Robot-Based Last-Mile Deliveries With Pedestrian Zones

Since delivery robots share sidewalks with pedestrians, it may be beneficial to choose paths for them that avoid zones with high pedestrian density. In this paper, we investigate a robot-based last-mile delivery problem considering path flexibility given the presence of zones with varying pedestrian level of service (LOS). Pedestrian LOS is a measure of pedestrian flow density. We model this new problem with stochastic travel times and soft customer time windows. The model includes an objective that reflects customer service quality based on early and late arrivals. The heuristic solution approach uses the minimum travel time paths from different LOS zones (path flexibility). We demonstrate that the presence of pedestrian zones leads to alternative path choices in 30% of all cases. In addition, we find that extended time windows may help increase service quality in zones with high pedestrian density by up to 40%.

A Stated Preference Survey for Evaluating Young Pedestrians’ Preferences on Walkways

For promoting pedestrian mobility, the quality levels of pedestrian paths should be increased. Many researchers suggest methodologies for determining the pedestrian level of service. Among these, some studies consider both paths’ physical characteristics and users’ perception about the walkways. Investigating users’ perceptions represents a good strategy for implementing interventions aimed at increasing the quality of service. The aim is recording pedestrians’ perceptions about the characteristics of the path and detecting the choices they would make in a hypothetical scenario. This work proposes the design of a Stated Preferences survey and the analysis of the preliminary results. A questionnaire was sent out to a sample of 240 pedestrians, prevalently students, about a walkway located in the University Campus of Rende (Italy). The collected data were analyzed by means of a discrete choice model for assessing the importance assigned by pedestrians to each aspect included in the analysis. The results showed that the environment can be considered as the most important aspect for young pedestrians, while the width of the path is not significant. The outcomes also highlighted the aspects it is necessary to change in order to make pedestrian paths increasingly attractive and to encourage users towards active mobility.

Applying a Pedestrian Level of Service in the Context of Social Distancing: The Case of the City of Madrid

During the COVID-19 pandemic, there has been a lot of discussion about keeping interpersonal distance to prevent the virus from spreading. To keep this interpersonal distance, authorities at different levels have taken measures to reduce people’s interactions, such as reducing capacities, curfews, pop-up cycle lanes, temporary pedestrianisation, and lockdowns. Many of these temporary measures have been perceived from a static view. Nevertheless, in a scenario of “new normality” or in the face of a possible new pandemic, the amount of data (big data) generated by different sources, such as sensors, in large cities has extraordinary potential to be used together with tactical urbanism for quick adaptation. The aim of this study was to gain insight into the aforementioned issues by analysing spatio-temporal patterns of pedestrian mobility and developing a variation of the pedestrian level of service measure; the pandemic pedestrian level of service (P-PLOS). This measure provides a dynamic view of pavement capacities according to the interpersonal distance recommendations during the pandemic. P-PLOS was tested in the city of Madrid based on the pedestrian counter data that was provided by the local government through its open data website. We found that the application of P-PLOS, together with street design, allows for knowing where and when it is necessary to take tactical urbanism measures in order to maintain or improve the level of service, as well as where it is necessary to take measures to reduce pedestrian flow.

A method for estimating pedestrian critical gap using microsimulation

Estimating critical gap is crucial for modelling pedestrian level of service at crossings. Critical gap modelling becomes more challenging in signalized crossings because the proportion of pedestrians seeking gaps during red is usually unknown. Besides, the willingness – or lack of it – to cross during red signal indication varies by pedestrian and local characteristics, which makes gap acceptance modelling even more challenging. The main objective of this study is to propose a method for estimating pedestrian critical gap at signalized crossings using Vissim. The method considers that all pedestrians seek for gaps on red, and the critical gap parameter is calibrated for each pedestrian type having delay as calibration target. The results showed MAPE values of 2% and 9% for the two studied crossings. This method was compared to three existing methods of critical gap estimation. The results showed that the proposed method yielded the best estimations of delay, followed by the HCM’s.

Factor Structure Analysis for Pedestrian Level of Service Assessment using Structural Equation Modelling

Pedestrian facilities are aimed at providing proper walking infrastructure and environment to promote walking in cities and needs to serve the desired requirements of users. It is important to assess the level of service (LOS) provided by such facilities. Various guidelines are available for assessing LOS of sidewalks, midblock crossings and pedestrians walking along the carriageway. However, the guidelines and factors considered for assessment are diverse and no single guideline is available that comprehensively takes into account all variables relevant for both sidewalks and crossings and for mixed land use settings. This work thus attempts to identify factors and their underlying variables and also the relative importance of the factors in determining LOS of pedestrian facilities in mixed land use areas. For this purpose, the study systematically identifies a comprehensive list of 20 important variables associated with LOS assessment for pedestrian facilities from literature. A survey was conducted of a heterogeneous group of 720 pedestrians from Patna, India to find importance perceptions of all the above identified variables. The important factors and their significant underlying variables were then identified using Exploratory Factor Analysis and the factor structure was confirmed using Structural Equation Model using survey data. Five factors namely Infrastructure, Crossing issues, Security, Sidewalk encroachments and Safety were identified with 13 significant underlying variables. It was observed that the crossing facility conditions predominantly influence the perception of LOS of pedestrian facilities. The findings of the study can be used by urban planners in focusing their improvement efforts for pedestrian facilities.