Difference: GameTheoryTraffic (1 vs. 21)

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A Distributed Approach for Coordination of Traffic Signal Agents Ana L. C. Bazzan Multiple intersections Maximize throughput and traffic saftey; minimize travel times and environmental costs Pseudo-agent multiagent learning approach Some good cites. The multiagent learning seems a little hacky
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
Traffic adaptive control of a single intersection: A taxonomy of approaches R.T. van Katwijk, B. De Schutter, and J. Hellendoorn Single Intersection Minimize the delay experienced by vehicles through manipulation of the traffic signal timings. Various, mostly MDP-type frameworks. Dynamic programming and tree-search used to optimize Good overview of adaptive controllers, but Porche & Lafortune (1997) is a better written overview
Deleted:
<
<		| [[http://paginas.fe.up.pt/~eol/PUBLICATIONS/2006/Eumas06_ITSUMO_final.pdf][Reinforcement Learning-based Control of Traffic Lights in Non-stationary Environments]] | Oliveira et al. | 9 intersection grid | Optimize light policy | Model with cellular automata, use RL learning|
 
Multi-Agent Reinforcement Learning for Traffic Control Marco Wiering 2x3 intersection Optimize Traffic lights Simlulate with discrete simulation; use RL  
Effects of Co-Evolution in a Complex Traffic Network Bazzan et al. 6x6 grid Optimize lighting control Look at Greedy or Adaptive drivers, Greedy, Adaptive, or Q-Learning lights. Small slice of agent, relatively few iterations allowed + no burn-in
Added:
>
>
Reinforcement Learning-based Control of Traffic Lights in Non-stationary Environments Oliveira et al 9 intersection grid Optimize light policy Model with cellular automata, use RL learning  
 

Other

Title Author Scope Problem Solution Comments
Line: 83 to 82
 
Traffic Calming in Three European Cities: Recent Experience Andrew Nash Three European Cities n/a n/a A laundry list of how Zurich, Vienna, and Munich have dealt with traffic calming
Learning Cooperative Lane Selection Strategies for Highways D. Moriarty and P Langley Single highway How should 'smart cars' switch lanes in a highway? Evolutionary algorithms Strange problem setting (a device that tells you what lane you should be in, once you give it a speed preference?), strange solution
Implementation of the OPAC adaptive control strategy in a traffic signal network Nathan H. Gartner et al. Multiple intersection Minimize delays and stops Rolling horizon tree-search approach, which synchronization layer Seems like a good approach, similar to ALLONS-D in goals and motivations. Gartner has other publications, and seems to cite few other people than himself... draw your own conclusions :)
Changed:
<
<
[http://delivery.acm.org/10.1145/310000/301193/p198-rogers.pdf?key1=301193&key2=1550070911&coll=GUIDE&dl=GUIDE&CFID=626325&CFTOKEN=63227024][An Adaptive Interactive Agent for Route Advice]] S Rogers, C Fiechter, P Langley route advice system How to build an adaptive interactive agent to generate route advice based on user preferences Agent generates route choices and update user model by observing feedback from user, assign costs to attributes of roads (travel time, length, road type) pretty simple approach, using some kind of learning/optimization, possible future work include better learning algorithm + taking into account of dynamic attributes (current road conditions)
>
>
An Adaptive Interactive Agent for Route Advice S Rogers, C Fiechter, P Langley route advice system How to build an adaptive interactive agent to generate route advice based on user preferences Agent generates route choices and update user model by observing feedback from user, assign costs to attributes of roads (travel time, length, road type) pretty simple approach, using some kind of learning/optimization, possible future work include better learning algorithm + taking into account of dynamic attributes (current road conditions)
 
