scholarly journals Potential of Private Autonomous Vehicles for Parcel Delivery

2020 ◽  
Vol 2674 (11) ◽  
pp. 520-531
Author(s):  
Tilmann Schlenther ◽  
Kai Martins-Turner ◽  
Joschka Felix Bischoff ◽  
Kai Nagel
Keyword(s):  
Service Provider ◽  
Autonomous Vehicles ◽  
Urban Traffic ◽  
Vehicle Miles Traveled ◽  
Traffic System ◽  
Autonomous Cars ◽  
Multi Agent ◽  
Wide Scale ◽  
Operator Behavior

Using the same vehicles for both passenger and freight transport, to increase vehicle occupancy and decrease their number, is an idea that drives transport planners and is also being addressed by manufacturers. This paper proposes a methodology to simulate the behavior of such vehicles within an urban traffic system and evaluate their performance. The aim is to investigate the impacts of resignation from fleet ownership by a transport service company (TSC) operating on a city-wide scale. In the simulation, the service provider hires private autonomous cars for tour performance. Based on assumptions concerning the operation of such vehicles and TSCs, the software Multi-Agent Transport Simulation (MATSim) is extended to model vehicle and operator behavior. The proposed framework is applied to a case study of a parcel delivery service in Berlin serving a synthetic parcel demand. Results suggest that the vehicle miles traveled for freight purposes increase because of additional access and egress trips. Moreover, the number of vehicles en route is higher throughout the day. The lowering of driver costs can reduce the costs of the operator by approximately 74.5%. If the service provider additionally considers the resignation from fleet ownership, it might lower the operation cost by another 10%, not taking into account the costs of system transfer or risks like vehicle non-availability. From an economic perspective, the reduction of the overall number of vehicles in the system seems to be beneficial.

scholarly journals A Programming Approach to Collective Autonomy

2021 ◽  
Vol 10 (2) ◽  
pp. 27
Author(s):  
Roberto Casadei ◽  
Gianluca Aguzzi ◽  
Mirko Viroli
Keyword(s):  
Autonomous Vehicles ◽  
Autonomic Computing ◽  
Autonomous Agents ◽  
Programming Approach ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Simulated Case ◽  
Complex Settings

Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane tasks (cf. driving and autonomous vehicles), from the risk of operating in unknown or perilous environments (cf. rescue scenarios), or to support timely decision-making in complex settings (cf. data-centre operations). Beyond the results that individual autonomous agents can carry out, a further opportunity lies in the collaboration of multiple agents or robots. Emerging macro-paradigms provide an approach to programming whole collectives towards global goals. Aggregate computing is one such paradigm, formally grounded in a calculus of computational fields enabling functional composition of collective behaviours that could be proved, under certain technical conditions, to be self-stabilising. In this work, we address the concept of collective autonomy, i.e., the form of autonomy that applies at the level of a group of individuals. As a contribution, we define an agent control architecture for aggregate multi-agent systems, discuss how the aggregate computing framework relates to both individual and collective autonomy, and show how it can be used to program collective autonomous behaviour. We exemplify the concepts through a simulated case study, and outline a research roadmap towards reliable aggregate autonomy.

scholarly journals Accelerating the Race to Autonomous Cars – A Case Study

2021 ◽  
pp. 219-231
Author(s):  
Divya Kumari ◽  
Subrahmanya Bhat
Keyword(s):  
Machine Learning ◽  
Autonomous Vehicles ◽  
Design Methodology ◽  
Production Efficiency ◽  
Production Costs ◽  
Business Strategies ◽  
Autonomous Cars ◽  
History Of ◽  
Start Ups

Background/Purpose: Every automaker is racing to generate self-driving innovations and some slew of fantastic tech firms and start-ups doing the same. The vehicle industry has a long history of implementing cutting-edge technologies to bring efficient, creative, and reliable vehicles to market, all while working to reduce production costs. Such innovations involve machine learning and computational intelligence, which are essential to automobiles progress. Machine learning (AI) technologies have made the innovative concept of self-driving vehicles an actuality. Today, global automotive rulers such as BMW, Volvo, and Tesla use intelligent automation to enhance production, raise production efficiency, and actually drive secure, extra relaxed, expanding, and increasingly enjoyable. This article provides a comprehensive analysis of Companies in the development of Autonomous vehicles and used ABCD analysis to examine the key parameters. Objective: Analyses the technology and business strategies of the companies in the Race of Autonomous cars. Design/Methodology/Approach: The information for this case study were gathered from various scholarly articles and websites. Findings/Result: The technological details of Artificial Intelligence, Self-driving car companies, laws and restrictions of different companies for using Self-driving vehicles, Autopilot driving features, sales volume and financial expansion, Impact of COIVID-19 on Autonomous vehicles business are studied. The impacts of COVID-19 on the autonomous car business are analysed using the ABCD framework. Originality/Value: The result provides a brief overview of different self-driving vehicle companies and self-driving technology building companies in the competitive race. Paper type: A Research Case study paper - focuses on companies in a race of producing Autonomous vehicles and the growth of those companies.

