activities on nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5), as well as on land surface temperature (LST) and the surface urban heat island intensity (SUHII) using satellite, modeled, and mobility data. Our findings show that there are great temporal and spatial differences and distinct patterns between the cities regarding the magnitude of change in the variables under study. In general, the results indicate a substantial decrease in NO2 concentrations in most of the studied cities compared with the reference period of 2015–2019. However, reductions could not be attributed to mobility changes such as less traffic at transit stations, contrary to the results of previous studies. O3 levels increased during the first lockdown in accordance with the decreasing NO2 concentrations. The PM pattern was inconsistent over time and space. Similar to the NO2 results, no relation to the altered mobility behavior was found. No clear signal could be detected for LST and the SUHII, likely due to dominating meteorological influences.

An ensemble federated learning framework for privacy-by-design mobility behaviour inference in smart cities

Inferring the travel behaviour of users in their GPS trajectories, while protecting their privacy is a significant issue for smart and sustainable cities. To address this challenge, we use Federated Learning (FL), a privacy-preserving machine learning technique that aims at collaboratively training a robust global model by accessing users’ locally trained models, but not their data. Specifically, we design a novel eNsemble federATed leArning for mobiLity InfErence (NATALIE) framework. The ensemble method combines the outputs from different DNN models learned via FL and shows an accuracy that surpasses comparable models reported in the literature. Extensive benchmarking experiments on open-access MTL Trajét and GeoLife GPS datasets demonstrate that the proposed inference model can achieve comparable accuracy in the identification of mode of travel without compromising privacy. The evaluation of the proposed model against non-i.i.d. data at varying sample sizes and different worker numbers shows improved performance. Findings are expected to contribute to the advancement of the transportation sector in smart and sustainable cities.

Fitness-based mobility enhances the maintenance of biodiversity in the spatial system of cyclic competition

In ecosystems, species are willing to stay longer when they are in good environments and, in this regard, explaining biodiversity and understanding the relative effect of species’ behavior is a fundamental issue in ecological sciences. Staying or moving stands for the movement of the population, and mobility has been accepted as one of the important mechanisms in systems of cyclic competition. In this paper, we investigate the biodiversity in the system of cyclic competition when an individual’s mobility is affected by environmental fitness. We found that fitness-based mobility, which is defined by the ratio of the difference between predator and prey among species, can lead to the slow behavior of species when local fitness is higher than the average fitness and enhance the biodiversity of species. The fitness-based mobility behavior is successful in reducing the extinction probability on the lattice network. However, when the average degree of the network increases, the extinction probability increases significantly. In addition, when we consider the same model on heterogeneous networks, the extinction probability is always 1 regardless of the sensitivity to the fitness. The finding indicates that the heterogeneous network destroys species coexistence. Through extensive numerical investigations, we provided solid evidence supporting the great importance of fitness-based mobility in maintaining biodiversity. We further highlighted the significant relationship among fitness, the fraction of empty sites, and the tunable parameter by investigating the correlation that the relationship is not influenced by mobility.

Analysis of Odor-Tracking Performance of Silk Moth Using a Sensory-Motor Intervention System.

Animals can adaptively behave in different environmental conditions by converting environmental information obtained from their sensory organs into actions. This sensory-motor integration enables the accomplishment of various tasks and is essential for animal survival. This sensory-motor integration also plays an important role in localization to females, relying on sex pheromones floating in space. In this study, we focused on the localization behavior of the adult male silk moth, Bombyx mori. We investigated sensory-motor integration against time delay using odor plume tracking performance as an index when we set a certain time delay for the sensory and motor responses. Given that it is difficult to directly intervene in the sensory and motor functions of the silk moth, we constructed an intervention system based on a mobile behavior measurement system controlled by them. Using this intervention system, not only can timing the detection of the odor in the environment and timing the presentation of the odor to the silk moth be manipulated, but timing the reflection of the movement of the silk moth can also be manipulated. We analyzed the extent to which the localization strategy of the silk moth could tolerate sensory delays by setting a delay to the odor presentation. We also evaluated behavioral compensation by odor sensory feedback by setting a delay to the motor. The results of the localization experiment have shown that the localization success rate did not decrease when there was a motor delay. However, when there was a sensory delay, the success rate decreased depending on the time delay. Analysis of the change in behavior after detection of the odor stimulus has shown that the movement was more linear when we set a motor delay. However, the movement was accompanied by a large rotational movement when there was a delay in the sensory input. This result has suggested that behavior is compensated for the delay in motor function by feedback control of odor sensation, but not when accompanied by sensory delay. To compensate for this, the silk moth may acquire appropriate information from the environment by making large body movements.

