Conference Papers 2020

Seminar
Day 3 (11 Sep 2020), Session 9, Mobile Network Data/GPS Data, 15:30 - 17:30

Status
Accepted, awaiting documents

Submitted by / Abstract owner
Giovanni Acciaro

Authors
G. di Acciaro, G. Ciccarelli, NET Engineering S.p.A, BU Transport & Mobility, IT
C. Andriolo, Comune di Vicenza, Area servizi al territorio, Servizio Mobilità e Trasporti, IT
K. Muthmann, Cyface GmbH, DE

Short abstract
An innovative data-driven framework has been jointly co-designed by enterprises and policy makers across Europe to allow cyclists and citizens alike to benefit from city-wide well-maintained cycling infrastructure

Abstract
An innovative data-driven framework has been jointly co-designed by enterprises and policy makers across Europe to allow cyclists and citizens alike to benefit from city-wide well-maintained cycling infrastructure and contribute to the development of car-free sustainable communities via proactive citizens’ engagement.

By means of crowdsourcing sensor location data from common smartphones, a smart mobility framework has been conceived to capture and analyse accurate real-time information on daily bike users’ trips across the city as well as up-to-date information of pavement conditions (potholes, rough surfaces) of cycling infrastructure via the acquisition of vibration data whilst performing bike trips.
The ultimate outputs of such framework are the characterisation of city-wide cycling demand levels (i.e. through in-depth analysis of o-d trajectories and mobility patterns), which will result in the formulation of evidence-based policies to further encourage cycling, improve safety of cyclists and/or provide evidence where new cycle infrastructures (both at junction and lane levels) are most needed; on the other hand, the quality monitoring of infrastructure assets across diverse transport modes, namely car-mode and cycling (both on- and off-road), will assist infrastructure managers and local authorities in prioritising network interventions (depending on infrastructure usage levels) and, therefore, in optimising the use of financial resources allocated to transport-related investments.
Experimental plans were set out in different cities characterised by heterogenous transport and socioeconomic settings: in particular, an experiment is starting in Vicenza, with the support of Vicenza Municipality and local cycling associations and the purpose to track (in a cheaper way compared to traditional survey methods) cyclists’ routes, record cycling distances travelled, monitor cycling traffic flows and determine safety-critical hot spots to design evidence-based policy improvements.
As a result, the major requirement of such studies was to collect trip data from representative samples of cyclists in the cities, with reference to all user types (segmented by age, gender, living situation etc.) and journey purposes (commuting, shopping leisure, etc.), allowing for a
sound evaluation of transport-related performances (both supply and demand sides). As such, critical factors to the success of such experimental studies were, amongst others, the dissemination of the trialling activities through awareness campaigns, demonstration launching at public engagement events, the proactive and continuous support of local authorities to encourage citizens’ involvement throughout the project lifespan, the use of incentives to promote cycling use.
Public engagement is therefore a key issue enabling stakeholders to better understand trip characteristics, origin/destination paths and demand for multimodal transport services within certain local areas. On the other hand, the ecosystem creates the environment to allow for the prioritisation of maintenance interventions of cycle networks based on a correlation between pavement conditions and travel demand.
A sound evaluation plan was defined in compliance with commonly established industry standards by making use of appropriate Key Performance Indicators (KPI's), monitoring both supply- and demand side aspects of
the trips, whose goals followed the SMART logic (specific, measurable, actionable, realistic and time-phased goals). The application of such plan allowed the assessment of cycling demand level, the estimation of traffic efficiency performances across the whole transport network (based on average travelling speed and journey times) as well as the elaboration of a roll-on ranking of network maintenance intervention policies based on actual travel demand.
Finished German and Italian studies show that local communities lack the global knowledge about bicycle infrastructure conditions; provided with such a knowledge, travel comfort betterment and significant enhancement of cycling modal share will result. Furthermore, Local and Regional Government bodies experience a new environment, where knowledge of mobility demand enhances the opportunity for finetuning transport planning policies and practices in the mid-term period and also supports the implementation of real-time network management strategies, significantly improving transport decision making processes.

Programme committee
Data