Definition of theSubject
The dynamic nature of traffic networks is manifested inboth temporal and spatial changes in traffic demand, roadwaycapacities, and traffic control settings. Typically, theunderlying network traffic demand builds up over time at theonset of a peak period, varies stochastically during thepeak period, and decays at the conclusion of the peak period. Astraffic congestion builds up within a transportationnetwork, drivers may elect to either cancel their tripaltogether, alter their travel departure time, change their modeof travel, or change their route of travel. Dynamic trafficrouting is defined as the process of dynamically selecting thesequence of roadway segments from a trip origin toa trip destination. Dynamic routing entails usingtime‐dependent roadway travel times to compute thissequence of roadway segments. Consequently, the modeling ofdriver routing behavior requires the estimation of roadwaytravel times into...
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsAbbreviations
- Link or arc:
-
A roadway segment with homogeneous traffic and roadway characteristics (e. g. same number of lanes, base lane capacity, free‐flow speed, speed‐at‐capacity, and jam density). Typically networks are divided into links for traffic modeling purposes.
- Route or path:
-
A sequence of roadway segments (links or arcs) used by a driver to travel from his/her point of origin to his/her destination.
- Traffic routing:
-
The procedure that computes the sequence of roadways that minimize some utility objective function. This utility function could either be travel time or a generalized function that also includes road tolls.
- Traffic assignment:
-
The procedure used to find the link flows from the Origin‐Destination (O‐D) demand. Traffic assignment involves two steps: (1) traffic routing and (2) traffic demand loading. Traffic assignment can be divided into static, time‐dependent, and dynamic.
- User equilibrium traffic assignment:
-
The assignment of traffic on a network such that it distributes itself in a way that the travel costs on all routes used from any origin to any destination are equal, while all unused routes have equal or greater travel costs.
- System optimum traffic assignment:
-
The assignment of traffic such that the average journey travel times of all motorists is a minimum, which implies that the aggregate vehicle‐hours spent in travel is also minimum.
- Static traffic assignment:
-
Traffic assignment ignoring the temporal dimension of the problem.
- Time‐dependent traffic assignment:
-
An approximate approach to modeling the dynamic traffic assignment problem by dividing the time horizon into steady‐state time intervals and applying a static assignment to each time interval.
- Dynamic traffic assignment:
-
Traffic assignment considering the temporal dimension of the problem.
- Traffic loading:
-
The procedure of assigning O‐D demands to routes.
- Synthetic O‐D estimation:
-
The procedure that estimates O‐D demands from measured link flow counts, which includes static, time‐dependent, and dynamic.
- Traffic stream motion model:
-
A mathematical representation (traffic flow model) for traffic stream motion behavior.
- Car‐following model:
-
A mathematical representation (traffic flow model) for driver longitudinal motion behavior.
- Marginal link travel time:
-
The increase in a link's travel time resulting from an assignment of an additional vehicle to this link.
- Road pricing:
-
Road pricing is an economic concept in which drivers are charged for the use of the road facility.
