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Autonomous Vehicles and Their Impact on Parking Search

Joschka Bischoff, Michal Maciejewski, Tilmann Schlenther, Kai Nagel
2018 IEEE Intelligent Transportation Systems Magazine  
In this case, the AV will not move from the link where the customer was dropped off. Otherwise find a nearby parking spot in the surroundings.  ...  Using this strategy, the AV will continue to the closest designated AV garage. • Cruise -In this case, the AV will cruise in circles around the last drop off point until it is required again within a defined  ...  He has a PhD in Computer Science from the University of Cologne; from 1995 to 1999 he was at Los Alamos National Laboratory as part of the TRANSIMS team. He is one of the creators of MATSim.  ... 
doi:10.1109/mits.2018.2876566 fatcat:hny5ijgcmnacreydpqk6v23pbu

A Comparative View on Existing Autonomous Control Approaches: Observations from a Simulation Study [chapter]

Till Becker, Katja Windt
2011 Autonomous Cooperation and Control in Logistics  
The presented simulation study applies multiple control algorithms within a simulation model using real business data derived from a scenario of an automobile logistics company.  ...  Still there is lack of broad applications of autonomous control in industry, which impedes a comprehensive evaluation of autonomous control algorithms.  ...  Acknowledgement This research is funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) as the Collaborative Research Center 637 "Autonomous Cooperating Logistic Processes -A Paradigm  ... 
doi:10.1007/978-3-642-19469-6_20 fatcat:m5taax4h2bhwppjmkojvjtqdya

What to do in the Meantime: A Service Coverage Analysis for Parked Autonomous Vehicles

Steffen Illium, Philipp Andreas Friese, Robert Müller, Sebastian Feld
2020 AGILE: GIScience Series  
Fully autonomously driving vehicles are expected to be a widely available technology in the near future.  ...  Our proposed methods are applied to a dataset of parking times of users of a telematics service provider in the Munich area (Germany).  ...  The provided trajectories have been chosen as a random sample from trips in a 30km radius around Munich and a 10km radius around Freising during the year 2018.  ... 
doi:10.5194/agile-giss-1-7-2020 fatcat:bakolgyuyvfttijo7ozkl4g7ga

Comparing Parking Strategies of Autonomous Transit On Demand with Varying Transport Demand

Biyu Wang, Sergio Arturo Ordonez Medina, Pieter J. Fourie
2019 Procedia Computer Science  
Autonomous transit on demand are increasingly considered to become a viable substitute for taxi services.  ...  Abstract Autonomous transit on demand are increasingly considered to become a viable substitute for taxi services.  ...  [4] pointed out that each SAV can replace around eleven conventional vehicles; [7] explored a automated parking lot management system with good performance for autonomous vehicles.  ... 
doi:10.1016/j.procs.2019.04.111 fatcat:mbcqdutr6nht7gefrzugtsb27e

Cruising for Parking with Autonomous and Conventional Vehicles

Mehdi Nourinejad, Matthew J. Roorda, Mehdi Keyvan-Ekbatani
2021 Journal of Advanced Transportation  
Parking is a cumbersome part of auto travel because travelers have to search for a spot and walk from that spot to their final destination.  ...  This conventional method of parking will change with the arrival of autonomous vehicles (AV).  ...  AVs drive D to drop off their occupants downtown and then drive back x to park at point X.  ... 
doi:10.1155/2021/6269995 fatcat:w3d3w2gm5jcvzppcdhdc6j52la

Extending Energy Storage Lifetime of Autonomous Robot-Like Mobile Charger for Electric Vehicles

Peng-Yong Kong
2020 IEEE Access  
An EV that has been charged may continue to occupy the parking lot and thus, blocking other EVs from using the limited number of charging points.  ...  We propose to decouple the parking need from charging need through the use of an autonomous robot-like mobile charger, which can roam freely in the parking area to reach each EV location for charging.  ...  FIGURE 1 . 1 Parking area model. In the figure, the mobile charger is seen moving from a way-point to another way-point towards an EV for charging.  ... 
doi:10.1109/access.2020.3000820 fatcat:yc3qsslekvhcdngjf3xnrf6hka

New Mobility Concepts and Autonomous Driving: The Potential for Change [chapter]

Barbara Lenz, Eva Fraedrich
2016 Autonomous Driving  
Autonomous Valet Parking in Carsharing The Autonomous Valet Parking use case starts from the assumption that the vehicle will be able to independently move from parking space to user and vice versa, even  ...  With Autonomous Valet Parking, providing vehicles at a station becomes essentially superfluous.  ... 
doi:10.1007/978-3-662-48847-8_9 fatcat:qrrtkndqqzhypdtjmr2mmq3ll4

Exploring the impact of shared autonomous vehicles on urban parking demand: An agent-based simulation approach

