scholarly journals Simulating the Impact of Shared, Autonomous Vehicles on Urban Mobility – a Case Study of Milan

10.29007/2n4h ◽  
2018 ◽  
Author(s):  
Sabina Alazzawi ◽  
Mathias Hummel ◽  
Pascal Kordt ◽  
Thorsten Sickenberger ◽  
Christian Wieseotte ◽  
...  
Keyword(s):  
Dynamic Pricing ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Transition Rate ◽  
Waiting Times ◽  
Region Of Interest ◽  
Autonomous Driving ◽  
Flow State ◽  
Wide Range ◽  
The Impact

Recent technological advances in vehicle automation and connectivity have furthered the development of a wide range of innovative mobility concepts such as autonomous driving, on-demand services and electric mobility. Our study aimed at investigating the interplay of these concepts to efficiently reduce vehicle counts in urban environments, thereby reducing congestion levels and creating new public spaces to promote the quality of live in urban cities. For analysis, we implemented the aforementioned factors by introducing the concept of robo-taxis as an autonomous and shared mobility service. Using SUMO as the simulation framework, custom functionalities such as ride sharing, autonomous driving and advanced data processing were implemented as python methods via, and around, the TraCI interface. A passenger origin-destination matrix for our region of interest in Milan was derived from publically available mobile phone usage data and used for route input. Key evaluation parameters were the density-flow relationship, particulate-matter emissions, and person waiting- times. Based on these parameters, the critical transition rate from private cars to robo- taxis to reach a free-flow state was calculated. Our simulations show, that a transition rate of about 50% is required to achieve a significant reduction of traffic congestion levels in peak hours as indicated by mean travel times and vehicle flux. Assuming peak- shaving, e.g. through dynamic pricing promised by digitalization, of about 10%, the threshold transition rate drops to 30%. Based on these findings, we propose that introducing a robo-taxi fleet of 9500 vehicles, centered around mid-size 6 seaters, can solve traffic congestion and emission problems in Milan.

The Impact of Mental States on Semi-autonomous Driving Takeover Performance: A Systematic Review

2020 ◽  
Vol 64 (1) ◽  
pp. 1372-1376
Author(s):  
Gaojian Huang ◽  
Christine Petersen ◽  
Brandon J. Pitts
Keyword(s):  
Systematic Review ◽  
Autonomous Vehicles ◽  
Response Times ◽  
Autonomous Driving ◽  
Mental States ◽  
Manual Control ◽  
Monitoring Systems ◽  
Wide Range ◽  
Different Types ◽  
The Impact

Semi-autonomous vehicles still require drivers to occasionally resume manual control. However, drivers of these vehicles may have different mental states. For example, drivers may be engaged in non-driving related tasks or may exhibit mind wandering behavior. Also, monitoring monotonous driving environments can result in passive fatigue. Given the potential for different types of mental states to negatively affect takeover performance, it will be critical to highlight how mental states affect semi-autonomous takeover. A systematic review was conducted to synthesize the literature on mental states (such as distraction, fatigue, emotion) and takeover performance. This review focuses specifically on five fatigue studies. Overall, studies were too few to observe consistent findings, but some suggest that response times to takeover alerts and post-takeover performance may be affected by fatigue. Ultimately, this review may help researchers improve and develop real-time mental states monitoring systems for a wide range of application domains.

scholarly journals An Efficiency Enhancing Methodology for Multiple Autonomous Vehicles in an Urban Network Adopting Deep Reinforcement Learning

2021 ◽  
Vol 11 (4) ◽  
pp. 1514 ◽  
Author(s):  
Quang-Duy Tran ◽  
Sang-Hoon Bae
Keyword(s):  
Reinforcement Learning ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Penetration Rate ◽  
Autonomous Vehicle ◽  
Effective Means ◽  
Urban Network ◽  
Learning Agents ◽  
Policy Optimization ◽  
The Impact

To reduce the impact of congestion, it is necessary to improve our overall understanding of the influence of the autonomous vehicle. Recently, deep reinforcement learning has become an effective means of solving complex control tasks. Accordingly, we show an advanced deep reinforcement learning that investigates how the leading autonomous vehicles affect the urban network under a mixed-traffic environment. We also suggest a set of hyperparameters for achieving better performance. Firstly, we feed a set of hyperparameters into our deep reinforcement learning agents. Secondly, we investigate the leading autonomous vehicle experiment in the urban network with different autonomous vehicle penetration rates. Thirdly, the advantage of leading autonomous vehicles is evaluated using entire manual vehicle and leading manual vehicle experiments. Finally, the proximal policy optimization with a clipped objective is compared to the proximal policy optimization with an adaptive Kullback–Leibler penalty to verify the superiority of the proposed hyperparameter. We demonstrate that full automation traffic increased the average speed 1.27 times greater compared with the entire manual vehicle experiment. Our proposed method becomes significantly more effective at a higher autonomous vehicle penetration rate. Furthermore, the leading autonomous vehicles could help to mitigate traffic congestion.

