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How can urban policies and planning approaches help in achieving a safer mobility and carbon reduction in the transport sector? The attention of planners and policy makers towards the promotion of sustainability and reduction of environmental impacts has grown in recent years. This paper investigates the role that Urban Planning plays in the long term towards a safer and climate friendlier mobility, highlighting the need for integrated approaches gathering spatial planning and mobility management. After a review of several urban policies and planning strategies, initiatives, and approaches, mainly based on the urban scale, the paper presents an urban regeneration case study leading to an increase of pedestrian accessibility at the neighborhood level. This can be seen as a support tool to foster sustainable, safe, and climate friendly mobility in cities. The results of the performed analysis show a dependency of accessibility from two different factors: the distribution of services and the capillarity of the soft mobility network, which can contribute to creating a more walkable space.

As it is widely accepted, cycling tends to produce health benefits and reduce air pollution. Policymakers encourage people to use bikes by improving cycling facilities as well as developing bicycle-sharing systems (BSS). It is increasingly interesting to investigate how environmental factors influence the cycling behavior of users of bicycle-sharing systems, as users of bicycle-sharing systems tend to be different from regular cyclists. Although earlier studies have examined effects of safety and convenience on the cycling behavior of regular riders, they rarely explored effects of safety and convenience on the cycling behavior of BSS riders. Therefore, in this study, we aimed to investigate how road safety, convenience, and public safety affect the cycling behavior of BSS riders by controlling for other environmental factors. Specifically, in this study, we investigated the impacts of environmental characteristics, including population density, employment density, land use mix, accessibility to point-of-interests (schools, shops, parks and gyms), road infrastructure, public transit accessibility, road safety, convenience, and public safety on the usage of BSS. Additionally, for a more accurate measure of public transit accessibility, road safety, convenience, and public safety, we used spatiotemporally varying measurements instead of spatially varying measurements, which have been widely used in earlier studies. We conducted an empirical investigation in Chicago with cycling data from a BSS called Divvy. In this study, we particularly attempted to answer the following questions: (1) how traffic accidents and congestion influence the usage of BSS; (2) how violent crime influences the usage of BSS; and (3) how public transit accessibility influences the usage of BSS. Moreover, we tried to offer implications for policies aiming to increase the usage of BSS or for the site selection of new docking stations. Empirical results demonstrate that density of bicycle lanes, public transit accessibility, and public safety influence the usage of BSS, which provides answers for our research questions. Empirical results also suggest policy implications that improving bicycle facilities and reducing the rate of violent crime rates tend to increase the usage of BSS. Moreover, some environmental factors could be considered in selecting a site for a new docking station.

As connected, electric, and autonomous vehicle (AV) services are developed for cities, the research is conclusive that the use of these services must be shared to achieve maximum efficiency. Yet, few agencies have prioritised designing an AV system that focuses on dynamic ridepooling, and there remains a gap in the understanding of what makes people willing to share their rides. However, in 2017, the Australian transport authority Transport for New South Wales launched over a dozen trials for on-demand, shared public transport, including AVs. In this paper, we investigate the user willingness-to-share, based on experiences from one of these trials. Four focus groups (19 participants in total) were held in New South Wales with active users of either the trialled on-demand dynamic ridepooling service (Keoride) or commercial ridepooling (UberPool). Through thematic analysis of the focus group conversations, the cost, comfort, convenience, safety, community culture, and trust in authority emerged as factors that influenced the willingness-to-share. When presented with driverless scenarios, the focus group participants had significant concerns about the unknown behaviour of their co-passengers, revealing sharing anxiety as a significant barrier to the adoption of shared AVs. This paper identifies previously disregarded factors that influence the adoption of AVs and dynamic ridepooling and offers insights on how potential users’ sharing anxiety can be mitigated.

