This document discusses how shared autonomous vehicles could change transportation by reducing private car ownership. It covers topics like adoption rates, modeling approaches, impacts on travel behavior and transportation networks, effects of shared autonomous taxis, and implications for infrastructure planning. The key points are that shared autonomous vehicles could increase mobility access, reduce transportation costs through mobility-as-a-service models, and optimize road usage through higher vehicle occupancy.
Tech & Transit Oriented Development - The New TODLisa Nisenson
Shared use mobility & autonomous vehicles are reshaping access to transit. This presentation shows how walking, biking & transit are still transportation's backbone, and how AVs + active form new opportunities for cities of all sizes.
Tech & Transit Oriented Development - The New TODLisa Nisenson
Shared use mobility & autonomous vehicles are reshaping access to transit. This presentation shows how walking, biking & transit are still transportation's backbone, and how AVs + active form new opportunities for cities of all sizes.
Based on a future vision of a multi-modal, end-to-end UK mobility system please describe your view of the role of Customer Experience in achieving this vision and where experience from other industry sectors can be used to add value
A 5-part course for university or engineering students on transport and mobility issues (history, current situation, theoretical concepts, future and the Finnish case)
This presentation starts with the current developments from the perspective of the driver. It gives more details ons how the human can be integrated in the automotive design process
Enhancing Traffic Intersection Control with Intelligent ObjectsRudi Ball
Presented at the Urban Internet of Things 2010 - Tokyo, Japan. 28th November 2010.
Abstract: Traffic control is an old and ever growing problem in cities throughout the world. Within many cities, intersections represent bottlenecks in the flow of traffic. Evaluating intersections control is complex and difficult. Given this, intersection management is both costly and time consuming. This paper considers the potential benefits of enhancing the traffic intersection with the use of intelligent objects in vehicles. We present, compare and demonstrate a novel Vehicle Back-Off Protocol against a classical Timed Traffic Control system. Our protocol uses ad-hoc messaging, collision avoidance and shared journey plans as a means by which to reduce delay, adapt a journey and maximize the efficient usage of a traffic intersection. We use simulation to model and evaluate intersection control.
Traffic signals work with artificial intelligence venkat k - mediumusmsystem
In U.S Drivers add 81 extra hours to their arrival each year due to traffic. The other U.S. cities are also worse, these cities are known for difficult driving conditions with hills, bridges, and bikers.
A 5-part course for university or engineering students on transport and mobility issues (history, current situation, theoretical concepts, future and the Finnish case)
2016 D-STOP Symposium ("Smart Cities") session by WNCG's Robert Heath. Get symposium details: http://ctr.utexas.edu/research/d-stop/education/annual-symposium/
Presentation by Stelios Rodoulis, of Jacobs Consulting, to a postgraduate audience at the Institute for Transport studies (ITS), University of Leeds UK. October 2015.
www.linkedin.com/in/rodoulis
www.its.leeds.ac.uk/courses/masters/programme-structure/#tabs-4
Based on a future vision of a multi-modal, end-to-end UK mobility system please describe your view of the role of Customer Experience in achieving this vision and where experience from other industry sectors can be used to add value
A 5-part course for university or engineering students on transport and mobility issues (history, current situation, theoretical concepts, future and the Finnish case)
This presentation starts with the current developments from the perspective of the driver. It gives more details ons how the human can be integrated in the automotive design process
Enhancing Traffic Intersection Control with Intelligent ObjectsRudi Ball
Presented at the Urban Internet of Things 2010 - Tokyo, Japan. 28th November 2010.
Abstract: Traffic control is an old and ever growing problem in cities throughout the world. Within many cities, intersections represent bottlenecks in the flow of traffic. Evaluating intersections control is complex and difficult. Given this, intersection management is both costly and time consuming. This paper considers the potential benefits of enhancing the traffic intersection with the use of intelligent objects in vehicles. We present, compare and demonstrate a novel Vehicle Back-Off Protocol against a classical Timed Traffic Control system. Our protocol uses ad-hoc messaging, collision avoidance and shared journey plans as a means by which to reduce delay, adapt a journey and maximize the efficient usage of a traffic intersection. We use simulation to model and evaluate intersection control.
Traffic signals work with artificial intelligence venkat k - mediumusmsystem
In U.S Drivers add 81 extra hours to their arrival each year due to traffic. The other U.S. cities are also worse, these cities are known for difficult driving conditions with hills, bridges, and bikers.
