The H2020 Road Transport Research European Conference was back with its 5th edition on 29 & 30 March 2022. LEVITATE was on the agenda on the first day in the parallel session: Automated driving and the users.
Andrew Morris, Loughborough University, presented the results of LEVITATE. He was accompanied by Peter Moertl (HADRIAN), Michiel Christoph (MEDIATOR) and Núria Parera Sallent (Safe-UP) who shared their insights and the results on their H2020 projects.
The panel of aforementioned experts talked about the need for a holistic approach when it comes to understanding users and innovative mobility solutions, moderated by Ingrid Skogsmo (VTI) and Suzanna Kraak (Policy Officer at the EC). Diversity, inclusivity and safety were at the heart of the discussion. More R&I activities on this topic will be essential to put users front and center in the development of Connected, Cooperative and Automated Mobility!
In case you missed it, you can replay the session below:
On April 7th, LEVITATE hosted a public webinar showcasing the principles of backcasting and the opportunities the resulting Policy Support Tool (PST) offers. Additionally, results of case studies in Vienna were presented, including the impacts of tolls on Cooperative, Connected and Automated Mobility (CCAM) and last-mile automated urban shuttle services.
First, Andrew Morris from Loughborough University, presented the LEVITATE project and its goal of building tools to help European cities, regions and national governments prepare for a future with increasing levels of automated vehicles. Amongst others, the project has developed methods of measuring the impacts of CCAM, including using backcasting principles, on mobility, safety, the environment and society.
Then Martin Zach from the Austrian Institute of Technology (AIT) laid out how LEVITATE’s backcasting methodology was established. Essentially, the method approaches the regulation of CCAM by starting from the top: initially, high-level visions and targets are set up (e.g. reducing CO2 emissions, accidents and fatalities), then possible influencing factors are identified (e.g. AV penetration rate and modal split of all journeys) and finally policy interventions are drawn up (e.g. road use pricing or public space reorganization).
This methodology is part of the foundations used to design LEVITATE’s open-access, web-based and user-friendly Policy Support Tool (PST), which was presented by Apostolos Ziakopoulos, from the National Technical University of Athens (NTUA).It is a one-stop-shop that integrates all of LEVITATE’s methodologies and findings, which can be used to assess CCAM general and targeted policy impacts using different automation penetration level scenarios. The webinar attendees were walked through the different parameters of the tool, which includes the assessment of 23 impacts, policy recommendations, benefits and costs of CCAM policies.
Finally, Gerald Richter and Johannes Müller from AIT concluded by showing how regulating CCAM could impact the city of Vienna. The researchers presented how the use of various tolls could influence modality shares, including automated and human-driven cars. They further highlighted how autonomous last-mile urban shuttle service could be deployed according to demographic density, average age and location of neighborhoods in Vienna.
Nearly 40 persons attended the LEVITATE webinar focusing on freight, which took place on 31 January 2022. Two freight case studies presented by researchers from LEVITATE partner, the Austrian Institute of Technology (AIT), were complemented by a contribution from the logistics platform ALICE, with which LEVITATE is cooperating in terms of sharing knowledge and dissemination activities.
The first of the LEVITATE freight case studies, presented by Bin Hu of AIT, covered an automated parcels delivery system in urban areas, for which the city of Vienna provided the test area. The main conclusions suggest that:
Electric vehicles will reduce the (local) emissions, but not the mileage
Consolidation reduces both, but is difficult to implement
Automation facilitates consolidation and reduces operating costs
The second freight case study addressed the impacts of truck platooning on urban bridges and was introduced by Marian Ralbovsky, AIT. The following conclusions were reached:
Truck platooning can significantly impact urban highway bridges
Effects depend on traffic composition (portion of trucks in traffic)
Mostly only bridges with large spans (river crossings) are expected to be affected
Intelligent access control can ensure bridge safety under platooned traffic
The final presentation was given by Fernando Liesa, Secretary General of Alice, which is a European Technology Platform bringing together stakeholders from the logistics sector. Fernando shared some of the main findings from projects and members activities that are relevant to CCAM. Among the useful insights provided are:
According to a survey by the Award project on incentives to use automated trucks, the most popular answer was ‘improve vehicle utilisation’
The shortage of truck drivers is a problem that CCAM may be able to help address
The ‘freight case studies webinar’ webinar recording can be found on this web page and directly on YouTube »
The aim of the LEVITATE project is to prepare a new impact assessment framework to enable policymakers to manage the introduction of connected and automated transport systems, maximise the benefits and utilise the technologies to achieve societal objectives. As part of this work, LEVITATE seeks to forecast societal level impacts of connected and automated transport systems (CATS) or, as these systems are more recently referred to, cooperative, connected, and automated mobility (CCAM). These impacts include effects on mobility, safety, environment and economy. Work Package 6 considers the societal impacts of automated passenger car use in urban environments. Within WP6, the impacts of six policy measures related to particular developments in automated passenger cars are considered in what are termed sub-use cases.
LEVITATE aims to forecast impacts of developments related to Cooperative, Connected and Automated Mobility (CCAM). Impacts are estimated for different so-called ‘sub use cases’ (SUCs) that reflect applications or interventions which can be implemented by policy makers. The impacts for the sub use cases are estimated by comparing the situation with intervention to the situation without intervention, i.e., the baseline scenario. The baseline scenario reflects the starting point for which increasing penetration levels of first cautious and later more ambitious automated vehicles (CAVs) are estimated over time. One of the relevant impact areas of CCAM is road safety.