A Collaborative Driving System Based on Multiagent Modelling and Simulations S Halle, B Chaib-draa some automated cars on a straight, one way, two lanes, highway segment which are good coordination models for collaborative driving system (platoons of collaborating vehicles) compared to centralized model, the multiagent teamwork model is more safe and flexible, but requires more messages to be communicated. part of the Automobile of the 21st Century (Auto21) supported by Government of Canada, interesting idea, try to tackle traffic from driving perspective instead of from redesigning traffic facilities
The Network Effects of Alternative Road Pricing Systems A D May et al network analysis done for city of Cambridge and York which 4 charging systems perform better in terms of its positive impact on traffic distribution network analysis produced different results than conceptual analysis, possible future work include incorporating dynamic route guidance so that drivers are aware of the possible charges in advance good facts about realistic charging systems for road use - make me wonder how highway 407 in Toronto does the charging.
Title Author Scope Problem Solution Comments

Revision 202007-10-11 - ErikZawadzki

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  1. Mode selection

Software:

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GIS Sources

Simulators

Commercial

 
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Papers

Added:
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>

Traffic Light Optimization

 
Title Author Scope Problem Solution Comments
Changed:
<
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Traffic Intersections of the Future K Dresner and P Stone Single intersection, automated drivers Increased efficiency and throughput Tile-based Reservation Good references
Using Intelligent Agents for Urban Traffic Control Systems D Roozemond Multi-Intersection, human-controlled vehicles General optimizing framework Rule-based pseudo-agent approach Terrible paper, no real content
>
>
Adaptive Look-Ahead Optimization of Traffic Signals Porche & Lafortune Single intersection, extension to multiple Minimize total delay Build an MDP, tree-search (Branch and Boundy) Good overview and taxonomy of different adaptive controllers. Presents ALLONS-D.
 
Optimizing Networks of Traffic Signals in Real Time - The SCOOT Method D Robertson and R Bretherton multiple intersections, human-controlled vehicles To minimize queues and vehicles stops at intersection SCOOT improved on TRANSYT (signal coordination based on fixed time plans) (1) measure CFP in real time (2) update online model of queues continuously (3) incremental optimization of signal settings Definitely a useful real scenario on signal coordination technique
Deleted:
<
<
10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
 
A Distributed Approach for Coordination of Traffic Signal Agents Ana L. C. Bazzan Multiple intersections Maximize throughput and traffic saftey; minimize travel times and environmental costs Pseudo-agent multiagent learning approach Some good cites. The multiagent learning seems a little hacky
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
Added:
>
>
Traffic adaptive control of a single intersection: A taxonomy of approaches R.T. van Katwijk, B. De Schutter, and J. Hellendoorn Single Intersection Minimize the delay experienced by vehicles through manipulation of the traffic signal timings. Various, mostly MDP-type frameworks. Dynamic programming and tree-search used to optimize Good overview of adaptive controllers, but Porche & Lafortune (1997) is a better written overview
| [[http://paginas.fe.up.pt/~eol/PUBLICATIONS/2006/Eumas06_ITSUMO_final.pdf][Reinforcement Learning-based Control of Traffic Lights in Non-stationary Environments]] | Oliveira et al. | 9 intersection grid | Optimize light policy | Model with cellular automata, use RL learning|
Multi-Agent Reinforcement Learning for Traffic Control Marco Wiering 2x3 intersection Optimize Traffic lights Simlulate with discrete simulation; use RL  
Effects of Co-Evolution in a Complex Traffic Network Bazzan et al. 6x6 grid Optimize lighting control Look at Greedy or Adaptive drivers, Greedy, Adaptive, or Q-Learning lights. Small slice of agent, relatively few iterations allowed + no burn-in

Other

Title Author Scope Problem Solution Comments
Traffic Intersections of the Future K Dresner and P Stone Single intersection, automated drivers Increased efficiency and throughput Tile-based Reservation Good references
Using Intelligent Agents for Urban Traffic Control Systems D Roozemond Multi-Intersection, human-controlled vehicles General optimizing framework Rule-based pseudo-agent approach Terrible paper, no real content
10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
 
Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 possible routes, 2 travellers, 1 person as road authority (road pricing) model as 3 types of games: Cournot, Stackelberg and social planner game For different objectives, multiple optimal solutions exist. the objective functions may have a non-continuous shape toy problem but interesting, definitely could be extended
Fictitious play for finding system optimal routings in dynamic traffic networks A Garcia et al some simulated traffic network with travellers (dynamic traffic assignment) minimize average trip time experienced in the network use repeated play of fictitious games that eventually weakly converge to a local system optimal routing (Alliance software) "assuming minimizing average travel time is common interests of all travellers" is a little too simplistic.
Optimal Dimensions of Bus Service Zones S K Chang and P M Schonfeld urban area divided into bus service zones (public transport system) optimize design of urban bus service zones by jointly optimizing decision variables (service headway, route spacing, route length, demand density) analytic optimization model optimization based on static data - i guess they can't change bus routes all the time, lots of references about optimizing design of transit systems
Deleted:
<
<
Traffic adaptive control of a single intersection: A taxonomy of approaches R.T. van Katwijk, B. De Schutter, and J. Hellendoorn Single Intersection Minimize the delay experienced by vehicles through manipulation of the traffic signal timings. Various, mostly MDP-type frameworks. Dynamic programming and tree-search used to optimize Good overview of adaptive controllers, but Porche & Lafortune (1997) is a better written overview
Adaptive Look-Ahead Optimization of Traffic Signals Porche & Lafortune Single intersection, extension to multiple Minimize total delay Build an MDP, tree-search (Branch and Boundy) Good overview and taxonomy of different adaptive controllers. Presents ALLONS-D.
 
Passenger Arrival Rates at Public Transport Stations Marco Luethi, Ulrich Weidmann, Andrew Nash Zürich How does one model passenger arrival statistically, given bus frequency Uniform distribution with shifted Johnson distribution Summarizes some previous approaches to modeling arrival rates. Worried about overfitting, and how general this result is (data collected in Zürich)
Traffic Calming in Three European Cities: Recent Experience Andrew Nash Three European Cities n/a n/a A laundry list of how Zurich, Vienna, and Munich have dealt with traffic calming
Learning Cooperative Lane Selection Strategies for Highways D. Moriarty and P Langley Single highway How should 'smart cars' switch lanes in a highway? Evolutionary algorithms Strange problem setting (a device that tells you what lane you should be in, once you give it a speed preference?), strange solution
Implementation of the OPAC adaptive control strategy in a traffic signal network Nathan H. Gartner et al. Multiple intersection Minimize delays and stops Rolling horizon tree-search approach, which synchronization layer Seems like a good approach, similar to ALLONS-D in goals and motivations. Gartner has other publications, and seems to cite few other people than himself... draw your own conclusions :)
Changed:
<
<
An Adaptive Interactive Agent for Route Advice S Rogers, C Fiechter, P Langley route advice system How to build an adaptive interactive agent to generate route advice based on user preferences Agent generates route choices and update user model by observing feedback from user, assign costs to attributes of roads (travel time, length, road type) pretty simple approach, using some kind of learning/optimization, possible future work include better learning algorithm + taking into account of dynamic attributes (current road conditions)
>
>
[http://delivery.acm.org/10.1145/310000/301193/p198-rogers.pdf?key1=301193&key2=1550070911&coll=GUIDE&dl=GUIDE&CFID=626325&CFTOKEN=63227024][An Adaptive Interactive Agent for Route Advice]] S Rogers, C Fiechter, P Langley route advice system How to build an adaptive interactive agent to generate route advice based on user preferences Agent generates route choices and update user model by observing feedback from user, assign costs to attributes of roads (travel time, length, road type) pretty simple approach, using some kind of learning/optimization, possible future work include better learning algorithm + taking into account of dynamic attributes (current road conditions)
 
A Collaborative Driving System Based on Multiagent Modelling and Simulations S Halle, B Chaib-draa some automated cars on a straight, one way, two lanes, highway segment which are good coordination models for collaborative driving system (platoons of collaborating vehicles) compared to centralized model, the multiagent teamwork model is more safe and flexible, but requires more messages to be communicated. part of the Automobile of the 21st Century (Auto21) supported by Government of Canada, interesting idea, try to tackle traffic from driving perspective instead of from redesigning traffic facilities
The Network Effects of Alternative Road Pricing Systems A D May et al network analysis done for city of Cambridge and York which 4 charging systems perform better in terms of its positive impact on traffic distribution network analysis produced different results than conceptual analysis, possible future work include incorporating dynamic route guidance so that drivers are aware of the possible charges in advance good facts about realistic charging systems for road use - make me wonder how highway 407 in Toronto does the charging.
Added:
>
>
Title Author Scope Problem Solution Comments
Title Author Scope Problem Solution Comments
 