Sources and enrichment processes of groundwater arsenite and arsenate in fissured bedrock aquifers in the Xunhua-Hualong basin, China

Although high arsenic (As) groundwater has been widely observed in sedimentary aquifers, arsenite (As(III)) and arsenate (As(V)) mobilization in fissured bedrock aquifers are less documented, and different mobilization behaviors of As(III) and As(V) in groundwater from those aquifers are little known. Thus, geochemical and isotopic characteristics of high As groundwater in fissured bedrock aquifers in the Xunhua-Hualong basin were investigated. Results showed that fissured bedrock aquifer hosted high As groundwater. Total As concentrations in spring waters were up to 628 μg/L being dominated by As(V) with high ORP values (from 87.2 to 212 mV). As(III) dominated dissolved As in deep groundwater (up to 22.5 μg/L) with low ORP values (−217 and −288 mV). The positive correlation between As concentration and δ18O in spring water revealed that oxidation of As-bearing pyritic minerals in the fissured bedrock aquifers released As into groundwater. In deep groundwater under anoxic conditions recharged by shallow aquifers, high As groundwater usually had high concentrations of dissolved Fe, suggesting that reductive dissolution of Fe (oxyhydr)oxide minerals mobilized As into groundwater. Elevated concentrations of PO43− in high As spring water and deep groundwater indicated the competition adsorption between PO43− and As(V) (and As(III)). Insignificant correlations were observed between As(V) and pH, HCO3−, and Na+/Ca2+ in spring water, revealing that desorption induced by pH and HCO3− and cation exchange between Ca2+ and Na + had negligible effects on As(V) mobilization. However, alkaline pH caused the desorption of As(III), and the presence of HCO3− was conducive to As(III) desorption in deep groundwater. A conceptual model was established to explain As distribution in fissured bedrock aquifers, emphasizing contributions of mineral dissolution, desorption, and hydrogeological conditions to As mobilization. This paper highlights different mobilization behaviors of As(III) and As(V) in groundwater from fissured bedrock aquifers, requiring the different strategies to ensure the safety of drinking water in those areas.

Getting Back on Track: Understanding COVID-19 Impact on Urban Mobility and Segregation with Location Service Data

Understanding the impact of COVID-19 on urban life rhythms is crucial for accelerating the return-to-normal progress and envisioning more resilient and inclusive cities. While previous studies either depended on small-scale surveys or focused on the response to initial lockdowns, this paper uses large-scale location service data to systematically analyze the urban mobility behavior changes across three distinct phases of the pandemic, i.e., pre-pandemic, lockdown, and reopen. Our analyses reveal two typical patterns that govern the mobility behavior changes in most urban venues: daily life-centered urban venues go through smaller mobility drops during the lockdown and more rapid recovery after reopening, while work-centered urban venues suffer from more significant mobility drops that are likely to persist even after reopening. Such mobility behavior changes exert deeper impacts on the underlying social fabric, where the level of mobility reduction is positively correlated with the experienced segregation at that urban venue. Therefore, urban venues undergoing more mobility reduction are also more filled with people from homogeneous socio-demographic backgrounds. Moreover, mobility behavior changes display significant heterogeneity across geographical regions, which can be largely explained by the partisan inclination at the state level. Our study shows the vast potential of location service data in deriving a timely and comprehensive understanding of the social dynamic in urban space, which is valuable for informing the gradual transition back to the normal lifestyle in a “post-pandemic era”.