Wenwen Zhang, Subhrajit Guhathakurta, Jinqi Fang, Ge Zhang
2015 Sustainable cities and society  
The simulation results indicate that we may be able to eliminate up to 90% of parking demand for clients who adopt the system, at a low market penetration rate of 2%.  ...  by reducing the demand for parking.  ...  In a grid based network, there exist multiple shortest routes between points A and B.  ... 
doi:10.1016/j.scs.2015.07.006 fatcat:iw6b5udaabffndx5epwps3c7ge

Page 588 of Mathematical Reviews Vol. 35, Issue 3 [page]

1968 Mathematical Reviews  
Let P be a point set and R a subset of the reals. Consider pairs (x, a) ¢ Px R and any relation p on Px R for which (x, «)p(y, 8) implies a2.  ...  The results obtained parallel those for autonomous systems. B. L. Reinhart (College Park, Md.) Hajek, Otomar Theory of processes. I. (Russian summary) Czechoslovak Math. J. 17 (92) (1967), 159-199.  ... 

Architecting Dependable Learning-enabled Autonomous Systems: A Survey [article]

Chih-Hong Cheng, Dhiraj Gulati, Rongjie Yan
2019 arXiv   pre-print
We provide a summary over architectural approaches that can be used to construct dependable learning-enabled autonomous systems, with a focus on automated driving.  ...  We conclude the study with a list of promising research directions addressing the challenges of existing approaches.  ...  Randomized planning, such as rapidly exploring random trees (RRT) [36] , could explore large state space with a high computational cost.  ... 
arXiv:1902.10590v1 fatcat:4unvep4bwjhk7o4yqjbrhyxqg4

Routing an Autonomous Taxi with Reinforcement Learning

Miyoung Han, Pierre Senellart, Stéphane Bressan, Huayu Wu
2016 Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16  
autonomous taxis in a real scenario at the scale of the city of Singapore with pick-up and drop-off events for a fleet of one thousand taxis.  ...  Singapore's government is strongly encouraging and supporting research and development of technologies for autonomous vehicles in general and autonomous taxis in particular.  ...  We call an episode the movement of a taxi to an actual pickup point. For the first episode, the taxi located at a random position moves according to the initial oblivious learning policy.  ... 
doi:10.1145/2983323.2983379 dblp:conf/cikm/HanSBW16 fatcat:hijhj5drujcilceps6hqgnn2tm

A city-scale IoT-enabled ridesharing platform [article]

Claudio Gambella, Julien Monteil, Anton Dekusar, Sergio Cabrero Barros, Andrea Simonetto, Yassine Lassoued
2019 arXiv   pre-print
The advent of on-demand mobility systems is expected to have a tremendous potential on the wellness of transportation users in cities.  ...  Yet such positive effects are reached when the systems under consideration enable seamless integration between data sources that involve a high number of transportation actors.  ...  For example, if the origin is a random point in Larger Eindhoven, there is a 0.05 probability of selecting a random point in Helmond as destination.  ... 
arXiv:1912.00648v1 fatcat:hy6otoxinzd77fjuoe34gtfism

Parking futures: Curbside management in the era of 'new mobility' services in British and Australian cities

Greg Marsden, Iain Docherty, Robyn Dowling
2020 Land Use Policy  
The balance of parking, pick up and drop off and movement could be radically different in future.  ...  Looking ahead, a range of actors are developing visions of a shift from individual ownership of cars to shared but intensively used highly automated fleets.  ...  We might not yet be moving away from a parking city, but we are already moving towards a pick up/drop-off one.  ... 
doi:10.1016/j.landusepol.2019.05.031 fatcat:om5lrs2f35dgnaghwnn2vk3l3i

Optimal deployment of stations for a car sharing system with stochastic demands: A queueing theoretical perspective

Elisabetta Biondi, Chiara Boldrini, Raffaele Bruno
2016 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC)  
This problem combines insights from queueing theory (used to model the stochastic demand for cars/parking spaces at the stations) with a variant of the classical set covering problem.  ...  For its evaluation, we use a trace of more than 100,000 pickup and drop-off events at a free-floating car sharing service in The Netherlands, which are used to model the input demand of the car sharing  ...  The second random scheme we consider (denoted as RAND2) places as many stations as OPT but their location is selected uniformly at random among all cells where pickup/drop-off events take place.  ... 
doi:10.1109/itsc.2016.7795692 dblp:conf/itsc/BiondiBB16 fatcat:efo5w2cg4neznhe6zw2lxgba5q

Evaluating Uncertainty Estimation Methods on 3D Semantic Segmentation of Point Clouds [article]

Swaroop Bhandary K and Nico Hochgeschwender and Paul Plöger and Frank Kirchner and Matias Valdenegro-Toro
2020 arXiv   pre-print
Bayesian methods for UQ have been extensively studied for Deep Learning models applied on images but have been less explored for 3D modalities such as point clouds often used for Robots and Autonomous  ...  Deep ensembles outperform other methods by a margin of 2.4% in terms of mIOU, 1.3% in terms of accuracy, while providing reliable uncertainty for decision making.  ...  rather than just random sampling based on a Bernoulli distribution.  ... 
arXiv:2007.01787v1 fatcat:d3mcwhrkabhflelgq5a4d54s5y
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