Revision 192007-10-10 - ErikZawadzki

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Revision 182007-09-25 - ErikZawadzki

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    1. Routes and schedules
  2. Road tolls
    1. Parking restictions
Added:
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  1. Route and departure guidance
 

Commuter Decisions

  1. Trip/Route planning
  2. Mode selection

Revision 172007-09-25 - XiAliceGao

Line: 1 to 1
 
META TOPICPARENT name="WebHome"
-- ErikZawadzki - 07 Sep 2007
Line: 60 to 60
 
10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
A Distributed Approach for Coordination of Traffic Signal Agents Ana L. C. Bazzan Multiple intersections Maximize throughput and traffic saftey; minimize travel times and environmental costs Pseudo-agent multiagent learning approach Some good cites. The multiagent learning seems a little hacky
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
Changed:
<
<
Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority (road pricing) model as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
>
>
Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 possible routes, 2 travellers, 1 person as road authority (road pricing) model as 3 types of games: Cournot, Stackelberg and social planner game For different objectives, multiple optimal solutions exist. the objective functions may have a non-continuous shape toy problem but interesting, definitely could be extended
 
Fictitious play for finding system optimal routings in dynamic traffic networks A Garcia et al some simulated traffic network with travellers (dynamic traffic assignment) minimize average trip time experienced in the network use repeated play of fictitious games that eventually weakly converge to a local system optimal routing (Alliance software) "assuming minimizing average travel time is common interests of all travellers" is a little too simplistic.
Changed:
<
<
Optimal Dimensions of Bus Service Zones S K Chang and P M Schonfeld bus transit systems (public transport system) optimize design of urban bus service zones by jointly optimizing decision variables analytic optimization model lots of references about optimizing design of transit systems
>
>
Optimal Dimensions of Bus Service Zones S K Chang and P M Schonfeld urban area divided into bus service zones (public transport system) optimize design of urban bus service zones by jointly optimizing decision variables (service headway, route spacing, route length, demand density) analytic optimization model optimization based on static data - i guess they can't change bus routes all the time, lots of references about optimizing design of transit systems
 
Traffic adaptive control of a single intersection: A taxonomy of approaches R.T. van Katwijk, B. De Schutter, and J. Hellendoorn Single Intersection Minimize the delay experienced by vehicles through manipulation of the traffic signal timings. Various, mostly MDP-type frameworks. Dynamic programming and tree-search used to optimize Good overview of adaptive controllers, but Porche & Lafortune (1997) is a better written overview
Adaptive Look-Ahead Optimization of Traffic Signals Porche & Lafortune Single intersection, extension to multiple Minimize total delay Build an MDP, tree-search (Branch and Boundy) Good overview and taxonomy of different adaptive controllers. Presents ALLONS-D.
Passenger Arrival Rates at Public Transport Stations Marco Luethi, Ulrich Weidmann, Andrew Nash Zürich How does one model passenger arrival statistically, given bus frequency Uniform distribution with shifted Johnson distribution Summarizes some previous approaches to modeling arrival rates. Worried about overfitting, and how general this result is (data collected in Zürich)
Line: 70 to 70
 
