E-scooter micromobility systems: Review of attributes and impacts

Impact evaluation has become one of the core objectives of the transport sector worldwide towards improving its sustainability performance. This study aims to provide a comprehensive overview of the impacts in the field of e-scooter services. A systematic literature review is conducted on scientific peered- review journal publications in the English language. Thirty-eight studies are considered; for which a database is built that includes e-scooter attributes, such as service type (i.e., docked or dockless), infrastructure (i.e., dedicated lanes) and role (i.e., competing or complementary to public transport), key performance indicators and measured impacts by considering empirical and simulated data. KPIs are organized into five dominant impact areas for e-scooters: (1) Environment, (2) Society-Users, (3) Economy, (4) Transport performance, and (5) Safety. More than hundred KPIs are recorded with the most frequently used ones to refer to emissions, modal shift and accidents. The review concludes that the community goals should lead the selection of the e-scooter type and role within the transport system, since e-scooter attributes contribute towards different impacts. Future research should aim to the development of methods and tools for estimating e-scooter impacts and to the investigation of the relationship between user characteristics, impacts and e-scooter attributes

Describing Micro-Mobility First/Last-Mile Routing Behavior in Urban Road Networks through a Novel Modeling Approach

E-scooters aspire to provide flexibility to their users while covering the first/last mile of a multimodal trip. Yet, their dual travel behavior, i.e., utilizing both vehicles’ roadways and pedestrians’ sidewalks, creates new challenges to transport modelers. This study aims to model e-scooter riding behavior in comparison to traditional urban transport modes, namely car and walking. The new modeling approach is based on perceived safety that is influenced by the road environment and affects routing behavior. An ordinal logistic model of perceived safety is applied to classify road links in a 7-point Likert scale. The parametric utility function combines only three basic parameters: time, cost, and perceived safety. First/last mile routing choices are modeled in a test road network developed in Athens, Greece, utilizing the shortest-path algorithm. The proposed modeling approach proved to be useful, as the road environment of an urban area is heterogenous in terms of safety perceptions. Indeed, the model outputs show that the flexibility of e-scooters is limited in practice by their low-perceived safety. To avoid unsafe road environments where motorized traffic dominates, e-scooter riders tend to detour. This decision-making process tool can identify road network discontinuities. Nevertheless, their significance regarding routing behavior should be further discussed

Describing Micro-Mobility First/Last-Mile Routing Behavior in Urban Road Networks through a Novel Modeling Approach

E-scooters aspire to provide flexibility to their users while covering the first/last mile of a multimodal trip. Yet, their dual travel behavior, i.e., utilizing both vehicles’ roadways and pedestrians’ sidewalks, creates new challenges to transport modelers. This study aims to model e-scooter riding behavior in comparison to traditional urban transport modes, namely car and walking. The new modeling approach is based on perceived safety that is influenced by the road environment and affects routing behavior. An ordinal logistic model of perceived safety is applied to classify road links in a 7-point Likert scale. The parametric utility function combines only three basic parameters: time, cost, and perceived safety. First/last mile routing choices are modeled in a test road network developed in Athens, Greece, utilizing the shortest-path algorithm. The proposed modeling approach proved to be useful, as the road environment of an urban area is heterogenous in terms of safety perceptions. Indeed, the model outputs show that the flexibility of e-scooters is limited in practice by their low-perceived safety. To avoid unsafe road environments where motorized traffic dominates, e-scooter riders tend to detour. This decision-making process tool can identify road network discontinuities. Nevertheless, their significance regarding routing behavior should be further discussed

An Approach to Model the Willingness to Use of E-Scooter Sharing Services in Different Urban Road Environments

E-scooter sharing services been grown exponentially within the last five years. They are based on the flexibility of accessing dense urban areas without specialized infrastructure. In modern cities, there are diverse road environments that impact the comfort, and therefore the attractiveness, of micro-mobility services. This study aims to investigate the willingness to use e-scooter sharing services, while considering the road environment. To formulate area-specific pricing policies, a stated preferences experiment with 243 respondents, who can be considered as potential users, is conducted in Athens, Greece and a binary logistic regression model with random beta parameters is developed. The analysis of the model marginal effects indicates that the integration of bonus points into micro-mobility services, combined with the option of transferring these points to parking services, can compensate a non-friendly road environment, thus increasing the service demand. The existence of roads with good pavement conditions and wide sidewalks significantly increased the willingness of respondents to use e-scooter sharing services. Unexpectedly, pedestrianized zones in a buffer area of 2 km radius from the trip origin reinforce the attractiveness of shared e-scooters, while the contribution of bike lanes and traffic calming streets (or shared space) were proven to be insignificant

Implementation and external validation of Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score for predicting complications in 74 consecutive partial nephrectomies

Study Type Prognosis (case series) Level of Evidence 4 What’s known on the subject? and What does the study add? Partial nephrectomy (PN) is the gold standard operation for small renal tumours. The decision for or against a PN has been based mostly on preoperative radiological evaluation of the tumour. Three nephrometry scoring systems have been recently proposed for prediction of postoperative complications of PN (RENAL, C-index and PADUA). We validate externally the accuracy of the PADUA system and suggest for the first time a novel scoring system, based on the original PADUA system, which implements three other significant factors for the postoperative course of a partial. OBJECTIVE To externally validate the Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) classification of renal tumours managed by partial nephrectomy (PN). PATIENTS AND METHODS Seventy-four consecutive patients in a single academic tertiary institution underwent open PN. Incidence of 90-day complications was stratified by several clinicopathological variables, such as gender, age of the patient, hospital stay, pathology report, tumour characteristics and positive surgical margins. PADUA scores were given to each case. The severity of complications was also categorized with the Clavien system. RESULTS The optimal threshold of PADUA for the prediction of complications was 8 with a sensitivity equal to 90.9% and a specificity equal to 77.8% (area under the curve [AUC], 0.89; 95% confidence interval [CI], 0.731.00). Multivariate analysis revealed that that PADUA is an independent predictor for the risk of complications. Also, PADUA score =8 identified a group of patients with almost 20-fold higher risk of complications (hazard ratio [HR]= 19.82; 95% CI, 1.7928.35; P= 0.015). Patients with papillary histology had greater risk for complications than those with clear-cell tumours (HR = 4.88; 95% CI, 1.3417.76; P= 0.016). CONCLUSIONS The PADUA score is a simple anatomical system that predicts the risk of postoperative complications. This is the first external validation of this system for open PN from a single centre. The authors believe that PADUA is an efficient tool, since the only variable of the present study that predicted a higher incidence of complications was the histology type, which is determined after surgery. However, it should be applied to laparoscopic and robot-assisted series and it could also include the ischaemia time and surgeon experience in the overall scoring to be complete