Transportation Research Interdisciplinary Perspectives最新文献

Enhancing accessibility in transportation systems is an escalating interest among researchers, fueled by the rising issues with traffic congestion and technological innovations. Accessibility significantly contributes to improving the quality of life, thereby necessitating an examination of how route guidance systems impact it. This study explores the influence of system optimum (SO) and user equilibrium (UE) route guidance systems on accessibility, particularly in the context of connected autonomous vehicles (CAVs) embedded in the network. We employ a hybrid assignment model that enables the concurrent allocation of SO and UE assignments, along with the Gravity model to compute accessibility. The Sioux Falls network, previously leveraged in prior research, was chosen for numerical simulations to permit insightful comparisons. Our study scrutinizes three scenarios: the first scenario examines the repercussions of route guidance systems on human-driven vehicles, while the second and third assess their effects on CAVs. The difference between the second and third scenario is in the way of increasing the capacity in the assignment. Our findings reveal that at lower penetration rates of route guidance systems, accessibility initially dips, and then ascends. When all human-driven users adopt route guidance systems, accessibility increases by 12.75% compared to the initial state (without any intervention). Remarkably, should all users employ autonomous vehicles, accessibility would surge by 220% compared to the initial state (without any intervention). These insights highlight the importance of integrating CAVs and route guidance systems into transportation planning to enhance accessibility and improve the quality of life.

Road safety messaging represents a long-standing strategy in efforts to reduce speeding, a behaviour which accounts for an estimated 30 % of all road crashes on Australian roads. This study aimed to further examine the effectiveness of such a strategy via the use of a novel message medium that included anti-speeding messaging disseminated to speeding offenders via warning notices issued by a Start Government Transport agency. Informed by the Step approach to Message Design and Testing (SatMDT), survey content was devised to compare the effectiveness of the messages across various outcome measures including intentions to stay within the posted speed limit. A total of 219 speeding offenders completed the online survey. Overall, the results found some positive responses regarding Intervention condition participants’ responses to the anti-speeding messaging featured within the warning notices. Among some of the key findings were that the Intervention condition participants reported relatively low levels of message rejection. Additionally, females responded more favourably to both messages than males. Collectively, the findings suggest that there is no harm in including such messages within warning notices providing such messages are concept-tested prior to use. Overall, the findings suggest this approach may represent a low-cost option for targeted message delivery.

In some sectors and settings, the ability to work from home is increasingly common. The way this ability is experienced, and its impact on socio-spatial ordering, is shaped by context. In this piece, we use parenting as one particular context to explore the impact of working from home on day-to-day travel in a car-dependent setting. We intentionally seek out the complexity of mundane family life to ground Bauman’s concept of liquidity by demonstrating its embodiment through families working from home. We use in-depth interviews with 30 parents in Sydney and Melbourne, Australia, to examine the way the experience of working from home are filtered through the lens of caring for children and onto ways of being mobile day-to-day. We propose that working from home intensifies the complexity of the spatialities, temporalities and emotional landscapes of the parenting task. This intensification is absorbed by families as flexibility, which appeals to parents. This is likely to perpetuate reliance on autonomous modes of mobility for families, namely, the private car, who use cars to order complexity and enact flexibility. We conclude that working from home sustains and augments liquid lives in myriad ways, including the mundane organisation of family life and ways of travelling in cities.

Tricycles contribute to road crashes globally, especially in Asia where it is a popular means of transport. Safety assessment of tricycles has discovered that associated fatality rate and severity of injuries from tricycle crashes, which has risen steadily, are due to their flawed designs especially the absence of seatbelts and paddings of hard surfaces. Tricycle related crashes were sourced weekly from the regional office of the National Road Safety Authority from January 2012 to June 2022 and modelled with Autoregressive Integrated Moving Average Model. The results showed ARIMA (1,0,3) errors were retained as the best model for estimating road fatalities caused by tricycle crashes. The exogenous factors: tricycle crashes, time of day, season of the year, and road design were tested and found to be statistically significant relative to its contribution to the fatalities. The time series components were deemed to be relevant contributing factors to fatalities for the study period. Further, crash data forecasted to October 2022 largely exhibited a sinusoidal behaviour with spikes at various weeks. It was recommended that tricycle drivers undergo mandatory refresher courses on safe driving techniques and general road safety regulations as a policy intervention. In addition, the licensing regime for tricycles should be strengthened, and government should create separate lanes along some major routes within the metropolitan, municipal, and district assemblies to eliminate or reduce the negative incidents.

Occupational health and safety (OHS) challenges persistently plague road construction endeavours. The pivotal role of worker behaviour in influencing these challenges is widely acknowledged. Nevertheless, a comprehensive exploration of how OHS issues manifest in road construction due to worker behaviour has been conspicuously absent. Within the context of India’s National Highway expansion project, this study investigates the key factors associated with worker behaviour that contribute to accidents and presents a systemic archetype for ameliorating worker behaviour and, consequently, OHS. Data sourced from surveys and robust statistical analyses form the foundation of this research, with the System Dynamics modelling (SD) framework employed to construct the archetype. Furthermore, the Theory of Planned Behaviour (TPB) serves as the theoretical underpinning for this study. The findings underscore that accidents are often precipitated by a dearth of knowledge and inadequate training regarding safety codes and practices, which consequently leads to their violation. However, an investment in knowledge dissemination and comprehensive training to heighten awareness, encourage adherence, and facilitate implementation of safety standards and practices could markedly enhance OHS within road construction projects. This study posits that fostering appropriate worker behaviour rooted in knowledge and training, along with promoting the rigorous enforcement of safety codes and practices, stands as a crucial strategy for preventing accidents in road construction. Consequently, it is argued that knowledge acquisition and training should be recognized as pivotal leverage points for enhancing OHS through the prism of worker behaviour in road construction projects.