Learning Cooperative Lane Selection Strategies for Highways D. Moriarty and P Langley Single highway How should 'smart cars' switch lanes in a highway? Evolutionary algorithms Strange problem setting (a device that tells you what lane you should be in, once you give it a speed preference?), strange solution
Implementation of the OPAC adaptive control strategy in a traffic signal network Nathan H. Gartner et al. Multiple intersection Minimize delays and stops Rolling horizon tree-search approach, which synchronization layer Seems like a good approach, similar to ALLONS-D in goals and motivations. Gartner has other publications, and seems to cite few other people than himself... draw your own conclusions :)
An Adaptive Interactive Agent for Route Advice S Rogers, C Fiechter, P Langley route advice system How to build an adaptive interactive agent to generate route advice based on user preferences Agent generates route choices and update user model by observing feedback from user, assign costs to attributes of roads (travel time, length, road type) pretty simple approach, using some kind of learning/optimization, possible future work include better learning algorithm + taking into account of dynamic attributes (current road conditions)
Added:
>
>
A Collaborative Driving System Based on Multiagent Modelling and Simulations S Halle, B Chaib-draa some automated cars on a straight, one way, two lanes, highway segment which are good coordination models for collaborative driving system (platoons of collaborating vehicles) compared to centralized model, the multiagent teamwork model is more safe and flexible, but requires more messages to be communicated. part of the Automobile of the 21st Century (Auto21) supported by Government of Canada, interesting idea, try to tackle traffic from driving perspective instead of from redesigning traffic facilities
The Network Effects of Alternative Road Pricing Systems A D May et al network analysis done for city of Cambridge and York which 4 charging systems perform better in terms of its positive impact on traffic distribution network analysis produced different results than conceptual analysis, possible future work include incorporating dynamic route guidance so that drivers are aware of the possible charges in advance good facts about realistic charging systems for road use - make me wonder how highway 407 in Toronto does the charging.
 

Revision 162007-09-25 - XiAliceGao

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META TOPICPARENT name="WebHome"
-- ErikZawadzki - 07 Sep 2007
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Traffic Calming in Three European Cities: Recent Experience Andrew Nash Three European Cities n/a n/a A laundry list of how Zurich, Vienna, and Munich have dealt with traffic calming
Learning Cooperative Lane Selection Strategies for Highways D. Moriarty and P Langley Single highway How should 'smart cars' switch lanes in a highway? Evolutionary algorithms Strange problem setting (a device that tells you what lane you should be in, once you give it a speed preference?), strange solution
Implementation of the OPAC adaptive control strategy in a traffic signal network Nathan H. Gartner et al. Multiple intersection Minimize delays and stops Rolling horizon tree-search approach, which synchronization layer Seems like a good approach, similar to ALLONS-D in goals and motivations. Gartner has other publications, and seems to cite few other people than himself... draw your own conclusions :)
Added:
>
>
An Adaptive Interactive Agent for Route Advice S Rogers, C Fiechter, P Langley route advice system How to build an adaptive interactive agent to generate route advice based on user preferences Agent generates route choices and update user model by observing feedback from user, assign costs to attributes of roads (travel time, length, road type) pretty simple approach, using some kind of learning/optimization, possible future work include better learning algorithm + taking into account of dynamic attributes (current road conditions)
 

Revision 152007-09-24 - ErikZawadzki

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META TOPICPARENT name="WebHome"
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Added:
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Problem Description

Objectives

  1. Minimize delays, stops, trip times, queue size
  2. Maximize 'bandwidths'

Planning Measures

  1. Optimize intersection timing
    1. Adding more sensors
    2. Single intersection/multiple (costly/noisy communication model?)
  2. Public transit
    1. Fares
    2. Routes and schedules
  3. Road tolls
    1. Parking restictions

Commuter Decisions

  1. Trip/Route planning
  2. Mode selection
 

Software:

Line: 13 to 30
 
Changed:
<
<

Adaptive Traffic Algorithms

  • ALLONS-D - online and distributed, arbitrary-cycle, tree-search optimization, local/regional
  • SPOT/UTOPIA - online and distributed, arbitrary-cycle, local/regional
  • OPAC - online and distributed, arbitrary-cycle, local
>
>

Traffic Adaptive Control Systems

  • ALLONS-D - online and distributed, arbitrary-cycle, tree-search optimization, local/regional. UMich.
  • SPOT/UTOPIA - online and distributed, arbitrary-cycle, local/regional. Designed by the FIAT Research Centre
  • OPAC - online and distributed, arbitrary-cycle, local/regional
 