scholarly journals CONGESTION EFFECTS OF AUTONOMOUS TAXI FLEETS

Transport ◽  
2018 ◽  
Vol 33 (4) ◽  
pp. 971-980 ◽  
Author(s):  
Michal Maciejewski ◽  
Joschka Bischoff
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Large Scale ◽  
Traffic Volume ◽  
City Centre ◽  
Conventional Vehicle ◽  
Road Capacity ◽  
Private Car ◽  
The One ◽  
The Impact

Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow. Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today’s congestion.

scholarly journals The impact of telematics on traffic safety

2021 ◽  
Author(s):  
Igor Jelić ◽  
◽  
Maja Balenović ◽  
Keyword(s):  
Environmental Pollution ◽  
Fuel Consumption ◽  
Traffic Safety ◽  
Traffic Congestion ◽  
Waiting Times ◽  
High Mobility ◽  
Goods And Services ◽  
New Business ◽  
Business Approach ◽  
The Impact

The development of traffic that is conditioned by the high mobility of people, goods and services must be in line with the principles of sustainable development, but it is only possible if the consumption of renewable resources is less than natural renewal opportunities. The future is in implementation of innovative technologies such as telematics systems that offer not only technical solutions but also a new way of life, a new business approach and a new cultural aspect of living for all traffic participants. Advanced telematics solutions such as inflow management and speed limit management greatly help to solve traffic problems, like incidents, environmental pollution, traffic congestion, fuel consumption, etc. Impact of telematics can increase safety but can also introduce new risks for drivers that pose special challenges to traffic psychology and public health. In order to reduce traffic congestion, longer waiting times, environmental pollution, reduce fuel consumption in incident situation various advanced grammatical solutions have been implemented in order to reduce these problems. Telematics, using techniques such as informatics, optoelectronics, automatics and telecommunications, helps to reduce costs of transportation potential management, improves the security and reliability of the transportation service.

scholarly journals MEMS Mirrors for LiDAR: A Review

Micromachines ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 456 ◽  
Author(s):  
Dingkang Wang ◽  
Connor Watkins ◽  
Huikai Xie
Keyword(s):  
Autonomous Vehicles ◽  
Figure Of Merit ◽  
Three Dimensional ◽  
Point Clouds ◽  
Autonomous Driving ◽  
Field Of View ◽  
Preliminary Assessment ◽  
Wide Range ◽  
Laser Scanners ◽  
Increasing Demand

In recent years, Light Detection and Ranging (LiDAR) has been drawing extensive attention both in academia and industry because of the increasing demand for autonomous vehicles. LiDAR is believed to be the crucial sensor for autonomous driving and flying, as it can provide high-density point clouds with accurate three-dimensional information. This review presents an extensive overview of Microelectronechanical Systems (MEMS) scanning mirrors specifically for applications in LiDAR systems. MEMS mirror-based laser scanners have unrivalled advantages in terms of size, speed and cost over other types of laser scanners, making them ideal for LiDAR in a wide range of applications. A figure of merit (FoM) is defined for MEMS mirrors in LiDAR scanners in terms of aperture size, field of view (FoV) and resonant frequency. Various MEMS mirrors based on different actuation mechanisms are compared using the FoM. Finally, a preliminary assessment of off-the-shelf MEMS scanned LiDAR systems is given.

scholarly journals Patient prioritisation methods to shorten waiting times for elective surgery: a systematic review of how to improve access to surgery

2021 ◽  
Author(s):  
Dimuthu Rathnayake ◽  
Mike Clarke ◽  
Viraj Jayasinghe
Keyword(s):  
Systematic Review ◽  
Web Of Science ◽  
Elective Surgery ◽  
Waiting Times ◽  
Healthcare Management ◽  
Waiting List ◽  
Cochrane Library ◽  
Wide Range ◽  
The Impact ◽  
Patient Prioritisation