Bibliography
Abdel‐Aty MA, Kitamura R, Jovanis PP (1997) Using Stated Preference Data for Studying the Effect of Advanced Traffic Information on Drivers' Route Choice. Transp Res Part C:(Emerg Technol) 5(1):39–50
Abdelfatah AS, Mahmassani HS (2001) A simulation‐based signal optimization algorithm within a dynamic traffic assignment framework. IEEE Intelligent Transportation Systems Proceedings, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC 2001, Oakland
Abdelghany AF, Abdelghany KF et al (2000) Dynamic traffic assignment in design and evaluation of high‐occupancy toll lanes. Transp Res Rec 1733:39–48
Abdelghany KF, Mahmassani HS (2001) Dynamic trip assignment‐simulation model for intermodal transportation networks. Transp Res Rec 1771:52–60
Abdelghany KF, Valdes DM et al (1999) Real-time dynamic traffic assignment and path-based signal coordination: Application to network traffic management. Transp Res Rec 1667:67–76
Abdulhai B, Porwal H, Recker W (2002) Short-term Freeway Traffic Flow Prediction Using Genetically Optimized Time-Delay-Based Neural Networks. ITS J: Intell Transp Syst J 7(1):3–41
Ahmed M, Cook (1982) Analysis of Freeway Traffic Time Series Data by Using Box‐Jenkins Techniques. Transp Res Rec 722:1–9
Ahn K, Rakha H et al (2002) Estimating vehicle fuel consumption and emissions based on instantaneous speed and acceleration levels. J Transp Eng 128(2):182–190
Ahn K, Rakha H et al (2004) Microframework for modeling of high‐emitting vehicles. Transp Res Rec 1880:39–49
Akcelik R, Rouphail NM (1994) Overflow queues and delays with random and platooned arrivals at signalized intersections. J Adv Transp 28(3):227–251
Allen RW, Stein AC, Rosenthal TJ, Ziedman D, Torres JF, Halati A (1991)Human factors simulation investigation of driver route diversion and alternate route selection using in‐vehicle navigation systems.In: Vehicle Navigation & Information Systems Conference, Dearborn, 20–23 Oct1991. Proceedings Part 1 (of 2) Society of Automotive Engineers. SAE, Warrendale, pp 9–26
Anastassopoulos I (2000) Fault‐Tolerance and Incident Detection using Fourier Transforms. Purdue University, Westlafayette
Arafeh M, Rakha H (2005) Genetic Algorithm Approach for Locating Automatic Vehicle Identification Readers. In: IEEE Intelligent Transportation System Conference, Vienna, 2005. ProceedingsITSV`05 IEEE Intelligent Conference on Transportations Systems, p 1153–1158
Arnott R, de Palma A, Lindsey R (1991) Does providing information to drivers reduce traffic congestion? Transp Res Part A (General) 25A(5):309
Arrow KJ (1951) Alternative Approaches to the Theory of Choice in Risk‐Taking Situations. Econometrica 19(4):404–437
Ashok K (1996) Estimation and Prediction of Time‐Dependent Origin‐Destination Flows. Boston, Massachusetts Institute of Technology. Ph D Thesis, Massachusetts Instituteof Technology
Ashok K, Ben-Akiva ME (1993) Dynamic Origin‐Destination Matrix Estimation and Prediction for Real-Time Traffic Management Systems. In: Daganzo CF (ed) 12th International Symposium on Transportation and Traffic Theory. Elsevier, New York, pp 465–484
Ashok K, Ben-Akiva ME (2000) Alternative approaches for real-time estimation and prediction of time‐dependent Origin‐Destination flows. Transp Sci 34(1):21–36
Balakrishna R, Koutsopoulos HN et al (2005) Simulation‐Based Evaluation of Advanced Traveler Information Systems. Transp Res Rec 1910:90–98
Barth M, An F et al (2000) Comprehensive Modal Emission Model (CMEM): Version 2.0 User's Guide. University of California, Riverside
Bell M, Iida Y (1997) Transportation network analysis. Iida Y translator. Wiley, Chichester / New York
