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Volvo Summer Workshop Track 2: Urban Transportation Physics. Carlos Daganzo. Outline. Focus Mass motions in cities How things work? New technologies New policies. Projects BLIPS Green Logistics Gridlock Self synchronizing buses Evacuation Safety. BLIP Concept.
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Volvo Summer WorkshopTrack 2: Urban Transportation Physics Carlos Daganzo
Outline • Focus • Mass motions in cities • How things work? • New technologies • New policies • Projects • BLIPS • Green Logistics • Gridlock • Self synchronizing buses • Evacuation • Safety
BLIP Concept • Right lane reserved for bus but open to traffic when bus is not near by, like IBL. • CMS and in-pavement lights dynamically restrict and allow access to lane. • One CMS per block • Rules of the road: Drivers bound by CMS message until next CMS is reached. Eichler and Daganzo, 2005, Bus Lanes with Intermittent Priority: Assessment and Design
Complexity Fades Away Results do not rely on particulars of how the “cocoon” is achieved. One example of cocoon formation.
Green Logistics – Implemented schemes Geroliminis and Daganzo (2005), A review of green logistics schemes used in cities around the world
Water use - Coordinated transport A DHL-boat sails through the canals and serves as base-centre for bicycle-couriers • reduction of 150.000 van-km / year • TOTAL COST: 7,000€ Amsterdam - Floating Distribution Centre
Clean vehicles • hybrid (clean and quiet) and energy efficient electric vehicles • urban distribution centre (UDC) • large trucks for long-distance transport to and from the UDC and of vans and small trucks for the centre. combining an efficient goods distribution concept with the environmental impact of electric vehicle transport Rotterdam - ELectric vehicle CIty DIstribution System Total Cost: 1.2 million EURO
Conclusions • Promising city logistics schemes with “green” characteristics • Largest and fastest growing cities in the developing world: ABSENT • Schemes can be combined, adapted and modified to be of use (HOW? Research is necessary)
Gridlock In Cities Nikolas Geroliminis
Self-Stabilizing Bus Routes Josh Pilachowski
Statement of Problem • Two parts of travel time • Time to travel between stops • Time to pick up and drop off passengers • Bus routes by their very nature are unstable • Demand is stochastic • Small variation in demand can create large instability over time without control • Queue proportional to headway • Increased demand Slows bus Larger headway Increased demand • Decreased demand Speeds up bus Smaller headway Decreased demand • Buses eventually come together and act as a single unit
Sustainability • Attracting Ridership • Minimum ridership needed to derive environmental benefits • Ridership from necessity as opposed to desire • Spare-the-Air days • Inherent Instability • Routes with smaller headways are more unstable • Smaller headways comes from higher use • Equity • Bus vs. Rail
Control Methods • Station Control • Holding • Station Skipping • Interstation Control • Speed Control* • Traffic Signal Preemption • Other • Adding/Removing Vehicles • Early Turns
Existing Controls • Instability still exists • Not many controls to alleviate this • Establish slack time • Estimate delays on route and add a fixed amount to the expected trip time • Control points • Determine certain stops as control points • If a bus arrives at a control point ahead of schedule it waits there
Existing Controls • Expand on the idea of control points • By increasing the number of control points errors have less time to propagate • Control points require slack time built into the schedule • A bus behind schedule cannot make up lost time easily • Passengers don’t like sitting on the side of the road • Station Control Interstation Control • Continuous control points become speed control
Speed Control • Dynamic stabilization • AVL allows buses to continually locate adjacent buses • Replace slack time with a lower cruising velocity • Allows buses to speed up to make up lost time • Buses can slow down if they get too far ahead • Trade off travel time for stability • Lower average velocity (maybe) but lower variance • Users have a higher cost for waiting time than for travel time
Possible Methods of Stabilization • Spring based stabilization • Springs connecting adjacent buses • k = spring constant • ‘force’ based on spacing or headway • F = k(hi – hi+1) • v = vt + k Dt hi – k Dt hi+1 • Unscheduled stabilized headways
Model Description • State Space: • yi(t) - spacing • hi(t) - headway • Variables • l - demand • b - loss time per pax • vt - target speed • E[vi(t)] = vt/(1+vtlbhi(t)) • Control: vt replaced by vi(hi(t),hi+1(t), yi(t),yi+1(t))
Testing the Model • Simulation • Simple simulation • Moves buses according to calculated velocity • Picks up and drops off pax • Real Data • Faux bus route with students as ‘bus drivers’ • Real bus route in Gothenburg, Sweden
Future Work • Additional areas of analysis and development • Traffic • Bus velocity constrained by traffic • Parallel Bus routes • Model interaction between overlapping routes? • Create platoons? • TSP/stoplights • Handicap passengers
Logistics of City Evacuation Volvo Summer Workshop July 24, 2006 Stella So
Immobile Car-less; Challenged Car-owners New Orleans, LA 3 weeks later… Houston, TX
Minimize { “evacuation time” } • Increase capacity • Contra flow • Alternate routes • Bottleneck clearance • Manage demand • Multi-modal • ↑ pax per car • ↓ “shadow” evacuation
Houston – a disaster for car-owners A Cut-Set Analysis… 19 h 23 h 8 h 6 h
Road User Adaptation to Road Safety Measures Presented by: Offer Grembek
Road Safety and Road Safety Measures Generic risk factors Physical / Behavioral No Danger Danger Road Safety
Road Safety and Road Safety Measures Road Safety Measures (RSM) Generic risk factors Physical / Behavioral “Engineered effect” No Danger Danger Road Safety
Road Safety and Road Safety Measures Road Safety Measures (RSM) Generic risk factors Physical / Behavioral “Engineered effect” “Behavioral adaptation” No Danger Danger Road Safety
Behavioral Adaptation • What is behavioral adaptation • Seatbelts • All-red interval • Current theories about behavioral adaptation • Risk compensation theories (Wilde) • Potential Benefits • Road safety measures design and evaluation • Academic
Research Question Is the effectiveness of RSM influenced by an identifiable road-user behavioral adaptation? • Are there specific types of RSM that generate behavioral adaptation? • Are there specific conditions that generate behavioral adaptation? • Do these behavioral adaptations have a significant impact on the effectiveness of RSM? • How does the impact of these behavioral adaptations change over time?
Road Safety and Behavioral Adaptation • Inconsistencies in RSM and behavioral adaptation • Mandatory seat-belts • Center high mounted stoplights • Setbacks of using RSM studies • Statistical validity (confounding, regression-to-the-mean) • Insufficient data
The Potential of a Different Approach • Industrial safety and security • Detailed longitudinal data • Immediate consequences • Tradeoff between safety and productivity • Epidemiology • Heterogeneous study population • No visible benefits of compliance • Non-compliance due to thrill (safe-sex) • Portfolio theory • Human behavior under risk
Future Work Carlos Daganzo
Transit/City Structure Buses - Small
Transit/City Structure Buses - Medium
Transit/City Structure Rail - Small
Transit/City Structure Rail - Large