  • SPPORT - online and distributed, arbitrary-cycle, local
  • PRODYN - online and distributed, arbitrary-cycle, local
  • SCOOT - online and centralized, fixed-cycle, regional
Line: 50 to 67
 
Adaptive Look-Ahead Optimization of Traffic Signals Porche & Lafortune Single intersection, extension to multiple Minimize total delay Build an MDP, tree-search (Branch and Boundy) Good overview and taxonomy of different adaptive controllers. Presents ALLONS-D.
Passenger Arrival Rates at Public Transport Stations Marco Luethi, Ulrich Weidmann, Andrew Nash Zürich How does one model passenger arrival statistically, given bus frequency Uniform distribution with shifted Johnson distribution Summarizes some previous approaches to modeling arrival rates. Worried about overfitting, and how general this result is (data collected in Zürich)
Traffic Calming in Three European Cities: Recent Experience Andrew Nash Three European Cities n/a n/a A laundry list of how Zurich, Vienna, and Munich have dealt with traffic calming
Changed:
<
<
Learning Cooperative Lane Selection Strategies for Highways D. Moriarty and P Langley Single highway How should 'smart cars' switch lanes in a highway? Evolutionary algorithms Strange problem setting (a device that tells you what lane you should be in, once you give it a speed preference?), strange solution
>
>
Learning Cooperative Lane Selection Strategies for Highways D. Moriarty and P Langley Single highway How should 'smart cars' switch lanes in a highway? Evolutionary algorithms Strange problem setting (a device that tells you what lane you should be in, once you give it a speed preference?), strange solution
Implementation of the OPAC adaptive control strategy in a traffic signal network Nathan H. Gartner et al. Multiple intersection Minimize delays and stops Rolling horizon tree-search approach, which synchronization layer Seems like a good approach, similar to ALLONS-D in goals and motivations. Gartner has other publications, and seems to cite few other people than himself... draw your own conclusions :)
 

Revision 142007-09-24 - ErikZawadzki

Line: 1 to 1
 
META TOPICPARENT name="WebHome"
-- ErikZawadzki - 07 Sep 2007

Software:

Added:
>
>
 
Deleted:
<
<
 

Adaptive Traffic Algorithms

Changed:
<
<
  • SCOOT (http://www.scoot-utc.com/) (evolved from TRANSYT) by TRL
  • UTOPIA-SPOT by PEEK traffic solutions (optimises a network of controlled intersections)
  • MOVA by TRL (strategy for controlling traffic signals at isolated junctions or stand-alone pedestrian crossing)
  • LHOVRA (Sweden)
  • PASSER
  • Prodyn
  • OPAC
  • OFSET
>
>
  • ALLONS-D - online and distributed, arbitrary-cycle, tree-search optimization, local/regional
  • SPOT/UTOPIA - online and distributed, arbitrary-cycle, local/regional
  • OPAC - online and distributed, arbitrary-cycle, local
  • SPPORT - online and distributed, arbitrary-cycle, local
  • PRODYN - online and distributed, arbitrary-cycle, local
  • SCOOT - online and centralized, fixed-cycle, regional
  • TRANSYT - offline and centralized, fixed-cycle, regional
  • SCATS - offline and centralized, fixed-cycle, regional
  • Webster's Equisaturation - offline and centralized, fixed-cycle, regional
 