ABSTRACTBackgroundConcern about long waiting times for elective surgeries is not a recent phenomenon, but it has been heightened by the impact of the COVID-19 pandemic and its associated measures. One way to alleviate the problem might be to use prioritisation methods for patients on the waiting list and a wide range of research is available on such methods. However, significant variations and inconsistencies have been reported in prioritisation protocols from various specialties, institutions, and health systems. To bridge the evidence gap in existing literature, this comprehensive systematic review will synthesise global evidence on policy strategies with a unique insight to patient prioritisation methods to reduce waiting times for elective surgeries. This will provide evidence that might help with the tremendous burden of surgical disease that is now apparent in many countries because of operations that were delayed or cancelled due to the COVID-19 pandemic and inform policy for sustainable healthcare management systems.MethodsWe searched PubMed, EMBASE, SCOPUS, Web of Science, and the Cochrane Library, with our most recent searches in January 2020. Articles published after 2013 on major elective surgery lists of adult patients were eligible, but cancer and cancer-related surgeries were excluded. Both randomised and non-randomised studies were eligible and the quality of studies was assessed with ROBINS-I and CASP tools. We registered the review in PROSPERO (CRD42019158455) and reported it in accordance with the PRISMA statement.ResultsThe electronic search in five bibliographic databases yielded 7543 records (PubMed, EMBASE, SCOPUS, Web of Science, and Cochrane) and 17 eligible articles were identified in the screening. There were four quasi-experimental studies, 11 observational studies and two systematic reviews. These demonstrated moderate to low risk of bias in their research methods. Three studies tested generic approaches using common prioritisation systems for all elective surgeries in common. The other studies assessed specific prioritisation approaches for re-ordering the waiting list for a particular surgical specialty.ConclusionsExplicit prioritisation tools with a standardised scoring system based on clear evidence-based criteria are likely to reduce waiting times and improve equitable access to health care. Multiple attributes need to be considered in defining a fair prioritisation system to overcome limitations with local variations and discriminations. Collating evidence from a diverse body of research provides a single framework to improve the quality and efficiency of elective surgical care provision in a variety of health settings. Universal prioritisation tools with vertical and horizontal equity would help with re-ordering patients on waiting lists for elective surgery and reduce waiting times.

scholarly journals Patient prioritisation methods to shorten waiting times for elective surgery: A systematic review of how to improve access to surgery

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256578
Author(s):  
Dimuthu Rathnayake ◽  
Mike Clarke ◽  
Viraj Jayasinghe
Keyword(s):  
Systematic Review ◽  
Web Of Science ◽  
Elective Surgery ◽  
Waiting Times ◽  
Healthcare Management ◽  
Waiting List ◽  
Cochrane Library ◽  
Wide Range ◽  
The Impact ◽  
Patient Prioritisation

Background Concern about long waiting times for elective surgeries is not a recent phenomenon, but it has been heightened by the impact of the COVID-19 pandemic and its associated measures. One way to alleviate the problem might be to use prioritisation methods for patients on the waiting list and a wide range of research is available on such methods. However, significant variations and inconsistencies have been reported in prioritisation protocols from various specialties, institutions, and health systems. To bridge the evidence gap in existing literature, this comprehensive systematic review will synthesise global evidence on policy strategies with a unique insight to patient prioritisation methods to reduce waiting times for elective surgeries. This will provide evidence that might help with the tremendous burden of surgical disease that is now apparent in many countries because of operations that were delayed or cancelled due to the COVID-19 pandemic and inform policy for sustainable healthcare management systems. Methods We searched PubMed, EMBASE, SCOPUS, Web of Science, and the Cochrane Library, with our most recent searches in January 2020. Articles published after 2013 on major elective surgery lists of adult patients were eligible, but cancer and cancer-related surgeries were excluded. Both randomised and non-randomised studies were eligible and the quality of studies was assessed with ROBINS-I and CASP tools. We registered the review in PROSPERO (CRD42019158455) and reported it in accordance with the PRISMA statement. Results The electronic search in five bibliographic databases yielded 7543 records (PubMed, EMBASE, SCOPUS, Web of Science, and Cochrane) and 17 eligible articles were identified in the screening. There were four quasi-experimental studies, 11 observational studies and two systematic reviews. These demonstrated moderate to low risk of bias in their research methods. Three studies tested generic approaches using common prioritisation systems for all elective surgeries in common. The other studies assessed specific prioritisation approaches for re-ordering the waiting list for a particular surgical specialty. Conclusions Explicit prioritisation tools with a standardised scoring system based on clear evidence-based criteria are likely to reduce waiting times and improve equitable access to health care. Multiple attributes need to be considered in defining a fair prioritisation system to overcome limitations with local variations and discriminations. Collating evidence from a diverse body of research provides a single framework to improve the quality and efficiency of elective surgical care provision in a variety of health settings. Universal prioritisation tools with vertical and horizontal equity would help with re-ordering patients on waiting lists for elective surgery and reduce waiting times.

