230.548 People
Martens, Karel
in Cooperation with on an Cooperation-Score of 37%
Topics
- planning
- city
- vehicle occupant
- case study
- passenger
- driving
- simulation
- vehicle fleet
- urban transportation
- waiting time
- demand responsive transportation
- parking management
- street
- bottleneck
- constraint
- passenger transportation
- shared mobility
- costs
- automation
- vehicle bunching
- curb side parking
- parking capacity
- data
- decision making
- bridge
- indicating instrument
- transportation planning
- accessibility
- automobile ownership
- automobile
- ownership
- public transit
- urban travel
- modeling
- traffic behavior
- bus
- fee
- taxicab
- commuting
- probe vehicle
- logit
- parking fee
- carsharing
- personal vehicle sharing
- urban population
- commuter
- migration
- no parking
- data collection
- road
- travel
- smartphone
- app
- bus rapid transit
- rapid transit
- neighborhood
- questionnaire
- departure time
- investment
- resident
- travel survey
- central business district
- re-procurement
- travel diary
- paratransit service
- parking
- parking demand
- behavior
- health
- parking facility
- walking
- parking duration
- walking distance
- off street parking
- reservation system
- vehicle
- on street parking
- vehicle to vehicle communication
- commodity
- dispute
- justice
- sphere
- transportation policy
- transport policy
- land use
- travel time
- sustainable development
- metropolitan area
- employment
- show 59 more
Publications
- 2021Parking space for shared automated vehiclescitations
- 2021Relocating shared automated vehicles under parking constraints: assessing the impact of different strategies for on-street parkingcitations
- 2021Parking space for shared automated vehicles: How less can be morecitations
- 2020Operationalizing an indicator of sufficient accessibility – a case study for the city of Rotterdamcitations
- 2020Relocating shared automated vehicles under parking constraintscitations
- 2020Identifying user classes for shared and automated mobility servicescitations
- 2020Relocating shared automated vehicles under parking constraints: assessing the impact of different strategies for on-street parkingcitations
- 2020Measuring individuals' travel behaviour by use of a GPS-based smartphone application in Dar es Salaam, Tanzaniacitations
- 2018Relocating Strategies under Parking Constraints for a Fleet of Shared Automated Vehicles
- 2017The Impact of Bottom-Up Parking Information Provision in a Real-Life Context: The Case of Antwerp
- 2016The Potential Impact of Vehicle-to-Vehicle Communication on On-Street Parking Under Heterogeneous Conditionscitations
- 2012Justice in transport as justice in accessibility: applying Walzer’s ‘Spheres of Justice’ to the transport sectorcitations
- 2011Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan areacitations
- 2011Substance precedes methodology: on cost–benefit analysis and equitycitations
Places of action
article
Parking space for shared automated vehicles
Abstract
<p>With the anticipated introduction of self-driving vehicles, new challenges arise for urban transport- and planning authorities. This study contributes to the efforts of formulating the potential opportunities and threats stemming from the introduction of larger fleets of self-driving vehicles to our cities, and what action could be taken by transport authorities to shape this introduction beneficially. In particular, the focus is put on the impact different parking management strategies can have on the performance of a fleet of shared automated vehicles providing on-demand transport services. This analysis focuses on aspects of service efficiency, externalities and service provision equity. The selected parking management strategies are tested in a large-scale activity-based simulation of a case study based on the city of Amsterdam, in which the parking facilities for SAV are digitally mapped throughout the city for different parking scenarios. The vehicles of the fleet aim at relocating to zones with high future demand, which can lead to bunching of vehicles at demand-hotspots. Parking management in the form of restricting parking facilities forces idle vehicles to spread out more evenly in the network. We show that this can reduce average passenger waiting times, increase service provision equity, cause less congestion and even can reduce the necessary fleet size. However, this comes at the cost of an increase in vehicle-kilometres-travelled, which reduces fleet efficiency and causes more undesired service externalities. Parking management is thus a simple, yet effective way for transport authorities to (a) determine where idle self-driving vehicles operating an on-demand transport service will be parked and (b) influence the performance of said transport service.</p>
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