Evaluation of a mobile behavior change program for weight loss in breast cancer survivors: A prospective single-arm pilot study.

12070 Background: Post-diagnosis weight gain is common among women with early-stage breast cancer and is associated with increased risk of recurrence, breast cancer death, and all-cause mortality. Intentional weight loss following diagnosis is difficult to maintain. Targeted lifestyle interventions focusing on behavioral changes and education that can be implemented long-term are needed. Methods: This was a prospective single-arm pilot study in patients with history of early-stage breast cancer (NCT04753268). Key eligibility criteria included body mass index (BMI) ≥27.5 kg/m2, stage I-III breast cancer, and completion of active cancer treatment ≥6 months prior to study enrollment. Patients were recruited at the Dempsey Center in Lewiston, ME and via social media. Participants were given access to the Noom mobile application, which utilizes cognitive behavioral therapy, motivational interviewing, and self-determination theory to induce behavior change using an educational curriculum of daily articles, virtual health coaching, social networking, food records, and physical activity logs. The primary endpoint was change in self-reported weight from baseline to 26 weeks. Secondary endpoints included change in physical activity measured using step count and the Global Physical Activity Questionnaire (GPAQ), change in diet patterns analyzed using the Nutrition Data System for Research, patient-reported outcome (PRO) measures, and metrics for engagement with the mobile application. Results: 31 patients were enrolled; 24 at the Dempsey Center and 7 via social media. Mean age was 56.8 and mean baseline BMI was 33.5 kg/m2. Mean weight change was -4.8 kg (range +0.6 to -19.9 kg, p < 0.001) and mean percent weight change was -5.6%; 11/31 patients (35.5%) lost ≥5% of their initial weight. Average daily step count increased by 54.7% (p = 0.004). Mean GPAQ score for physical activity increased from 990 to 1773 (p = 0.01), and the proportion of patients who met physical activity guidelines increased from 45.1% to 74.2%. Mean energy intake did not change significantly over 26 weeks (p = 0.779). Improvements were observed in PROMIS-Physical Functioning T-scores and Body Image Scale scores (p = 0.04, p < 0.001 respectively). Metrics of engagement with Noom that were predictive of weight loss ≥5% included total articles read (p = 0.012), total weights logged (p = 0.006), total food records logged (p = 0.001), messages sent to coach (p = 0.001), and number of times the application was opened (p = 0.014). Conclusions: In this pilot study, breast cancer survivors lost weight and became more physically active using a commercially-available mobile application. This digital weight loss program is a scalable intervention, and these findings support future studies investigating impact on breast cancer outcomes. Clinical trial information: NCT04753268 .

Health consciousness and pro-environmental behaviors in an Italian representative sample: A cross-sectional study

Individual health-related behavior is among the most influential yet modifiable factors affecting both climate change and chronic disease. To encourage behaviors bringing about environmental and health co-benefits, it is important to understand the underlying factors of behavior change for healthy and sustainable lifestyles. One area of potential overlap concerns people’s health consciousness. The purpose of this study was to examine the relationship between health consciousness and pro-environmental behavior. We investigated whether health consciousness correlates with five clusters of pro-environmental behaviors: sustainable food consumption, recycling, green purchasing, sustainable mobility, and energy saving. Research data were collected via cross-sectional survey involving a representative sample of n = 1011 Italian citizens. Statistically significant differences emerged in the frequency of the different classes of pro-environmental behaviors: people living in Italy most frequently implement sustainable behaviors related to energy saving and recycling while sustainable mobility behaviors are the least implemented. Moreover, the stepwise linear regression model demonstrated the predictive role of citizens’ health consciousness on the adoption of specific classes of pro-environmental behaviors showing how higher involvement in one’s own health determines higher levels of pro-environmental behaviors. These results highlight the relevance of developing and testing complex programs featuring educational, sensitization, and structural strategies to increase citizens involvement in public health and pro-environmental behaviors.