This working document prepared by SWOV discusses in which way road safety is impacted by increasing penetration levels of connected and automated vehicles (CAVs) and 2) quantifies the road safety impacts of increasing penetration levels of CAVs as far as possible.
The POLIS Annual Conference has been held in Gothenburg on 1 and 2 December 2021. 640 participants were present exchanging knowledge on the outcomes of EU transport projects. POLIS Network, one of the partners of project LEVITATE, organizes its Conference every year to give a platform for exchange of best practices between POLIS members and EU transport project representatives.
LEVITATE was represented by several project partners, including the National Technical University of Athens (NTUA) and the Austrian Institute of Technology (AIT), giving visibility to the project results at the exhibition and a dedicated session on Vehicle Automation. LEVITATE and its Policy Support Tool (PST) – which is in the final phase of development – has been demonstrated by Apostolos Ziakopoulos, Research Associate at NTUA. Presentations from this dedicated session 4B are available here. During his presentation Apostolos expressed that: “The PST will consolidate the outputs of different methods into an overall framework for the assessment of impacts, benefits and costs of connected and automated transport services, for different automation and penetration levels and on different time horizons.”
The proliferation of connected and autonomous vehicles provides new opportunities for crime. Predicting crime is one of the enduring challenges for the security community. Connected and autonomous vehicles present a particular challenge for society, because it will be possible for remote attackers to hack into them, or for such vehicles to be used driverless to commit crimes, in effect anonymizing the offender.
A security risk analysis was conducted to identify possible cyberattacks against a future transport system consisting of autonomous and connected vehicles. Six scenarios were developed: joyriding, kidnapping, domestic abuse, autopilot manipulation, a large transport accident, and paralysis of the transport system. Even if it were possible to increase the difficulty of conducting such cyberattacks, it might be impossible to eliminate such attacks entirely. Measures that limit the consequences will therefore be necessary. Such measures include safety measures in vehicles to protect their occupants in traffic accidents and measures that make vehicles easier to remove in case they do not function.
This study was funded by the EU-funded (Horizon 2020) project LEVITATE. Open access funding was provided by our project partner Institute Of Transport Economics.
High-capacity Connected and Autonomous Vehicles (CAVs) are expected to be extensively utilized by on-demand services. This paper aims to assess the impacts of large-scale autonomous on-demand mobility services on traffic, environment, and road safety, under various service specifications using microsimulation. To that end, an urban on-demand shuttle service was designed, optimized, based on a variation of the Dial-a-Ride optimization problem (DARP), and implemented in the road network of the city of Athens to serve different portions of demand with various capacity specifications. It was then investigated through forty mobility scenarios, with differences in policy implementation and market penetration rate of CAVs. Findings show that it led to improved network level traffic conditions, as delays decreased, and that traffic impacts evolve with fleet capacity and served demand. Furthermore, the number of conflicts decreased and the environmental conditions significantly improved, with CAVs in the network, while the traveled distance increased.
Cooperative, connected, and automated mobility (CCAM) is expected to be introduced in increasing numbers over the next decades, having considerable impacts on mobility, safety, the environment and society as a whole. The Horizon 2020 project LEVITATE aims to prepare a new impact assessment framework to enable policymakers to manage the introduction of cooperative, connected and automated mobility, maximise the benefits and utilise the technologies to achieve societal objectives.
LEVITATE studied 3 use cases: automated urban transport, the automated passenger cars and the automated freight transport. In terms of the automated urban transport use case two sub-use cases were studied. The point-to-point automated urban shuttle service (AUSS) and the on-demand AUSS that were formulated after an extensive literature review and a Stakeholders reference group workshop. For these sub-use cases several impacts were quantified on traffic, safety, the environment, and society using microscopic simulation, mesoscopic simulation, system dynamics and the Delphi method.
This webinar took place on 23 November. The impact assessment methodologies used and the results that occurred regarding the automated urban transport sub-use cases were discussed. Several partners presented their findings including National Technical University of Athens (NTUA), Loughborough University (LOUGH) and the Austrian Institute of Technology (AIT).
Autonomous point to point shuttles are an emerging paradigm of a future mobility-on-demand ecosystem. However, the traffic and environmental impacts of their operation are largely under researched especially in relation to influential infrastructure related factors and service-related specifications.
The scope of this study is to reveal the factors that may affect the degree and magnitude of the road segment level impacts of an autonomous urban shuttle service (AUSS) operating in a city using microsimulation and structural equation modeling (SEM). For the purposes of this research, a systematic framework is developed and applied in the city center of Athens (Greece), which encompasses different scenarios of operations including: (i) Baseline (no AUSS operation), (ii) AUSS operation with a dedicated lane during peak hour, (iii) AUSS operation mixed with regular traffic during peak hour and (iv) AUSS operation mixed with regular traffic during off-peak hour. Two connected automated vehicle (CAV) profiles were used to model the advent of automation in the overall traffic: a cautious profile is introduced first, followed by a more aggressive profile. SEM findings indicate that the AUSS operation has a significant effect on cumulative travel time per segment and CO2 emissions per segment only during the scenario of mixed operation with traffic during off-peak hours. Additionally, the influence of the network geometry is correlated with reduced travel time and with increased CO2 emissions. Road traffic density was found to be positively correlated with both travel time and CO2 emissions, while the penetration of both cautious and aggressive CAVs was found to be negatively correlated with both indicators.
Read our publication ‘Quantifying the implementation impacts of a point to point automated urban shuttle service in a large-scale network’ based on the research carried out in WP5 in the Transport Policy Journal using this link.