Assessing travel time savings and user benefits of automated driving – A case study for a commuting relation

Combining cooperative vehicle driving behavior of Connected and Automated Vehicles with supporting information infrastructure, is expected to increase the capacity of roadway infrastructure, which in turn results in travel time savings and user benefits. Automated driving also relieves the driver from steering the car, allowing to conduct other activities during the trip, which is likely to generate further user benefits. In order to assess the magnitude of automated driving on travel time-related user benefits, a typical commuting relation is analyzed, considering three route options as well as level 4 and 5 vehicle automation. The impacts on travel times are estimated by microscopic traffic flow simulations. The simulations reveal that around 27% of the travel time can be saved on a commuting relation due to road automation according to level 5. For level 4 vehicles the travel time savings amount to up to 20%. User benefits that accrue from time savings and the passenger\u27s option of using travelling time for activities other than conducting the car, are expected at a relevant magnitude. Even under consideration of higher operating costs of an automated car, significant user benefits accrue: 1,310–2,240 € p.a. for level 4 and 2,770–3,440 € p.a. for level 5 vehicles during a passenger car\u27s typical depreciation period. Thus, automated driving will decrease the commuters\u27 generalized user costs for individual motorized mobility, which is likely to enhance the urban hinterland\u27s attractiveness as residential area. This pattern and inherent second-order effects pose challenges for transport, land use and urban planners. Furthermore, it represents a challenge for transport research: to elaborate appropriate concepts that allow for exploiting the benefits of use of automated vehicles while countervailing undesirable socio-economic effects, as well as strains on the transport system and land use

Book of abstracts of the 24th Euro Working Group on Transportation Meeting

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Prospects of the Activity-Based Modelling Approach: A Review of Sweden’s Transport Model- SAMPERS

The rapid changes in global development scenarios, such as technological advancements, lifestyle decisions and climate change, call for updated transport models to test micro-level policy decisions. This paper explores the advances in activity-based transport modelling in simulating travel demand in urban scenarios, focusing on Sweden’s National Transport model. Sampers is used for impact analysis, investment calculations for traffic simulations, transport policy implementation evaluations, and accessibility and impact analysis of extensive changes in land use and transport systems in cities and regions of Sweden. This research systematically compares individual components, sub-models, and algorithms and discusses integrations with cutting-edge agent-based models. Furthermore, recent research and projects for Sampers are investigated, highlighting its advantages over current models, potential gaps and limitations, and long-term development prospects. The study concludes by cross-referencing Sampers’ global developments and regional needs to assess its long-term development prospects

Networking Transportation

Networking Transportation looks at how the digital revolution is changing Greater Philadelphia's transportation system. It recognizes several key digital transportation technologies: Artificial Intelligence, Big Data, connected and automated vehicles, digital mapping, Intelligent Transportation Systems, the Internet of Things, smart cities, real-time information, transportation network companies (TNCs), unmanned aerial systems, and virtual communications. It focuses particularly on key issues surrounding TNCs. It identifies TNCs currently operating in Greater Philadelphia and reviews some of the more innovative services around the world. It presents four alternative future scenarios for their growth: Filling a Niche, A Tale of Two Regions, TNCs Take Off, and Moore Growth. It then creates a future vision for an integrated, multimodal transportation network and identifies infrastructure needs, institutional reforms, and regulatory recommendations intended to help bring about this vision

Policy and strategy evaluation of ridesharing autonomous vehicle operation: a london case study

To understand the dynamics of an autonomous ridesharing transport mode from the perspectives of different stakeholders, a single model of such a system is essential, because this will enable policymakers and companies involved in the manufacture and operation of shared autonomous vehicles (SAVs) to develop user-centered strategies. The model needs to be based on real data, network, and traffic information and applied to real cities and situations, particularly those with complex public transportation systems. In this paper, we propose a new agent-based model for SAV deployment that enables the parametric assessment of key performance indicators from the perspective of potential SAV users, vehicle manufacturers, operators, and local authorities. This has been applied to a case study of three regions in London: central, inner, and outer. The results show there is no linear correlation between an increased ridesharing acceptance level and average trip duration. Without a fleet rebalancing algorithm, over 80% of SAVs’ energy expenditure is on picking up customers. By reducing pickup distance, SAVs could be a contender for a nonpersonal transportation system based on trip energy comparisons. The results provide a picture of future SAV systems for potential users and offer suggestions as to how operators can devise an optimal transportation strategy beyond the question of fleet size and how policymakers can improve the overall transport network and reduce its environmental impact based on energy consumption. As a result of its flexibility and parametric capability, the model can be utilized to inform any local authority how SAV services could be deployed in any city

Local Climate Action Planning as a Tool to Harness the Greenhouse Gas Emissions Mitigation and Equity Potential of Autonomous Vehicles and On-Demand Mobility

This report focuses on how cities can use climate action plans (CAPs) to ensure that on-demand mobility and autonomous vehicles (AVs) help reduce, rather than increase, green-house gas (GHG) emissions and inequitable impacts from the transportation system. We employed a three-pronged research strategy involving: (1) an analysis of the current literature on on-demand mobility and AVs; (2) a systematic content analysis of 23 CAPs and general plans developed by municipalities in California; and (3) a comparison of findings from the literature and content analysis of plans to identify opportunities for GHG emissions reduction and mobility equity. Findings indicate that maximizing the environmental and social benefits of AVs and on-demand mobility requires proactive and progressive planning; yet, most cities are lagging behind in this area. Although municipal CAPs and general plans in California have adopted a few strategies and programs relevant to AVs and on-demand mobility, many untapped opportunities exist to harness the GHG emissions reduction and social benefits potential of AVs and on-demand mobility. Policy and planning discussions should consider the synergies between AVs and on-demand mobility as two emerging mobility trends, as well as the key factors (e.g., vehicle electrification, fuel efficiency, use and ownership, access and distribution, etc.) that determine whether deployment of AVs would help reduce GHG emissions from transportation. Additionally, AVs and on-demand mobility can potentially contribute to a more equitable transportation system by improving independence and quality of life for individuals with disabilities and the elderly, enhancing access to transit, and helping alleviate the geographic gap in public transportation services