URBAN MOBILITY DURING THE PANDEMIC IN YOGYAKARTA CITY

The urban situation has changed during COVID-19 pandemic since 2020. The swift of mobility behavior happened in all over the city in the world. The WHO’s suggestion to maintain NPIs; the physical distancing is a push factor for people to reduce traveling and mobility. The slogan ‘stay at home’ became part of the new normal until nowadays, because publication of it was spread on all media to reach out the society. Yogyakarta City responds to the pandemic issue with the same strategy, minimizing mobility and travel. However, there is uniqueness in the practice on minimizing mobility and travel in 2020 and 2021. In 2020, the control of mobility and travel is based on community and in 2021 the control of mobility and travel is based on government policy. The security level of travel in 2020 is housing and urban kampung, and in 2021 is on the city level. The research is focused on the perception of respondent on minimizing travel and mobility between these two years. The data was analyzed using the Principle Component Analysis method. The quantitative result will be compared with observation, so it shows the important value to respond during uncertainty on travel and mobility issue. The study will give how local wisdom and public policy collaborate to produce urban resilience in Yogyakarta City.

Hubungan Dukungan Keluarga, Peran Bidan dan Motivasi Ibu dengan Perilaku Mobilisasi Dini Pasca SC di RSIA Brawijaya Duren Tiga Jakarta Tahun 2022

Introduction: Early mobilization can maintain a person's independence to guide the patient out of bed such as walking, and moving limbs in a left and right tilt. Family support, the role of the midwife and the mother's motivation are one of the success factors in early mobilization behavior after surgery. Objectives: This study aims to determine the relationship between family support, the role of midwives and mother's motivation with early post-SC early mobilization behavior at RSIA Brawijaya Duren Tiga Jakarta in 2022. Method: This study used an analytic method with a cross-sectional approach with a total sample of 58 patients. In this study, the instrument used was a questionnaire with data analysis using the Chi-Square test. Result: The results of this study indicate that there is a relationship between family support and early mobilization behavior, obtained a P-Value of 0.002 and OR = 1.029 (0.294-3.604), the relationship between the midwife's role and early mobilization behavior with a P-Value of 0.029 and OR = 0.900 (0.267-3.029), and the relationship between maternal motivation and early mobilization behavior obtained P-Value 0.022 and OR = 1.095 (0.329-3.648). Conclusion: There is a relationship between family support, the role of midwives and the mother's motivation with early post-SC mobilization behavior at RSIA Brawijaya Duren Tiga Jakarta in 2022.

Do gender roles affect urban poverty in Ethiopia? A focus on women in micro and small enterprises

This original research article investigates the impacts of gender roles on women’s urban poverty in Assosa city, Benishangul Gumuz National Regional State, Ethiopia. It emphasizes how gender roles impacted women’s educational attainment and social mobility, healthy or unhealthy behavior and lifestyles, unemployment, and benefits from the infrastructural services available. A qualitative research design was employed to conduct the study with semi-structured interviews among women who engaged in Micro and Small Enterprises (n = 30), key informant interviews with experts working in government sectors (n = 15), and 4 focus group discussions (n = 32) among women who were selected based on their experiences in the micro and small enterprises in the study area. Thematic analysis was used to analyze the data generated aiming at understanding the different views of the study participants related to the revelation and expression of gender roles in women’s urban poverty. In the context of this study, revelation implies the state of being exposed to gendered roles while expression indicates the reactions of victims to exposure. This study has policy implications informing interventions at all levels toward mitigating the impacts of gender roles on women’s urban poverty.