Ben-Akiva M, Bierlaire M et al (1998) DynaMIT: a simulation‐based system for traffic prediction. DACCORD Short Term Forecasting Workshop, Delft, February 1998
Ben-Akiva M, Bolduc D et al (1993) Estimation of travel choise models with randomly distributed values of time. Transp Res Rec 1413:88–97
Ben-Akiva M, Kroes E et al (1992) Real-Time Prediction of Traffic Congestion. Vehicle Navigation and Information Systems, IEEE, New York
Ben-Akiva M, Bierlaire M, Bottom J, Koutsopoulos H et al (1997) Development Of A Route Guidance Generation System For Real-Time Application. In: 8th International Federation of Automatic Control Symposium on Transportation Systems, Chania, 16–18 June 1997
Ben-Akiva MMB, Koutsopoulos H, Mishalani R (1998) DynaMIT: a simulation‐based system for traffic prediction. DACCORD Short Term Forecasting Workshop, Delft
Bierlaire M, Crittin F (2004) An efficient algorithm for real-time estimation and prediction of dynamic OD tables. Oper Res 52(1):116–27
Birge JR, Ho JK (1993) Optimal flows in stochastic dynamic networks with congestion. Oper Res 41(1):203–216
Bolland JD, Hall MD et al (1979) SATURN: Simulation and Assignment of Traffic in Urban Road Networks. In: International Conference on Traffic Control Systems, Berkeley
Boyce DE, Ran B, Leblanc LJ (1995) Solving an instantaneous dynamic user‐optimal route choice model. Transp Sci 29(2):128–142
Braess D (1968) Über ein Paradoxon der Verkehrsplanung. Unternehmensforschung 12:258–268
Brilon W (1995) Delays at oversaturated unsignalized intersections based on reserve capacities. Transp Res Rec 1484:1–8
Brilon W, Wu N (1990) Delays at fixed-time traffic signals under time‐dependent traffic conditions. Traffic Eng & Control 31(12):8
Burell JE (1968) Multipath Route Assignment and its Application to Capacity‐Restraint. Fourth International Symposium on the Theory of Traffic Flow, Karlsruhe
Burell JE (1976) Multipath Route Assignment: A Comparison of Two Methods. In: Florian M (ed) Traffic Equilibrium Methods. Lectue Notes in Economics and Mathematical Systems, vol 118. Springer, New York, pp 210–239
Busemeyer JR, Townsend JT (1993) Decision Field Theory: A Dynamic‐Cognitive Approach to Decision Making in an Uncertain Environment. Psychol Rev 100(3):432
Byung-Wook Wie TRL, Friesz TL, Bernstein D (1995) A discrete time, nested cost operator approach to the dynamic network user equilibrium problem. Transp sci 29(1):79–92
Cantarella GE, Cascetta ES (1995) Dynamic processes and equilibrium in transportation networks: towards a unifying theory. Transp Sci 29(4):305–329
Carey M (1986) Constraint qualification for a dynamic traffic assignment model. Transp Sci 20(1):55–58
Carey M (1987) Optimal time‐varying flows on congested networks. Oper Res 35(1):58–69
Carey M (1992) Nonconvexity of the dynamic traffic assignment problem. Transp Res Methodol 26B(2):127
Carey M, Subrahmanian E (2000) An approach to modelling time‐varying flows on congested networks. Transp Res Methodol 34B(3)
Cascetta E, Marquis G (1993) Dynamic estimators of origin‐destination matrices using traffic counts. Transp Sci 27(4):363–373
Cassidy MJ, Han LD (1993) Proposed model for predicting motorist delays at two-lane highway work zones. J Transp Eng 119(1):27–42
Cassidy MJ, Rudjanakanoknad J (2005) Increasing the capacity of an isolated merge by metering its on-ramp. Transp Res Part B Methodol 39(10):896–913
Cassidy MJ, Son Y et al (1994) Estimating motorist delay at two-lane highway work zones. Transp Res Part A, Policy Pract 28(5):433–444
Cassidy MJ, Windover JR (1995) Methodology for assessing dynamics of freeway traffic flow. Transp Res Rec 1484:73–79
Castillo E, Menendez JM, Jimenez P (2008) Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations. Transp Res Part B: Methodol 42(5):455–481
