Effects of driverless vehicles

Driverless vehicles have the potential to significantly affect the transport system, society, and environment. However, there are still many unanswered questions regarding what the development will look like, and there are several contradictory forces. This paper addresses the effects of driverless vehicles by combining the results from 26 simulation studies. Each simulation study focuses on a particular case, e.g. a certain mobility concept or geographical region. By combining and analysing the results from the 26 simulation studies, an overall picture of the effects of driverless vehicles is presented. In the paper, the following perspectives are considered: what types of application of driverless vehicles have been studied in literature; what effects these simulation studies predict; and what research gaps still exist related to the effects of driverless vehicles. The analysis shows that it is primarily driverless taxi applications in urban areas that have been studied. Some parameters, such as trip cost and waiting time, show small variations between the simulation studies. Other parameters, such as vehicle kilometres travelled (VKT), show larger variations and depend heavily on the assumptions concerning value of time and level of sharing. To increase the understanding of system level effects of driverless vehicles, simulations of more complex applications and aspects such as land use, congestion and energy consumption are considered

Data-driven Spatio-Temporal Scaling of Travel Times for AMoD Simulations

With the widespread adoption of mobility-on-demand (MoD) services and the advancements in autonomous vehicle (AV) technology, the research interest into the AVs based MoD (AMoD) services has grown immensely. Often agent-based simulation frameworks are used to study the AMoD services using the trip data of current Taxi or MoD services. For reliable results of AMoD simulations, a realistic city network and travel times play a crucial part. However, many times the researchers do not have access to the actual network state corresponding to the trip data used for AMoD simulations reducing the reliability of results. Therefore, this paper introduces a spatio-temporal optimization strategy for scaling the link-level network travel times using the simulated trip data without additional data sources on the network state. The method is tested on the widely used New York City (NYC) Taxi data and shows that the travel times produced using the scaled network are very close to the recorded travel times in the original data. Additionally, the paper studies the performance differences of AMoD simulation when the scaled network is used. The results indicate that realistic travel times can significantly impact AMoD simulation outcomes

Simulating the Integration of Urban Air Mobility into Existing Transportation Systems: A Survey

Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility. However, the integration of UAM into existing transportation systems is a complex task that requires a thorough understanding of its impact on traffic flow and capacity. In this paper, we conduct a survey to investigate the current state of research on UAM in metropolitan-scale traffic using simulation techniques. We identify key challenges and opportunities for the integration of UAM into urban transportation systems, including impacts on existing traffic patterns and congestion; safety analysis and risk assessment; potential economic and environmental benefits; and the development of shared infrastructure and routes for UAM and ground-based transportation. We also discuss the potential benefits of UAM, such as reduced travel times and improved accessibility for underserved areas. Our survey provides a comprehensive overview of the current state of research on UAM in metropolitan-scale traffic using simulation and highlights key areas for future research and development

Ridepooling and public bus services: A comparative case-study

This case-study aims at a comparison of the service quality of time-tabled buses as compared to on-demand ridepooling cabs in the late evening hours in the city of Wuppertal, Germany. To evaluate the service quality of ridepooling as compared to bus services, and to simulate bus rides during the evening hours, transport requests are generated using a predictive simulation. To this end, a framework in the programming language R is created, which automatically combines generalized linear models for count regression to model the demand at each bus stop. Furthermore, we use classification models for the prediction of trip destinations. To solve the resulting dynamic dial-a-ride problem, a rolling-horizon algorithm based on the iterative solution of Mixed-Integer Linear Programming Models (MILP) is used. A feasible-path heuristic is used to enhance the performance of the algorithm in presence of high request densities. This allows an estimation of the number of cabs needed depending on the weekday to realize the same or a better general service quality as the bus system

Maintaining Mobility in Substantial Urban Growth Futures

Integrated land use/transport models traditionally follow a simple integration concept: The land use model provides the origins and destinations of trips, and the travel demand model provides aggregate travel times between zones. High levels of congestion and the limitation of travel budgets, however, require travelers to scrutinize travel options and housing locations more carefully. In this paper, a microscopic integration of land use and transport models is proposed that - for the first time - is capable of capturing travel times and constraints at the level of the individual traveler. This level of integration allows choosing housing locations from which workplaces of all household members are accessible. In addition, discretionary travel can be limited to a household's travel budget after mandatory trips have been completed. The model is expected to represent travel and housing location choice constraints more realistically under high congestion/high cost scenarios

SimMobility Short-Term: An Integrated Microscopic Mobility Simulator

This paper presents the development of an integrated microscopic mobility simulator, SimMobility Short-Term (ST). The simulator is integrated because its models, inputs and outputs, simulated components, and code base are integrated within a multiscale agent- and activity-based simu- lation platform capable of simulating different spatiotemporal resolutions and accounting for different levels of travelers’ decision making. The simulator is microscopic because both the demand (agents and its trips) and the supply (trip realization and movements on the network) are microscopic (i.e., modeled individually). Finally, the simulator has mobility because it copes with the multimodal nature of urban networks and the need for the flexible simulation of innovative transportation ser - vices, such as on-demand and smart mobility solutions. This paper follows previous publications that describe SimMobility’s overall framework and models. SimMobility is an open-source, multiscale platform that considers land use, transportation, and mobility-sensitive behavioral models. SimMobility ST aims at simulating the high-resolution movement of agents (traffic, transit, pedestrians, and goods) and the operation of different mobility services and control and information systems. This paper presents the SimMobility ST modeling framework and system architecture and reports on its successful calibration for Singapore and its use in several scenarios of innovative mobility applications. The paper also shows how detailed performance measures from SimMobility ST can be integrated with a daily activity and mobility patterns simulator. Such integration is crucial to model accurately the effect of different technologies and service operations at the urban level, as the identity and preferences of simulated agents are maintained across temporal decision scales, ensuring the consistency and accuracy of simulated accessibility and performance measures of each scenario.Singapore. National Research Foundation (CREATE program)Singapore-MIT Alliance. Center. Future Urban Mobility Interdisciplinary Research Grou

Shared autonomous vehicle services: A comprehensive review

© 2019 Elsevier Ltd The actions of autonomous vehicle manufacturers and related industrial partners, as well as the interest from policy makers and researchers, point towards the likely initial deployment of autonomous vehicles as shared autonomous mobility services. Numerous studies are lately being published regarding Shared Autonomous Vehicle (SAV) applications and hence, it is imperative to have a comprehensive outlook, consolidating the existing knowledge base. This work comprehensively consolidates studies in the rapidly emerging field of SAV. The primary focus is the comprehensive review of the foreseen impacts, which are categorised into seven groups, namely (i) Traffic & Safety, (ii) Travel behaviour, (iii) Economy, (iv) Transport supply, (v) Land–use, (vi) Environment & (vii) Governance. Pertinently, an SAV typology is presented and the components involved in modelling SAV services are described. Issues relating to the expected demand patterns and a required suitable policy framework are explicitly discussed