A Comparative Analysis of E-Scooter and E-Bike Usage Patterns: Findings from the City of Austin, TX

E-scooter-sharing and e-bike-sharing systems are accommodating and easing the increased traffic in dense cities and are expanding considerably. However, these new micro-mobility transportation modes raise numerous operational and safety concerns. This study analyzes e-scooter and dockless e-bike sharing system user behavior. We investigate how average trip speed change depending on the day of the week and the time of the day. We used a dataset from the city of Austin, TX from December 2018 to May 2019. Our results generally show that the trip average speed for e-bikes ranges between 3.01 and 3.44 m/s, which is higher than that for e-scooters (2.19 to 2.78 m/s). Results also show a similar usage pattern for the average speed of e-bikes and e-scooters throughout the days of the week and a different usage pattern for the average speed of e-bikes and e-scooters over the hours of the day. We found that users tend to ride e-bikes and e-scooters with a slower average speed for recreational purposes compared to when they are ridden for commuting purposes. This study is a building block in this field, which serves as a first of its kind, and sheds the light of significant new understanding of this emerging class of shared-road users.Comment: Submitted to the International Journal of Sustainable Transportatio

On-line proactive relocation and regulation strategies for one-way station-based car-sharing systems

This study examines the on-line proactive planning of relocations in a one-way station-based electric car-sharing system that implements a complete parking reservation policy. A Markovian model that utilizes reservation information is formulated in order to estimate the expected near-future shortages of vehicles and parking spots at each station. The outcome of the model is used in algorithms for staff-based and user-based relocations. The proposed algorithms are tested in a simulation environment using data derived from a real-world car-sharing system. In addition, in collaboration with a car-sharing operator, the algorithms are test in the field

On-line proactive relocation strategies in station-based one-way car-sharing systems

In this work, we study the integration of relocation activities and system regulations in the operation of one-way car-sharing systems. Specifically, we consider the on-line proactive planning of relocations in a one-way station-based car-sharing system that implements a complete journey reservation policy. Under such policy, a user’s request is accepted only if at the booking time, a vehicle is available at the origin station and a parking spot is available at the destination station. If a request is accepted, the vehicle is reserved until the user arrives at the vehicle and the spot is reserved until the user returns the vehicle. Each parking spot may be in one of the following states: empty free spot, empty reserved spot, available vehicle and reserved vehicle. The reserved vehicles/spots provide additional information regarding spots/vehicles that are about to become available. We thus propose utilizing this information in order to plan relocation activities and implement impactful demand shifting strategies. We devise two relocation policies and two demand shifting strategies that are based on the evaluation of the near future states of the system. Using a purpose-built event based simulation, we compare these polices to a state-of-the-art inventory rebalancing policy. An extensive numerical experiment is performed in order to demonstrate the effectiveness of the proposed policies under various system configurations

Environmental benefits of bike sharing: A big data-based analysis

Bike sharing is a new form of transport and is becoming increasingly popular in cities around the world. This study aims to quantitatively estimate the environmental benefits of bike sharing. Using big data techniques, we estimate the impacts of bike sharing on energy use and carbon dioxide (CO 2 ) and nitrogen oxide (NO X ) emissions in Shanghai from a spatiotemporal perspective. In 2016, bike sharing in Shanghai saved 8358 tonnes of petrol and decreased CO 2 and NO X emissions by 25,240 and 64 tonnes, respectively. From a spatial perspective, environmental benefits are much higher in more developed districts in Shanghai where population density is usually higher. From a temporal perspective, there are obvious morning and evening peaks of the environmental benefits of bike sharing, and evening peaks are higher than morning peaks. Bike sharing has great potential to reduce energy consumption and emissions based on its rapid development

Classifying bicycle sharing system use in Southern European island cities : cycling for transport or leisure?

Bicycle sharing systems (BSS) have been implemented in cities worldwide in an attempt to promote cycling. Cycling as a mode of transport has the potential to provide transport alternatives for those marginalized by car-based mobility, to reduce traffic related diseases and injuries, noise and air pollution, and to promote an active lifestyle and improve public health. The three Southern European island cities included in this research, Limassol (Cyprus), Las Palmas de Gran Canaria (Spain) and the Valletta conurbation (Malta), exhibit characteristics considered as barriers to cycling, such as hot summers and high humidity, hilliness and car-oriented culture and infrastructure. Thus far, cycling modal share is low: under 1%. However, bicycle sharing systems and policies promoting cycling have emerged in these cities too. In this research a year of trip data, shared by the BSS operators, is used to analyse the use of the BSS on a system and station level. An analysis of the origin-destination matrices highlights spatial patterns, and the assessment of different types of use captures user behaviour. Particular attention is paid to the influence of tourism on the system use, by analysing the spatial influence of tourist accommodation, points of interests and land use, by classifying BSS trips carried out for leisure or for transport, and by assessing the temporal influence of the tourist season. The comparative analysis between the three cities shows that despite sharing commonalities, the cities exhibit differences in their shared bicycle use.peer-reviewe