Catling I (1977) A Time‐Dependent Approach to Junction Delays. Traffic Eng Control 18(11):520–523:526
Chang GL, Mahmassani HS (1988) Travel Time Prediction And Departure Time Adjustment Behavior Dynamics In A Congested Traffic System. Transp Res, Part B: Methodol 22B(3):217–232
Chang GL, Tao X (1999) Integrated model for estimating time‐varying network origin‐destination distributions. Transp Res, Part A: Policy Pract 33(5):381–399
Chen SQ (2000) Comparing Probabilistic and Fuzzy Set Approaches for Design in the Presence of Uncertainty. In: Aerospace and Ocean Engineering. Ph D, Polytechnic Institute and State University, Blacksburg
Chiu YC, Mahmassani HS (2001) Toward hybrid dynamic traffic assignment‐models and solution procedures. In: IEEE Intelligent Transportation Systems Proceedings, IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC 2001, Oakland
Coifman B (1998) New algorithm for vehicle reidentification and travel time measurement on freeways. In: Proceedings of the 1998 5th International Conference on Applications of Advanced Technologies in Transportation, Newport Beach, Proceedings of the International Conference on Applications of Advanced Technologies in Transportation Engineering, ASCE, Reston
Coifman B, Banerjee B (2002) Vehicle reidentification and travel time measurement on freeways using single loop detectors‐from free flow through the onset of congestion. In: Proceedings of the seventh International Conference on: Applications of Advanced Technology in Transportation, Cambridge,5‐7 Aug 2002. Proceedings of the International Conference on Applications of Advanced Technologies in Transportation Engineering. American Civil Engineers
Coifman B, Cassidy M (2001) Vehicle reidentification and travel time measurement, Part I: Congested freeways. In: IEEE Intelligent Transportation Systems Proceedings, Conference IEEE on Intelligent Transportation Systems, Proceedings, ITSC 2001, Oakland
Coifman B, Ergueta E (2003) Improved vehicle reidentification and travel time measurement on congested freeways. J Transp Eng 129(5):475–483
Colyar JD, Rouphail NM (2003) Measured Distributions of Control Delay on Signalized Arterials. Transp Res Rec 1852:1–9
Cremer M, Keller H (1987) New Class Of Dynamic Methods For The Identification Of Origin‐Destination Flows. Transp Res, Part B: Methodol 21(2):117–132
Cronje WB (1983) Analysis of Existing Formulas for Delay, Overflow, and Stops. Transp Res Rec 905:89–93
Cronje WB (1983) Derivation of Equations for Queue Length, Stops, and Delay for Fixed-Time Traffic Signals. Transp Res Rec 905:93–95
Cronje WB (1983) Optimization Model for Isolated Signalized Traffic Intersections. Transp Res Rec 905:80–83
Cronje WB (1986) Comparative Analysis of Models for Estimating Delay for Oversaturated Conditions at Fixed-Time Traffic Signals. Transp Res Record 1091:48–59
Dafermos S (1980) Traffic equilibrium and variational inequalities. Transp Sci 14(1):42–54
Daganzo CF, Laval JA (2005) On the numerical treatment of moving bottlenecks. Transp Res Part B Methodol 39(1):31–46
Daniel J, Fambro DB et al (1996) Accounting for nonrandom arrivals in estimate of delay at signalized intersections. Transp Res Rec 1555:9–16
Dantzig GB (1957) The Shortest Route Problem. Oper Res 5:270–273
Dial R (1971) A Probabilistic Multipath Traffic Assignment Model which Obviates Path Enumeration. Transp Res 5:83–111
Dijkstra EW (1959) A Note on Two Problems in Connection with Graphics. Numeriche Math 1:209–271
Dion F, Rakha H (2006) Estimating dynamic roadway travel times using automatic vehicle identification data for low sampling rates. Transp Res Part B 40:745–766