People

Line: 46 to 46
 
Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority (road pricing) model as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
Fictitious play for finding system optimal routings in dynamic traffic networks A Garcia et al some simulated traffic network with travellers (dynamic traffic assignment) minimize average trip time experienced in the network use repeated play of fictitious games that eventually weakly converge to a local system optimal routing (Alliance software) "assuming minimizing average travel time is common interests of all travellers" is a little too simplistic.
Optimal Dimensions of Bus Service Zones S K Chang and P M Schonfeld bus transit systems (public transport system) optimize design of urban bus service zones by jointly optimizing decision variables analytic optimization model lots of references about optimizing design of transit systems
Added:
>
>
Traffic adaptive control of a single intersection: A taxonomy of approaches R.T. van Katwijk, B. De Schutter, and J. Hellendoorn Single Intersection Minimize the delay experienced by vehicles through manipulation of the traffic signal timings. Various, mostly MDP-type frameworks. Dynamic programming and tree-search used to optimize Good overview of adaptive controllers, but Porche & Lafortune (1997) is a better written overview
Adaptive Look-Ahead Optimization of Traffic Signals Porche & Lafortune Single intersection, extension to multiple Minimize total delay Build an MDP, tree-search (Branch and Boundy) Good overview and taxonomy of different adaptive controllers. Presents ALLONS-D.
Passenger Arrival Rates at Public Transport Stations Marco Luethi, Ulrich Weidmann, Andrew Nash Zürich How does one model passenger arrival statistically, given bus frequency Uniform distribution with shifted Johnson distribution Summarizes some previous approaches to modeling arrival rates. Worried about overfitting, and how general this result is (data collected in Zürich)
Traffic Calming in Three European Cities: Recent Experience Andrew Nash Three European Cities n/a n/a A laundry list of how Zurich, Vienna, and Munich have dealt with traffic calming
Learning Cooperative Lane Selection Strategies for Highways D. Moriarty and P Langley Single highway How should 'smart cars' switch lanes in a highway? Evolutionary algorithms Strange problem setting (a device that tells you what lane you should be in, once you give it a speed preference?), strange solution
 

Revision 132007-09-23 - XiAliceGao

Line: 1 to 1
 
META TOPICPARENT name="WebHome"
-- ErikZawadzki - 07 Sep 2007
Line: 45 to 45
 
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority (road pricing) model as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
Fictitious play for finding system optimal routings in dynamic traffic networks A Garcia et al some simulated traffic network with travellers (dynamic traffic assignment) minimize average trip time experienced in the network use repeated play of fictitious games that eventually weakly converge to a local system optimal routing (Alliance software) "assuming minimizing average travel time is common interests of all travellers" is a little too simplistic.
Added:
>
>
Optimal Dimensions of Bus Service Zones S K Chang and P M Schonfeld bus transit systems (public transport system) optimize design of urban bus service zones by jointly optimizing decision variables analytic optimization model lots of references about optimizing design of transit systems
 

Revision 122007-09-23 - XiAliceGao

Line: 1 to 1
 
META TOPICPARENT name="WebHome"
-- ErikZawadzki - 07 Sep 2007
Line: 43 to 43
 
10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
A Distributed Approach for Coordination of Traffic Signal Agents Ana L. C. Bazzan Multiple intersections Maximize throughput and traffic saftey; minimize travel times and environmental costs Pseudo-agent multiagent learning approach Some good cites. The multiagent learning seems a little hacky
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
Changed:
<
<
Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority model road pricing problem as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
>
>
Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority (road pricing) model as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
Fictitious play for finding system optimal routings in dynamic traffic networks A Garcia et al some simulated traffic network with travellers (dynamic traffic assignment) minimize average trip time experienced in the network use repeated play of fictitious games that eventually weakly converge to a local system optimal routing (Alliance software) "assuming minimizing average travel time is common interests of all travellers" is a little too simplistic.
 

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10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
A Distributed Approach for Coordination of Traffic Signal Agents Ana L. C. Bazzan Multiple intersections Maximize throughput and traffic saftey; minimize travel times and environmental costs Pseudo-agent multiagent learning approach Some good cites. The multiagent learning seems a little hacky
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
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Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority model road pricing problem as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
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Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority model road pricing problem as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
 

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10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
A Distributed Approach for Coordination of Traffic Signal Agents Ana L. C. Bazzan Multiple intersections Maximize throughput and traffic saftey; minimize travel times and environmental costs Pseudo-agent multiagent learning approach Some good cites. The multiagent learning seems a little hacky
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
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Different Policy Objectives of the Road Pricing Problem – a Game Theory Approach D Joksimovic et al one origin-destination (OD) pair, 2 travellers, 1 person as road authority model road pricing problem as 3 types of games: Cournot, Stackelberg and social planner game Multiple optimal solutions exist. the objective functions may have a non-continuous shape scope of the problem is pretty reasonable. not much empirical studies, looks like mostly theoretical stuff.
 

