Autonomous vehicles New technologies and new flows - Lessons from the SEVS3 for AD project

Transcription

1 Autonomous vehicles New technologies and new flows - Lessons from the SEVS3 for AD project Transport Area of Advance Lunch seminar Anders Grauers Associate Professor in Electric and Hybrid vehicle systems, Chalmers Michael Browne Professor of logistics and urban freight transport, University of Gothenburg

2 SEVS for Autonomus Drive (AD) Det automatiserade transportsystemets effekter på samhället Ett projekt inom Drive Sweden, Vinnova, Formas och Energimyndigheten. Partners: SAFER, Electromobility Centre, Chalmers, GU, Malmeken, SP, Trafikverket, Volvo Cars, VTI, Uniti, Göteborg Stad Only presenting a few of many results in this presentation!

3 How to understand introduction of autonomous vehicles Content: Important steps in technology development Niches for introduction of autonomous drive Effects on the transport system & society - Requires analysis on user level. Disclaimer: Preliminary conclusions with some speculation!

4 Important steps in AD technology Assumption: Technology development is successful. Steps in functionality: Limited roads, Limited function, Driver required Low speed, small vehicles, no passengers Low speed, any road Any speed, prepared roads Any speed, any road The goal is fully autonomous vehicles, i.e. not requiring driver, communication or central systems A Grauers

5 Why these development steps? Full AD which never requires a human driver. Small distribution Vehicle City taxi City bus certain lines Car for any road Challanges and Benefits 15 km/h 30 km/h 50 km/h 150 km/h Required sensing range 10 m 40 m 80 m 200 m Conseq. of unintended braking Conseq. of missed braking Predefined operating environment Cost savings by AD (per vehicle over 10 yr) MSEK MSEK MSEK MSEK Likely order of introduct

6 Possible vehicle introduction niches Technology step Private cars Public transport & Transport service Goods transport Limited AD on predetermined roads - driver in vehicle Limited AD on cars - driver in car Limited AD Long haul Full AD on small, low-speed vehicles. No people on-board Small low-speed distribution vehicles & small robot vehicles Full AD in low speed Low speed AD taxis, in special areas Low speed distribution vehicles (f.ex. night delivery) Full AD on predetermined & prepared roads AD city buses Full AD Long haul, Node-to-node Full AD possible on most vehicles Autonomous buses and taxis everywhere Low cost Full AD Full AD on many cars

7 Effects on transport system & society Positive effects: Cheaper transport, especially commercial vehicles, taxi, public transport Better road capacity utilization (~ 2-3 times) High accessibility for non-drivers Higher safety Negative effects - likely to require policy measures: Much more transport / travel Higher resource use A Grauers

8 Some insights Strong economic forces make AD highly likely. Development to fully autonomous vehicles likely to go via some niche vehicles AD have many positive effects Policies needed to enable AD and counteract some negative effects. We need to understand AD on the user level... as Michael Browne will present more about.

9 AD on the user level The role of use cases in understanding the bottom up perspective Michael Browne

10 Use cases personal and freight Based on the time-geographical activity based approach Travel decisions are activity based Sequences or patterns of activities and linked trips are the relevant unit of analysis Household composition, life stage and other social structures influence individual activity pattern and travel behaviour Spatial, temporal and interpersonal interdependencies constrain activity and travel behavior

11 Use case the Kungsbacka family Björn 46, works in Torslanda, travel by car, disabled Unsafe crossings Lena 43, works in Kungsbacka, travel by bike or walk to work Opening hours at store Working obligations and norms Stella 14, school in Gbrg city, bus and tram, basket in Mölndal David 10, school in Kungsbacka, mainly bikes, scouting outside Kungsbacka Public transport complicated with a wheelchair Restrictions Fear of walking alone Others need of care

12 Everyone likes flowers Mrs Rose

13 Use case Mrs Rose Runs a flower shop in Linnégatan Delivery in person is important Uses a small van for work and for commuting Knows many of her customers Last minute change plans Restrictions Seasonality and peaks Would like to increase her delivery business for flowers to private and business customers Flowers not easy to transport Has to mix family and work activities

14 It s just a parcel GotaParcel

15 Use case GotaParcel 60 consignments per round Vans need to be flexible for payload Drivers know the routes very well Traffic conditions vary with day of week and time of year Reacting to problems Variety of handling equipment Time spent at delivery point Restrictions Part of a logistics system Unpredictable demands

16 Urban deliveries: A London example (refers to the following 2 slides) Parcel operation in central London Data collected October 2016 as part of a UK EPSRC project Freight Traffic Control See website for more information

17 Manual Data (26 th Oct) Red = parking; blue = delivery/collection Source: FTC2050 Project (Cherrett, 2017)

18 Round distance: 14.8 kms Round duration: 7.82 hrs Total driving time: 1.77 hrs Total parking time: 6.05 hrs Average speed: 1.89 km/hr #parking stops: 35 #items delivered: 119 Last-mile complexity Source: FTC2050 Project (Cherrett, 2017)

19 Some insights Users have challenging and complex needs Important topics are much wider than the vehicle and transport we need to understand the logistics context Design and system questions need more research Behaviour questions (drivers, receivers, transport operators) Considerable scope for research collaboration

20 Contacts Anders Grauers, SHC Michael Browne Department of Business Administration, University of Gothenburg