Dion F, Rakha H et al (2004) Comparison of delay estimates at under‐saturated and over‐saturated pre-timed signalized intersections. Transp Res Part B Methodol 38(2):99–122
Dion F, Rakha H et al (2004) Evaluation of potential transit signal priority benefits along a fixed-time signalized arterial. J Transp Eng 130(3):294–303
Elefteriadou L, Fang C et al (2005) Methodology for evaluating the operational performance of interchange ramp terminals. Transp Res Rec 1920:13–24
Engelbrecht RJ, Fambro DB et al (1996) Validation of generalized delay model for oversaturated conditions. Transp Res Rec 1572:122–130
Evans JL, Elefteriadou L et al (2001) Probability of breakdown at freeway merges using Markov chains. Transp Res Part B Methodol 35(3):237–254
Fambro DB, Rouphail NM (1996) Generalized delay model for signalized intersections and arterial streets. Transp Res Rec 1572:112–121
Fang FC, Elefteriadou L et al (2003) Using fuzzy clustering of user perception to define levels of service at signalized intersections. J Transp Eng 129(6):657–663
Fisk C (1979) More Paradoxes in the Equilibrium Assignment Problem. Transp Res 13B:305–309
Flannery A, Kharoufeh JP et al (2005) Queuing delay models for single‐lane roundabouts. Civ Eng & Environ Syst 22(3):133–150
Frank M (1981) The Braess Paradox. Math Program 20:283–302
Frank M, Wolfe P (1956) An Algorithm of Quatdratic Programming. Nav Res Logist 3:95–110
Friesz TL, DB, Smith TE, Tobin RL, Wie BW (1993) A Variational Inequality Formulation of the Dynamic Network User Equilibrium Problem. Oper Res 41(1):179–191
Friesz TL, JL, Tobin RL, Wie B-W (1989) Dynamic network traffic assignment considered as a continuous time optimal control problem. Oper Res 37(6):893–901
Ghali MO, Smith MJ (1995) A model for the Dynamic System Optimum Traffic Assignment Problem. Transp Res 29B(3):155–170
Greenshields BD (1934) A study of traffic capacity. In: Proc Highway Research Board 14:448–477
Hagring O, Rouphail NM et al (2003) Comparison of Capacity Models for Two-Lane Roundabouts. Transp Res Rec 1852:114–123
Hall MD, Van Vliet D et al (1980) SATURN - A Simulation‐Assignment Model fo the Evalaution of Traffic Management Schemes. Traffic Eng Control 4:167–176
Hawas YE (1995) A Decentralized Architecture And Local Search Procedures For Real-Time Route Guidance In Congested Vehicular Traffic Networks. University of Texas, Austin
Hawas YE (2004) Development and calibration of route choice utility models: Neuro-fuzzy approach. J transp eng 130(2):171–182
Hawas YE, Mahmassani HS (1995) A Decentralized Scheme For Real-Time Route Guidance In Vehicular Traffic Networks. In: Second World Congress on Intelligent Transport Systems, Yokohama, 1995, p 1965–1963
Hawas YE, Mahmassani HS (1997) Comparative analysis of robustness of centralized and distributed network route control systems in incident situations. Transp Res Rec 1537:83–90
Hawas YE, Mahmassani HS, Chang GL, Taylor R, Peeta S, Ziliaskopoulos A (1997) Development of Dynasmart-X Software for Real-Time Dynamic Traffic Assignment. Center for Transportation Research, The University of Texas, Austin
Hellinga BR, Van Aerde M (1998) Estimating dynamic O-D demands for a freeway corridor using loop detector data. Canadian Society for Civil Engineering, Halifax, Montreal
Ho JK (1980) A successive linear optimization approach to the dynamic traffic assignment problem. Transp Sci 14(4):295–305
Hu SR, Madanat SM, Krogmeier JV, Peeta S (2001) Estimation of dynamic. assignment matrices and OD demands using adaptive Kalman Filtering. Intell Transp Syst J 6:281–300
Huey-Kuo C, Che-Fu H (1998) A model and an algorithm for the dynamic user‐optimal route choice problem. Transp Res, Part B Methodol 32B(3):219–234