Evaluation of 3D-Traffic Accessibility Based on Space Syntax: A Case Study of Xi'an Subways

2012 ◽  
Vol 157-158 ◽  
pp. 338-343
Author(s):  
Fang Xiao Zhou ◽  
Chang Hua Li
Keyword(s):  
Rapid Development ◽  
Space Syntax ◽  
Urban Traffic ◽  
Traffic System ◽  
Urbanization In China ◽  
Xi’An City ◽  
Relation Matrix

With the rapid development of urbanization in China, many cities begin to build subway to relieve the increasing traffic pressure. How to evaluate effect of subway on existing urban traffic system interests urban planners. Space Syntax is the most widely used theory for calculating accessibility measures. However, as the basis model of space syntax, axial-map is only aimed at 2D traffic system, not suitable for 3D situation. Based on natural-street map, a method is proposed which treats stations as junctions between subway and streets and rebuilds relation matrix to calculate accessibility. Using the method, we analyze a case study of Xi’an city in china. It is found out that subway can change accessibility to some extent depended on routine of subway and site of station, which implies it reasonable to layout subway along streets with high integration.

Urban Traffic Modeling and Simulation: Moroccan Capital Case Study

2018 ◽  
Author(s):  
Aboutaib Brahim ◽  
Bahili Lahoucine ◽  
Fonlupt Cyril ◽  
Virginie Marion ◽  
Sebastiaan Verelst
Keyword(s):  
Modeling And Simulation ◽  
Urban Traffic ◽  
Traffic Modeling ◽  
Capital Case

scholarly journals Analysis of the System of Controlling Paid Parking Zones

2021 ◽  
Vol 13 (8) ◽  
pp. 4211
Author(s):  
Maciej Kozłowski ◽  
Andrzej Czerepicki ◽  
Piotr Jaskowski ◽  
Kamil Aniszewski
Keyword(s):  
Control System ◽  
Smart City ◽  
Measurement Errors ◽  
Fundamental Problem ◽  
Urban Traffic ◽  
Statistical Dependence ◽  
Actual State ◽  
Event Time ◽  
Operational Data

Urban traffic can be curbed in various ways, for instance, by introducing paid unguarded parking zones (PUPZ). The operational functionality of this system depends on whether or not the various system features used to document parking cases function properly, including those which enable positioning of vehicles parked in the PUPZ, recognition of plate numbers, event time recording, and the correct anonymisation of persons and other vehicles. The most fundamental problem of this system is its reliability, understood as the conformity of control results with the actual state of matters. This characteristic can be studied empirically, and this article addresses the methodology proposed for such an examination, discussed against a case study. The authors have analysed the statistical dependence of the e-control system’s measurement errors based on operational data. The results of this analysis confirm the rationale behind the deployment of the e-control system under the implementation of the smart city concept in Warsaw.

scholarly journals Exploring the Distribution of Traffic Flow for Shared Human and Autonomous Vehicle Roads

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3425
Author(s):  
Huanping Li ◽  
Jian Wang ◽  
Guopeng Bai ◽  
Xiaowei Hu
Keyword(s):  
Traffic Flow ◽  
Autonomous Vehicles ◽  
Flow Model ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Transformation Model ◽  
Hydrodynamic Theory ◽  
Traffic Flow Model ◽  
Traffic System ◽  
The Stability

In order to explore the changes that autonomous vehicles would bring to the current traffic system, we analyze the car-following behavior of different traffic scenarios based on an anti-collision theory and establish a traffic flow model with an arbitrary proportion (p) of autonomous vehicles. Using calculus and difference methods, a speed transformation model is established which could make the autonomous/human-driven vehicles maintain synchronized speed changes. Based on multi-hydrodynamic theory, a mixed traffic flow model capable of numerical calculation is established to predict the changes in traffic flow under different proportions of autonomous vehicles, then obtain the redistribution characteristics of traffic flow. Results show that the reaction time of autonomous vehicles has a decisive influence on traffic capacity; the q-k curve for mixed human/autonomous traffic remains in the region between the q-k curves for 100% human and 100% autonomous traffic; the participation of autonomous vehicles won’t bring essential changes to road traffic parameters; the speed-following transformation model minimizes the safety distance and provides a reference for the bottom program design of autonomous vehicles. In general, the research could not only optimize the stability of transportation system operation but also save road resources.

Sign in / Sign up

Export Citation Format

Share Document