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Traffic Intersections of the Future K Dresner and P Stone Single intersection, automated drivers Increased efficiency and throughput Tile-based Reservation Good references

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Adaptive Traffic Algorithms

  • SCOOT (http://www.scoot-utc.com/) (evolved from TRANSYT) by TRL
  • UTOPIA-SPOT by PEEK traffic solutions (optimises a network of controlled intersections)
  • MOVA by TRL (strategy for controlling traffic signals at isolated junctions or stand-alone pedestrian crossing)
  • LHOVRA (Sweden)
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Using Intelligent Agents for Urban Traffic Control Systems D Roozemond Multi-Intersection, human-controlled vehicles General optimizing framework Rule-based pseudo-agent approach Terrible paper, no real content
Optimizing Networks of Traffic Signals in Real Time - The SCOOT Method D Robertson and R Bretherton multiple intersections, human-controlled vehicles To minimize queues and vehicles stops at intersection SCOOT improved on TRANSYT (signal coordination based on fixed time plans) (1) measure CFP in real time (2) update online model of queues continuously (3) incremental optimization of signal settings Definitely a useful real scenario on signal coordination technique
10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
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A Distributed Approach for Coordination of Traffic Signal Agents Ana L. C. Bazzan Multiple intersections Maximize throughput and traffic saftey; minimize travel times and environmental costs Pseudo-agent multiagent learning approach Some good cites. The multiagent learning seems a little hacky
Game Theory: Potential Applications in Transportation Planning Karim A. S. Ismail Multiple intersections Finding out applications for game theory in traffic Driver timing, Road Pricing, Traffic Assignment, Public Transport, Signal Timing Looks like a good start
 

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  • LHOVRA (Sweden)
 

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Title Author Scope Problem Solution Comments
Traffic Intersections of the Future K Dresner and P Stone Single intersection, automated drivers Increased efficiency and throughput Tile-based Reservation Good references
Using Intelligent Agents for Urban Traffic Control Systems D Roozemond Multi-Intersection, human-controlled vehicles General optimizing framework Rule-based pseudo-agent approach Terrible paper, no real content
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Optimizing Networks of Traffic Signals in Real Time - The SCOOT Method D Robertson and R Bretherton multiple intersections, human-controlled vehicles To minimize queues and vehicles stops at intersection SCOOT improved on TRANSYT (signal coordination based on fixed time plans) (1) measure CFP in real time (2) update online model of queues continuously (3) incremental optimization of signal settings Definitely a useful real scenario on signal coordination technique
10 Years with LHOVRA - What are the experiences P Engstrom multiple intersections Reduce stops, delays, and accidents in rural & urban areas L=Truck Priority, H=Major road priority, O=Incident reduction, V=Variable green/yellow, R=Reduction of red light infringement Seems to be poorly translated, I didn't get much out of this paper.
 

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Traffic Intersections of the Future K Dresner and P Stone Single intersection, automated drivers Increased efficiency and throughput Tile-based Reservation Good references
Using Intelligent Agents for Urban Traffic Control Systems D Roozemond Multi-Intersection General optimizing framework Rule-based pseudo-agent approach Terrible paper, no real content
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Traffic Intersections of the Future K Dresner and P Stone Single intersection, automated drivers Increased efficiency and throughput Tile-based Reservation Good references
Using Intelligent Agents for Urban Traffic Control Systems D Roozemond Multi-Intersection, human-controlled vehicles General optimizing framework Rule-based pseudo-agent approach Terrible paper, no real content
 

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Title Author Scope Problem Solution Comments
Traffic Intersections of the Future K Dresner and P Stone Single intersection, automated drivers Increased efficiency and throughput Tile-based Reservation Good references
Using Intelligent Agents for Urban Traffic Control Systems D Roozemond Multi-Intersection General optimizing framework Rule-based pseudo-agent approach Terrible paper, no real content

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