Ishak S, Al-Deek H (2003) Performance Evaluation of a Short-Term Freeway Traffic Prediction Model. Transportation Research Board 82nd Annual Meeting, Washington DC
Janson BN (1991) Convergent Algorithm for Dynamic Traffic Assignment. Transp Res Rec 1328:69–80
Janson BN (1991) Dynamic Traffic Assignment For Urban Road Networks. Transp Res, Part B Methodol 25B:2–3
Jayakrishnan R, Mahmassani HS (1990) Dynamic simulation‐assignment methodology to evaluate in‐vehicle information strategies in urban traffic networks. Winter Simulation Conference Proceedings, New Orleans 1990. 90 Winter Simulation Conf Winter Simulation Conference Proceedings. IEEE, Piscataway (IEEE cat n 90CH2926–4)
Jayakrishnan R, Mahmassani HS (1991) Dynamic modelling framework of real-time guidance systems in general urban traffic networks. In: Proceedings of the 2nd International Conference on Applications of Advanced Technologies in Transportation Engineering, Minneapolis. ASCE, New York
Jayakrishnan R, Mahmassani HS et al (1993) User‐friendly simulation model for traffic networks with ATIS/ATMS. Proceedings of the 5th International Conference on Computing in Civil and Building Engineering - V ICCCBE, Anaheim 1993. ASCE, New York
Jeffery DJ (1981) The Potential Benefits of Route Guidance. TRRL, Department of Transportation, Crowthorne
Jha M, Madanat S, Peeta S (1998) Perception updating and day-to-day travel choice dynamics in traffic networks with information provision. Transp Res Part C Emerg Technol 6C(3):189–212
Katsikopoulos KV, Duse-Anthony Y et al (2000) The Framing of Drivers' Route Choices when Travel Time Information Is Provided under Varying Degrees of Cognitive Load. J Hum Factors Ergonomics Soc 42(3):470–481
Kerner BS (2004) The physics of traffic. Springer, Berlin
Kerner BS (2004) Three-phase traffic theory and highway capacity. Physica A 333(1-4):379–440
Kerner BS (2005) Control of spatiotemporal congested traffic patterns at highway bottlenecks. Physica A 355(2-4):565–601
Kerner BS, Klenov SL (2006) Probabilistic breakdown phenomenon at on-ramp bottlenecks in three-phase traffic theory: Congestion nucleation in spatially non‐homogeneous traffic. Physica A 364:473–492
Kerner BS, Rehborn H et al (2004) Recognition and tracking of spatial‐temporal congested traffic patterns on freeways. Transp Res Part C Emerging Technologies 12(5):369–400
Khattak AJ, Schofer JL, Koppelman FS (1993) Commuters' enroute diversion and return decisions: analysis and implications for advanced traveller information systems. Transp Res (Policy and Practice) 27A(2):101
Kim H, Baek S et al (2001) Origin‐destination matrices estimated with a genetic algorithm from link traffic counts. Transp Res Rec 1771:156–163
Koutsopoulos HN, Polydoropoulou A et al (1995) Travel simulators for data collection on driver behavior in the presence of information. Transp Res Part C Emerging Technologies 3(3):143
Krishnamurthy S, Coifman B (2004) Measuring freeway travel times using existing detector infrastructure. In: Proceedings - 7th International IEEE Conference on Intelligent Transportation Systems, ITSC, Washington, 2004
Laval JA, Daganzo CF (2006) Lane‐changing in traffic streams. Transp Res Part B Methodol 40(3):251–264
Lawson TW, Lovell DJ et al (1996) Using input‐output diagram to determine spatial and temporal extents of a queue upstream of a bottleneck. Transp Res Rec 1572:140–147
LeBlanc LJ (1975) An Algorithm for Discrete Network Design Problem. Tranp Sci 9:183–199
LeBlanc LJ, Abdulaal M (1970) A Comparison of User‐Optimum versus System‐Optimum Traffic Assignment in Transportation Network Design. Transp Res 18B:115–121
LeBlanc LJ, Morlok EK et al (1974) An Accurate and Efficient Approach to Equilibrium Traffic Assignment on Congested Networks. Transp Res Rec 491:12–23
