Game-theoretical approach to decentralized multi-drone conflict resolution and emergent traffic flow operations

This paper introduces decentralized control concepts for drones using differential game theory. The approach optimizes the behavior of an ego drone, assuming the anticipated behavior of the opponent drones using a receding horizon approach. For each control instant, the scheme computes the Nash equilibrium control signal which is applied for the control period. This results in a multi-drone conflict resolution scheme that is applied to all drones considered. The paper discusses the approach and presents the numerical algorithm, showing several examples that illustrate the performance of the model. We examine at the behavior of the ego drone, and the resulting collective drone flow operations. The latter shows that while the approach aims to optimize the operation cost of the ego drone, the experiments provide evidence that resulting flow operations are very efficient due to the self-organization of various flow patterns. The presented work contributes to the state of the art in providing a generic approach to multi-drone conflict resolution with good macroscopic flow performance characteristics. The approach enables relatively straightforward inclusion of error due to sensing and communication. The approach also allows for including different risk levels (e.g., for malfunctioning of sensor and communication technology), priority rules, regulations, and higher-level control signals (e.g., routing, dynamic speed limits).Comment: Submitted to the TRB Annual Meeting 202

What is the market potential for on-demand services as a train station access mode?

Ride-hailing and other on-demand mobility services are often proposed as a solution for improving the accessibility of public transport by offering first/last mile connectivity. We study the potential of using on-demand services to improve train station access by means of a three-step sequential stated preference survey. We compare the preferences for on-demand services with the bicycle, car and public transport for accessing two alternative train stations at different access distances. We estimate a joint access mode and train station choice model. By estimating a latent class choice model, we uncover five distinct segments in the population. We describe the classes based on their stated preferences, travel behaviour, attitudes towards new mobility and their socio-demographic characteristics. The two largest classes, accounting for over half of the sample, are the most likely to adopt on-demand services. Having an average willingness-to-pay, they would choose these services for longer access distances, competing mainly with the car and local public transport. Applying the model estimates, we observe that while on-demand services mainly compete with public transportation (obtaining most of its travellers from it), they are not able to fully substitute a public transport service for train station access, as many users would switch to cycling or driving a car, rather than opting for the on-demand service

Potential of on-demand services for urban travel

On-demand mobility services are promising to revolutionise urban travel, but preliminary studies are showing that they may actually increase the total vehicle miles travelled, thereby worsening road congestion in cities. In this study, we assess the demand for on-demand mobility services in urban areas, using a stated preference survey, to understand the potential impact of introducing on-demand services on the current modal split. The survey was carried out in the Netherlands and offered respondents a choice between bike, car, public transport and on-demand services. 1,063 valid responses are analysed with a multinomial logit and a latent class choice model. By means of the latter, we uncover four distinctive groups of travellers based on the observed choice behaviour. The majority of the sample (55%) are avid cyclists and do not see on-demand mobility as an alternative for making urban trips. Two classes (27% and 9% of the sample) would potentially use on-demand services: the former is fairly time-sensitive and would thus use on-demand service if they were sufficiently fast. The latter class however is highly cost-sensitive, and would therefore use on-demand mobility primarily if it is cheap. The fourth class (9%) shows very limited potential for using on-demand services

State-of-the-art of Longitudinal Travel Surveys – A Comparison of the MOP and MPN

Longitudinal travel surveys are needed to capture individual travel behaviour changes. Only two longitudinal tavel surveys of national relevance are currently in operation, the German Mobility Panel (MOP) since 1994 and the Netherlands Mobility Panel (MPN) since 2013. This paper provides an overview of both panels\u27 differences and similarities in design and data collection. Furthermore, representativeness, diary fatigue and non-random attrition are assessed in both panels to show the challenges panel surveys have to deal with. Overall, this paper shows important aspects of a panel survey that should be considered when designing a new longitudinal travel survey

Defining, measuring, and modeling passenger's in-vehicle experience and acceptance of automated vehicles

Automated vehicle acceptance (AVA) has been measured mostly subjectively by questionnaires and interviews, with a main focus on drivers inside automated vehicles (AVs). To ensure that AVs are widely accepted by the public, ensuring the acceptance by both drivers and passengers is key. The in-vehicle experience of passengers will determine the extent to which AVs will be accepted by passengers. A comprehensive understanding of potential assessment methods to measure the passenger experience in AVs is needed to improve the in-vehicle experience of passengers and thereby the acceptance. The present work provides an overview of assessment methods that were used to measure a driver's behavior, and cognitive and emotional states during (automated) driving. The results of the review have shown that these assessment methods can be classified by type of data-collection method (e.g., questionnaires, interviews, direct input devices, sensors), object of their measurement (i.e., perception, behavior, state), time of measurement, and degree of objectivity of the data collected. A conceptual model synthesizes the results of the literature review, formulating relationships between the factors constituting the in-vehicle experience and AVA acceptance. It is theorized that the in-vehicle experience influences the intention to use, with intention to use serving as predictor of actual use. The model also formulates relationships between actual use and well-being. A combined approach of using both subjective and objective assessment methods is needed to provide more accurate estimates for AVA, and advance the uptake and use of AVs.Comment: 22 pages, 1 figur

De nieuwe bereikbaarheidsindicator

Contains fulltext : 140588.pdf (publisher's version ) (Open Access

Mobiliteitspanel Nederland (MPN 2013)

The MPN's main objectives are to establish short-run and long-run dynamics in travel behaviour of individuals and households, and to determine how changes in personal and household characteristics and in othe