Urban rail transit (URT) systems are critical to modern public transportation services. Unfortunately, disruptions in URT systems can lead to dysfunction and threaten sustainable development. This study analyses URT network sustainability from a vulnerability perspective. Two network attack scenarios, including random attacks and intentional attacks, are designed to assess different kinds of disruptions to URT networks. Under random attacks, nodes are randomly removed from the network. In contrast, under intentional attacks, key nodes are identified and removed based on topological metrics and passenger flow volume. Then, URT network vulnerability is evaluated by quantifying the changes in network efficiency and structural integrity under the network attacks from a spatio-temporal point of view. The real-world case of the Shanghai URT system from 1993 to 2020 is used to illustrate the vulnerability in the evolution of the URT system. The results indicate that the URT network is increasingly fault-tolerant and structurally robust over time. The URT network is more vulnerable to intentional attacks than to random failures. Additionally, there are significant spatial differences in the vulnerability of Shanghai URT network. Stations in the central activity zone (CAZ) are more fault-tolerant and robust than stations located outside of the CAZ. Furthermore, stations with large centrality and greater passenger flow volumes and lines with many key nodes and greater passenger flow volumes, are vulnerable to disruptions in the URT networks. This study provides a new index to comprehensively quantify node centrality; it also fills a research gap by analysing the vulnerability of URT networks based on both longitudinal and spatial patterns. Finally, this paper highlights significant practical implications for the sustainable development of URT networks, as well as the sustainable development of public transportation services.

Providing a sufficiently appropriate route environment is crucial to ensuring fair and safe biking, thus encouraging cycling as a sustainable mode of transport. At the same time, better understanding of cyclists’ preferences regarding the features of their routes and their infrastructure requirements is fundamental to evaluating improvement of the current infrastructure or the development of new infrastructure. The present study has two objectives. The first is to investigate cyclists’ route preferences by means of a choice experiment based on a stated preference survey. Subsequently, the second objective is to compare cyclist preferences in two countries with different cycling characteristics (both in infrastructure as well as cyclists’ behavior). For this purpose, a graphical online stated preferences survey was conducted in Greece and Germany. Within the framework of statistical analyses, multinomial mixed logit discrete choice models were developed that allow us to quantify the trade-offs of interest, while distinguishing between the preferences of different user groups. In addition, user requirements in Greece, as a country with a low cycling share and very little dedicated bike infrastructure, were compared to the requirements in Germany, where cycling is popular and the infrastructure is well developed. The results over the whole sample indicate that subgroups value infrastructure differently according to their specific needs. When looking at country specifics, users from Greece are significantly more willing to accept longer travel times in return for higher-quality facilities. The utility of low speed limits in mixed traffic is also different. In Germany, low speed limits offset the disturbance caused by motorized traffic, but in Greece they do not. Consequently, the results help to asses which types of infrastructure are most sustainable from a user perspective and help to set priorities when the aim is to adapt the road infrastructure efficiently in a stable strategy.

Urban transportation issues continue to emerge and evolve as a result of rapid urbanization, and the systematic and scientific assessment of urban mobility is becoming increasingly essential. In this work, a Pressure-State-Response (PSR) model with 25 indicators was established to reflect the status of urban mobility. Then, the importance of indicators was determined with the interval-valued intuitionistic fuzzy analytic hierarchy process (IVIF-AHP) method, and the fuzzy comprehensive evaluation (FCE) method was applied to assess the overall status of urban mobility. The validity of the proposed model was demonstrated using the mobility system of Beijing as a case study, and the pressure, state, and response scores were calculated. The proposed assessment model can help to improve urban transportation monitoring and can also provide a scientific foundation for future urban transportation policymaking, planning, and traffic management, thereby further ensuring the sustainable development of urban transportation systems.

Understanding commuters’ behavior and influencing factors becomes more and more important every day. With the steady increase of the number of commuters, commuter traffic becomes a major bottleneck for many cities. Commuter behavior consequently plays an increasingly important role in city and transport planning and policy making. Although prior studies investigated a variety of potential factors influencing commuting decisions, most of them are constrained by the data scale in terms of limited time duration, space and number of commuters under investigation, largely owing to their dependence on questionnaires or survey panel data; as such only small sets of features can be explored and no predictions of commuter numbers have been made, to the best of our knowledge. To fill this gap, we collected inter-city commuting data in Germany between 1994 and 2018, and, along with other data sources, analyzed the influence of GDP, housing and the labor market on the decision to commute. Our analysis suggests that the access to employment opportunities, housing price, income and the distribution of the location’s industry sectors are important factors in commuting decisions. In addition, different age, gender and income groups have different commuting patterns. We employed several machine learning algorithms to predict the commuter number using the identified related features with reasonably good accuracy.