A 5-part course for university or engineering students on transport and mobility issues (history, current situation, theoretical concepts, future and the Finnish case)
2016 D-STOP Symposium ("Smart Cities") session by WNCG's Robert Heath. Get symposium details: http://ctr.utexas.edu/research/d-stop/education/annual-symposium/
Presentation by Stelios Rodoulis, of Jacobs Consulting, to a postgraduate audience at the Institute for Transport studies (ITS), University of Leeds UK. October 2015.
www.linkedin.com/in/rodoulis
www.its.leeds.ac.uk/courses/masters/programme-structure/#tabs-4
Ridesharing services are already changing the transportation paradigm. If autonomous vehicles are introduced what other impacts could they have? Is traffic going to get better…or worse? We will cover potential impacts that begin on the roadway and lead to areas that could impact society tremendously. Presented at the 2017 D-STOP Symposium.
Under-appreciated and neglected urban transport policy opportunities (and ref...Paul Barter
Presentation to 6 May 2009 event in Singapore organised by the Land Transport Authority (LTA), the Asian Development Bank (ADB) and the Centre for Liveable Cities (CLC).
Local Motors Awesome System is a self optimized sustainable autonomous vehicle system.
It is safe, affordable and enable new business models.
Join the mobility revolution.
(V3.0)
Making the Most of Long-Range Models for Automated and Connected Vehicle Planning poster was presented at the 95th Annual Transportation Research Board (TRB) Annual Meeting in January 2016.
Automated/Connected Vehicle technology (AV/CV) is expected to have significant impacts on travel behavior. The
potential transformative nature of these technologies to alter
or influence future travel behavior and demand is quite significant.
Welcome to the Connected Vehicle Training Overview. This program will give professionals an overview of overarching concepts of the connected vehicle space Mobile Comply has created the Connected Vehicle Management Overview, a highly selective two-hour course designed to give participants a basic understanding of the connected vehicle space for Future connected vehicle education and certification programs.
Autonomous cars, car sharing and electric vehiclesAnandRaoPwC
Talk presented at the second Autonomous Cars conference hosted by SwissRe in Armonk, NY on September 24, 2015. The talk covers the interaction between car sharing, autonomous cars and electric vehicles and how the feedback between these three areas will propel greater consumer adoption.
Ride Sharing, Congestion, and the Need for Real SharingJeffrey Funk
Current ride sharing services are not financially sustainable. Although they provide more convenience than do taxi services, they are experiencing massive losses because they have the same cost structure as do taxis and thus must compete through subsidies and lower wages. After all, they use the same vehicles, roads, and drivers, and only GPS algorithms and phones are new.
They also increase congestion. Just as more private vehicles or taxis on the road will increase congestion, more ride sharing vehicles also increase congestion.
These slides describe new ways to use the technologies of ride sharing to reduce congestion along with costs while at the same time keeping travel time low. This can be done through changing public transportation systems or allowing private companies to offer competing services. For instance, current bus services, whether they are private or public, need to use the algorithms, GPS, phones and other technologies of ride sharing to revise routes, schedules and the premises that currently underpin public transportation. There is no reason a bus should be certain size, stop every 200 meters, or follow the same route all day. Algorithms and phones enable new types of routes in which designers simultaneously minimize time travel and maximize number of passengers transported per vehicle.hour.
Presentation given by Dr. Chandra Bhat during SXSW '14. Dr. Bhat is the Director at the Center of Transportation Research at the University of Texas at Austin.
Mobility & Energy Futures Series: transport consumes a fifth of global energy and has a near-exclusive reliance on petroleum. As such it has an important role to play in the Energy Trilemma of reducing energy consumption and associated greenhouse gas emission, creating an energy system built on secure supplies and developing the system in ways which are affordable.
Addressing the Energy Trilemma in the transport and mobility sector is especially challenging due to the continued growth in demand for the movement of goods and people, the technical, regulatory and social challenges of moving away from an oil based system of mobility and a complex and fragmented set of stakeholders required to work together to deliver change.
Drawing on the expertise and opinions of the University of Leeds academics from different disciplines, this series will highlight the drivers, gaps and opportunities in reducing the energy consumption and carbon emissions from the transport sector in future. This is the inaugurating briefing in the series.