scholarly journals Sitting Postures and Activities in Autonomous Vehicles – New Requirements towards Occupant Safety

2019 ◽  
Vol 63 (1) ◽  
pp. 1874-1878
Author(s):  
Anna-Lena Köhler ◽  
Julia Pelzer ◽  
Kristian Seidel ◽  
Stefan Ladwig
Keyword(s):  
Autonomous Vehicles ◽  
Degrees Of Freedom ◽  
User Study ◽  
Autonomous Driving ◽  
Test Case ◽  
Automated Driving ◽  
Occupant Safety ◽  
Safety Requirements ◽  
Technological Developments ◽  
The Impact

In the context of autonomous driving, new possibilities for passenger positions and occupation arise. Vehicle concepts provide more degrees of freedom for seating configurations and different activities as a passenger, leading to a need for advanced protection principles. The H2020-project OSCCAR analyses occupant safety requirements for highly automated vehicles (HAV) and defines technological developments necessary for novel safety principles. In order to understand the potential of novel sitting postures and activities in the context of autonomous driving, an empirical user study was conducted to examine the impact of different scenarios on preferred sitting postures in a simulated automated driving situation. Results gave insights into detailed sitting postures that are most likely to be obtained by occupants in future use cases. The results serve as input to a test case matrix in order to design future occupant restraint principles.

The potential effects of autonomous vehicles on walking

2021 ◽  
pp. 175797592110192
Author(s):  
Simone Pettigrew
Keyword(s):  
Traffic Congestion ◽  
Trade Unions ◽  
Policy Development ◽  
Autonomous Vehicles ◽  
Transportation Systems ◽  
Central Feature ◽  
The European Union ◽  
Vehicle Ownership ◽  
Walking Activity ◽  
Wide Range

Vehicle automation is progressing rapidly and autonomous vehicles (AVs) are forecast to become a central feature of transportation systems globally. This development has the potential to result in profound changes in walking behaviors. The present study examined this issue from the perspective of relevant experts for the purpose of informing health policy. Interviews were conducted with 44 key stakeholders in Australia ( n = 34), the European Union ( n = 5), the UK ( n = 4), and the US ( n = 1). The stakeholders represented a wide range of sectors including government, AV manufacturing/servicing companies, transport policy consortiums, technology firms, insurers (public and private), trade unions, consumer representation organizations, and academia. Two potential scenarios were evident in interviewees’ discussions of the ways AVs are likely to be introduced and the implications for walking behaviors. The most beneficial scenario, but the least likely to eventuate, was considered to be the situation where people relinquish private vehicle ownership and rely on a combination of walking, public transport, and on-demand transport. The alternative scenario involved greater private AV ownership, traffic congestion, and urban sprawl, resulting in less walking activity. The convergence of the stakeholders’ views around the opposing identified scenarios highlights the need for proactive policy development to ensure the emerging transport transformation does not result in substantial increases in sedentarism.

scholarly journals On-Board Road Friction Estimation Technique for Autonomous Driving Vehicle-Following Maneuvers

2021 ◽  
Vol 11 (5) ◽  
pp. 2197
Author(s):  
Stefania Santini ◽  
Nicola Albarella ◽  
Vincenzo Maria Arricale ◽  
Renato Brancati ◽  
Aleksandr Sakhnevych
Keyword(s):  
Environmental Conditions ◽  
Autonomous Vehicles ◽  
Heavy Rain ◽  
Autonomous Driving ◽  
The State ◽  
Driver Assistance Systems ◽  
Model Based ◽  
Wide Range ◽  
Road Friction ◽  
Friction Estimation

In recent years, autonomous vehicles and advanced driver assistance systems have drawn a great deal of attention from both research and industry, because of their demonstrated benefit in reducing the rate of accidents or, at least, their severity. The main flaw of this system is related to the poor performances in adverse environmental conditions, due to the reduction of friction, which is mainly related to the state of the road. In this paper, a new model-based technique is proposed for real-time road friction estimation in different environmental conditions. The proposed technique is based on both bicycle model to evaluate the state of the vehicle and a tire Magic Formula model based on a slip-slope approach to evaluate the potential friction. The results, in terms of the maximum achievable grip value, have been involved in autonomous driving vehicle-following maneuvers, as well as the operating condition of the vehicle at which such grip value can be reached. The effectiveness of the proposed approach is disclosed via an extensive numerical analysis covering a wide range of environmental, traffic, and vehicle kinematic conditions. Results confirm the ability of the approach to properly automatically adapting the inter-vehicle space gap and to avoiding collisions also in adverse road conditions (e.g., ice, heavy rain).

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