Driving Towards Car-Independent Neighborhoods in Europe: A Typology and Systematic Literature Review

Car-independent neighborhoods can be seen as a planning strategy for overcoming car dependency and achieving urban sustainability goals. This implies a structural and psychological car independency of people, which manifests itself into positive attitudes and perceptions towards sustainable mobility, acceptance of corresponding measures, and a shift from private cars to active transport, public transport, and sharing modes. Despite their relevance, knowledge regarding the actual implications of the various existing strategies remains scarce. This gap is addressed in this literature review, which aims to: (a) identify types of implemented car-independent neighborhood policies; (b) explore their rationales, main characteristics, and implications for mobility behavior, psychological factors, perceptions, and acceptance; and (c) investigate how they have been evaluated. Existing implementations in Europe can be divided into four types: car-independent central areas, residential developments, citywide implementations, and temporary interventions, which differ in their rationales and scope. Overall, little research was found on this topic, with most studies focusing on newly built residential developments, compared to the other types. There is evidence of positive impacts on sustainable mobility behavior in the relevant use cases. However, it is often unclear whether this is a causality or correlation due to the absence of comprehensive (longitudinal) evaluations. Less is known regarding the implications of implementations for psychological factors and perceptions and their interplay with mobility behavior. For future research, it is recommended to evaluate other types of car-independent interventions beyond newly built developments through long-term observation of attitudinal and behavioral changes.

Identifying latent activity behaviors and lifestyles using mobility data to describe urban dynamics

Urbanization and its problems require an in-depth and comprehensive understanding of urban dynamics, especially the complex and diversified lifestyles in modern cities. Digitally acquired data can accurately capture complex human activity, but it lacks the interpretability of demographic data. In this paper, we study a privacy-enhanced dataset of the mobility visitation patterns of 1.2 million people to 1.1 million places in 11 metro areas in the U.S. to detect the latent mobility behaviors and lifestyles in the largest American cities. Despite the considerable complexity of mobility visitations, we found that lifestyles can be automatically decomposed into only 12 latent interpretable activity behaviors on how people combine shopping, eating, working, or using their free time. Rather than describing individuals with a single lifestyle, we find that city dwellers’ behavior is a mixture of those behaviors. Those detected latent activity behaviors are equally present across cities and cannot be fully explained by main demographic features. Finally, we find those latent behaviors are associated with dynamics like experienced income segregation, transportation, or healthy behaviors in cities, even after controlling for demographic features. Our results signal the importance of complementing traditional census data with activity behaviors to understand urban dynamics.

From Modeling to Optimizing Sustainable Public Transport: A New Methodological Approach

This paper explores the potential for connected public-transport (PT) mobility as an alternative to motorized private transport (MPT) in medium-sized cities. Despite the high demand for MPT, it occupies a lot of space and contributes to conflicts and reduced livability. The more sustainable mobility solution of PT, however, is often considered slow, unreliable, and uncomfortable. To overcome these issues, the authors investigate the state-of-the-art research of connected PT mobility, including ways to quantify mobility behavior, micro- and macro-simulations of traffic flow, and the potential of not-yet-established modes of transport such as Mobility on Demand (MoD) for last-mile transportation. MoD could reduce the drawbacks of PT and provide sufficient and sustainable mobility to all citizens, including those in rural areas. To achieve this, precise information on individual traffic flows is needed, including origin–destination (OD) relations of all trips per day. The paper outlines a two-step approach involving the expansion of OD relations to include all modes of transport and diurnal variation, followed by microscopic traffic simulations and macroscopic optimization to determine potentials for on-demand offers within inner-city traffic. The paper concludes by calling for critical questioning of the approach to validate and verify its effectiveness.

When perceived fairness and acceptance go hand in hand–Drivers of regulatory and economic policies for low-carbon mobility

Restrictive measures are indispensable to achieving sustainable and low-carbon mobility. At the same time, these are often not implemented due to concerns that public support will not materialize; therefore, they are relegated to the background in the debate on policy measures that can be applied to change mobility behavior. In this national study (N = 1,083), we used structural equation modeling (SEM) to examine the drivers of and differences between regulatory and economic transport policies. We find that policy-specific beliefs and, in particular, perceived fairness are key drivers of public acceptance. Our results indicate that policies must be perceived as fair, effective, and minimally intrusive for them to be accepted by the public and thus implementable. No major differences were found between the two types of policies examined, namely, regulatory and economic policies. Overall, public acceptance of the proposed measures is low. We discuss these results in terms of the study content and methodology and conclude by describing their implications for transport policy design.