BREAKTHROUGH TECHNOLOGIES ARE SHAPING NEW MOBILITY SOLUTIONS AND FUTURE CITIES GrzegorzOmbach
During the next 30 years, about 70% of the population will live in megacities. This shift requires entirely new approaches to urban mobility and urban planning. We can already see many positive developments, such as electric cars, e-scooters, e-buses, autonomous electric pods, e-planes, super-fast charging, stereoscopic garages and many others. New technologies like wireless charging, batteries with 10C rate for charging and discharging, and new 5G technology for more reliable and faster data communication will help to improve current mobility solutions and create new ones. This presentation will discuss some examples that are currently under development or in a test. It will give an outlook on future urban mobility as part of a new city concept.
A presentation conducted by Professor Ram Pendyala, Transport Systems, School of Sustainable Engineering and the Built Environment, Ira A. Fulton Schools of Engineering, Arizona State University, United States of America. Presented on Tuesday the 1st of October 2013
Rapidly evolving vehicular technologies, including the advent of driverless and connected vehicles, are likely to have far-reaching implications on the design, development, provision, and financing of infrastructure in the future.
There is widespread interest in and debate on the possible impacts that autonomous vehicles will have on people’s activity travel patterns, location choices, vehicle ownership, and use of time. At the same time, ubiquitous mobile technologies and rapidly evolving communication systems
have provided the ability to access information any time anywhere, and to obtain instantaneous feedback on the
financial, temporal, energy, carbon, and health impacts of the full range of travel choices that may be exercised by users of the transport infrastructure. The gradual penetration of driverless and connected vehicles into households and business fleets over a period of time will necessitate the adaptation of existing infrastructure
to deal with a mixed fleet of autonomous and manually controlled vehicles on the transition to a fully automated transportation system. This presentation focuses on the
scenarios that may play out on the path to transport automation and the implications of the different scenarios on the design and provision of infrastructure. The presentation will draw a distinction among various emerging vehicular technologies, consider market penetration scenarios, identify the range of behavioral choices and outcomes that may result from the ownership of such vehicles, and assess the sustainability implications of emerging vehicles. While driverless vehicles may ease the stress of driving, enhance safety, reliability, and capacity utilization, and allow travelers to use travel time productively, many of these benefits do not necessarily come without costs. The convenience afforded by such
technologies may lead to dramatic shifts in work and home location choices that result in larger vehicle miles of travel – which will in turn have implications from energy, environmental, and infrastructure provision perspectives. This presentation includes a discussion of the multitude of perspectives that must be considered in planning for a driverless transportation system of the future.This presentation is the result of a collaboration between Professor Pendyala and Professors Brad Allenby and Mikhal Chester
Similar to Driving alone versus riding together - How shared autonomous vehicles can change the way we drive (20)
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
The French Revolution Class 9 Study Material pdf free download
Driving alone versus riding together - How shared autonomous vehicles can change the way we drive
1. DRIVING ALONE VERSUS RIDING
TOGETHER - HOW SHARED
AUTONOMOUS VEHICLES CAN
CHANGE THE WAY WE DRIVE
Tesla Model S
2. Key topics to cover
How quickly will they be adopted?
How can we model AV?
How will they change our transport
networks?
What are the effects of shared AV?
How will they change our cities?
What are the implications for what we
do now?