4-to-3 lane conversions, often called road diets, have been implemented throughout the U.S. as a means to reduce crashes. However, the reduction in lanes has led to community wide concerns across the country regarding the possible negative effect on emergency responses. This study investigates the impact of 4-to-3-lane roadway conversions on emergency response in Iowa through surveys and a retrospective analysis of EMS data. The 170 survey responses were analyzed descriptively, and a text analysis was done on two open text survey questions. Generalized linear models were constructed to examine the impact of lane conversions on emergency response times. Over half of EMS respondents believed there was no effect or a positive effect on responses, while 40% believed there was a negative effect. The negative effect was often attributed to driver confusion on how to properly yield to EMS vehicles. Despite the differing perceptions, EMS response rates from before to after the implementation of 4-to-3 lane conversions did not meaningfully differ. Overall, there was a lack of evidence of an effect of 4-to-3 lane conversions on EMS response rates in Cedar Rapids, Iowa. However, survey results showed that public guidance on how to properly respond to the presence of EMS vehicles on these roadways may be needed. This study provides evidence for addressing local concerns about road diets and emergency response to add to other known safety benefits. Results of this analysis may be applicable to other lane conversion sites when appropriately combined with local context relevant to the target area.

Motor vehicle traffic fatalities (MVTFs) are a public health issue that substantially affects the growing Black or African American, Indigenous, and People of Color (BIPOC) population. To further understand the racial discrepancies that exist in MVTFs, data from the Fatality Analysis Reporting System (FARS) and U.S. Census were utilized to explore factors such as rurality, urbanicity, restraint use, and alcohol-impairment. Calculations considered yearly driver and occupant fatality rates per 100,000 population for each race and ethnicity from 2010 through 2021. A Poisson regression model was used to quantify the relationship between the MVTF rates and the factors of interest. Results demonstrated that the American Indian or Alaska Native population was statistically the most overrepresented group in fatality rates across all factors explored. Additionally, the American Indian or Alaska Native population and Black or African American populations were the only groups to have statistically significant increases in fatality rates in recent years when accounting for factors such as unrestrained vehicle driver/occupants and alcohol-impaired fatality rate. In contrast, the Native Hawaiian or Pacific Islander population has consistently experienced one of the largest statistically significant reductions in driver and occupant fatality rates over time. Further analysis is necessary to develop and implement countermeasures that may reduce the increasing fatality rates of the most vulnerable populations while continuing to decrease rates for others as well. Despite limitations of FARS and population data, these results provide a pathway to reducing MVTFs and associated racial inequities that exist in the nation, particularly as the BIPOC population continues to grow.

The wide utilization of smartphones has provided extensive availability to Inertial Measurement Units, providing a wide range of sensory data that can be advantageous for transportation mode detection. This study proposes a novel end-to-end approach to effectively explore a reduced amount of sensory data collected from a smartphone, aiming to achieve accurate mode detection in common daily traveling activities. Our approach, called Feature Pyramid biLSTM (FPbiLSTM), is characterized by its ability to reduce the number of sensors required and processing demands, resulting in a more efficient modeling process without sacrificing the quality of the outcomes than the other current models. FPbiLSTM extends an existing CNN biLSTM model with the Feature Pyramid Network, leveraging the advantages of both shallow layer richness and deeper layer feature resilience for capturing temporal moving patterns in various transportation modes. It exhibits an excellent performance by employing the data collected from only three out of seven sensors, i.e., accelerometers, gyroscopes, and magnetometers, in the 2018 Sussex-Huawei Locomotion (SHL) challenge dataset, attaining a noteworthy accuracy of 95% and an $F_1$-score of 94% in detecting eight different transportation modes.

This paper critically evaluates the prevailing conceptualisations in transport equity research, emphasising the inadvertent Eurocentrism inherent in many contemporary frameworks. By distinguishing between social equality and social equity, the paper underscores the need for differentiated treatments in varied contexts to truly achieve fairness.

Central to this discourse is the assertion that the prevailing Eurocentric models may misrepresent or oversimplify non-Western contexts, particularly in regions with complex societal structures and cultural nuances, such as China. Drawing from China’s experiences, the paper illustrates the potential pitfalls of uncritically adopting Western transport equity theories, revealing how they can lead to significant misunderstandings. These inaccuracies are often perpetuated by a reliance on reductionist methodologies that do not account for the serpentine regional challenges and cultural dynamics unique to non-Western nations. Therefore, I advocate for an evolved, contextually apt approach to transport equity research that is sensitive to cultural and regional intricacies, ensuring a more comprehensive and accurate understanding of transport equity dynamics in global contexts.

Cycling has seen a remarkable rise, signifying a paradigmatic move towards sustainable, eco-friendly, and efficient commuting alternatives in the contemporary urban setting. Cities also encourage this trend by establishing cycle lanes, bike-sharing programs, and incentives for frequent riders. To enhance these motivations from an urbanistic perspective, it is essential to comprehend the influence of urban characteristics on cycling volume and to incorporate this understanding into data-driven decision-making processes.

This research examines the Bicification project data from Istanbul with a spatial perspective. Utilising a comprehensive array of spatial big data, the study explores the impact of urban land use, transport services, land morphology, and sociodemographic factors on cycling volume through a Multi-scale Geographically Weighted Regression (MGWR). With an Adj R² value of 0.68, the model demonstrates a strong relation between cycling volume and several factors, including biking park stations, park and ride points, pier stops, rail stops, transfer points, main roads, elevation, population, industrial facilities, health facilities, sports areas, and residential areas. The findings will serve to develop a data-driven strategic approach to promote cycling in Istanbul.