6. Adoption rate of other technologies
Others
Airbags: 0-100% in 25 years (1973-1998)
Automatic transmission: 0-80% in 70 yrs (1940’s)
Hybrid vehicles: 0-5% in 25 years (1990’s)
Smartphone: 0-80% in 9 years (2007)
8. 4S
Structure
Stochastic:
● Monte Carlo methods to draw
values from probability
distributions
● Random variable parameters
● Number of slices can be
varied
SIMULTANEOUS
Segmented:
● Comprehensive
breakdown of travel
markets (20 private + 40
CV segments)
● Behavioural parameters
vary by market segment
EXPLICIT RANDOM UTILITY
Slice:
● Takes slices of the travel
market
○ across model area
○ through probability
distributions
● Very efficient – detailed
networks, large models
Simulation:
● Uses state-machine with
very flexible transition rules
● Simulates all aspects of
travel choice
● Complex public transport
● Multimodal freight
● Easily extended
9. Key features of 4S model
No matrices, no skims, no zones, no centroid
connectors
All travel is from node to node
Models constructed with MUCH less manual effort
Usually include all roads, all paths, timetabled transit
Can build from OpenStreetMap and GTFS
Population and employment can come from multiple
sources with different zoning, including point data
(schools, hospitals etc)
Multimodal with all modes assigned
Continuous time and simultaneous choice (DTA)
Easily include any demand based effects and capacity
constraints (not just roads and transit)
Much more detailed outputs (volumes by purpose)
12. Stages of AV Modelling
Stage 1: Driver must be present but
inattentive
Stage 2: No driver required, can
sleep etc
Shared AV Taxi: single passenger
vehicles
Shared multi-occupant AV: allows
for car-sharing, however not picking
up people along a journey
13. Mobility-as-a-Service
‘Mobility-as-a-Utility’ - have a right to this service
Complete re-think of how we think of travel
Door-to-door transport service
Different payment plans - pay-as-you-go or a monthly
fee
Supports shared AV use
Huge potential to reduce car ownership
Likely to increase the efficiency and utilisation of
transport providers
Possibility for public transport to become more
competitive and affordable due to increase efficiency of
the network and the use of AVs
The model used in this analysis considers fully multi-
modal travel so in affect we already consider a basic
model for MaaS.
16. Assumptions: Value of time
Stage 1: Driver present but
inattentive
VOT multiplier: 75%-100% c.f.
standard
Stage 2: No driver required
VOT multiplier: 60%-100%
Shared AV Taxi: Assume same as
Stage 2
Shared multi-occupant AV: 65%-
100%
17. Assumptions: Trip rates
Multiple reasons for more travel
Reduced cost (perceived and actual)
Easier sharing of car within family
Reduced parking hassles
Travel by non-drivers (children, elderly,
unlicensed, disability)
Travel in non-driving state (drunk, tired)
Assume 10% increase in Stage 1
15% in Stage 2
10% for Shared AV Taxi
15% for Shared multi-occupant AV
18. Assumptions: Veh. operating costs
AV are likely to be plug in electric
Significantly lower energy cost and
maintenance costs
Even traditional ICE cars will have lower
costs due to better driving
Stage 1: 50%-75% of current VOC
Stage 2: 50% of current VOC
19. Assumptions: Capacity
Stage 1: Mixed AV and Manual
5% capacity increase
reduced crash rates and improved
operations from connected vehicles
Stage 2: 100% AV
no manually driven cars - significant
operational improvements; high density;
higher speeds; improved intersection
operations
20% capacity increase
20% improvement in free flow speeds
25% decrease in intersection delays
26. WHAT ARE THE EFFECTS OF
SHARED AUTONOMOUS VEHICLES
27. Behavioural Response to
Shared Autonomous Taxis
Change from an up front model (buy a car,
annual registration and insurance) to a pay-as-
you-go model
Lower annual cost, but higher trip cost (for
most trips)
For modelling, assume that people make
travel choices based on marginal costs
This may overstate the impact of shared AV
If people only consider annualised costs then
they will do more travel
29. Other effects of shared
Autonomous Taxis
25% drop in time spent travelling: 8.4 to 6.3 m
h/d or 76 to 56 min/person/day
55% drop in distance travelled: 269 to 147 m
km/d or 40.4 to 22 km/person/day
Increase in daily costs and drop in per capita
net utility
But annual costs are equivalent to $14-
$24/day
40% cost savings: $38 to $23/person/d
Net utility increases by $9.60/person/day
30. Effects of Multi-occupant
Shared AVs
Reduced cost leads to increased car
demand, but higher vehicle occupancy
Reduced public transport
More efficient use of road space
Better environmental outcomes (due to
higher efficiency and smaller vehicle
fleet)
34. Overall consequences
Operate AV as
improved
private cars
Big problems!
100% AV
Capacity +
speed
improves
Mitigate extra
demand
100% AV with
shared
autonomous taxis
Better operations
Reduced demand
35. Overall Consequences
Best with shared vehicles and mobility-
as-a-service
Reduce car footprint, share released road
Revolutionise transport and big changes
in urban form
36. Conclusions on Infrastructure
Will need to justify infrastructure spending based
on much shorter projected benefit streams
Best approach (as usual) would be to implement
road pricing - it could take us over the hump
Need more modelling
Time
infrastructure
requirements