Lee S, Fambro D (1999) Application of the Subset ARIMA Model for Short-Term Freeway Traffic vol Forecasting. Transp Res Rec 1678:179–188
Leonard DR, Tough JB et al (1978) CONTRAM - A Traffic Assignment Model for Predicting Flows and Queues During Peak Periods. TRRL SR 568. Transport Research Laboratory, Crowthome
Lertworawanich P, Elefteriadou L (2001) Capacity estimations for type B weaving areas based on gap acceptance. Transp Res Rec 1776:24–34
Lertworawanich P, Elefteriadou L (2003) A methodology for estimating capacity at ramp weaves based on gap acceptance and linear optimization. Transp Res Part B Methodol 37(5):459–483
Li J, Rouphail NM et al (1994) Overflow delay estimation for a simple intersection with fully actuated signal control. Transp Res Rec 1457:73–81
Li Y (2001) Development of Dynamic Traffic Assignment Models for Planning Applications. Northwestern University, Evanston
Lighthill MJ, Witham GB (1955) On Kinematic Waves. I: Flood Movement in Long Rivers, II. A Theory of Traffic Flow on Long Crowded Roads. In: Proceedings of the Royal Society of London A 229, pp 281–345
Lorenz MR, Elefteriadou L (2001) Defining freeway capacity as function of breakdown probability. Transp Res Rec 1776:43–51
Lotan T (1997) Effects of familiarity on route choice behavior in the presence of information. Transp Res Part C Emerg Technol 5(3-4):225–243
Mahmassani H, Jou R-C (2000) Transferring insights into commuter behavior dynamics from laboratory experiments to ®eld surveys. Transp Res Part A Policy Pract 34A(4):243–260
Mahmassani H, Peeta S (1992) System optimal dynamic assignment for electronic route guidance in a congested traffic network. In: Gartner NH, Improta G (eds) Urban TrafficNetworks. Dynamic Flow Modelling and Control. Springer, Berlin, pp 3–37
Mahmassani HS, Chiu Y-C, Chang GL, Peeta S, Ziliaskopoulos A (1998) Off-line Laboratory Test Results for the DYNASMART-X Real-Time Dynamic Traffic Assignment System. Center for Transportation Research, The University of Texas, Austin
Mahmassani HS, Hawas Y, Abdelghany K, Abdelfatah A, Chiu Y-C, Kang Y, Chang GL, Peeta S, Taylor R, Ziliaskopoulos A (1998) DYNASMART-X, vol II: Analytical and Algorithmic Aspects. Center for Transportation Research, The University of Texas, Austin
Mahmassani HS, Hawas Y, Hu T-Y, Ziliaskopoulos A, Chang G-L, Peeta S, Taylor R (1998) Development of Dynasmart-X Software for Real-Time Dynamic Traffic Assignment. Technical ReportST067-85-Tast E (revised) submitted to Oak Ridge National Laboratoryunder subcontract 85X-SU565C,
Mahmassani HS, Peeta S (1993) Network Performance under System Optimal and User Equilibrium Dynamic Assignments: Implications for ATIS. Transp Res Rec 1408:83–93
Mahmassani HS, Peeta S (1995) System Optimal Dynamic Assignment for Electronic Route Guidance in a Congested Traffic Network. In: Gartner NH, Improta G (eds) URBAN TRAFFIC NETWORKS: Dynamic Flow Modeling and Control. Springer, Berlin, pp 3–37
Mahmassani HS, Peeta S, Hu T, Ziliaskopoulos A (1993) Algorithm for Dynamic Route Guidance in Congested Networks with Multiple User Information Availability Groups. In: 26th International Symposium on Automotive Technology and Automation, Aachen
Matsoukis EC (1986) Road Traffic Assignment - A Review Part I: Non‐Equilibrium Methods. Transp Plan Technol 11:69–79
Matsoukis EC, Michalopolos PC (1986) Road Traffic Assignment - A Review Part II: Equilibrium Methods. Transp Plan Technol 11:117–135
Mekky A (1995) Toll revenue and traffic study of highway 407 in Toronto. Transp Res Rec 1498:5–15
Mekky A (1996) Modeling toll pricing strategies in greater Toronto areas. Transp Res Rec 1558:46–54
Mekky A (1998) Evaluation of two tolling strategies for Highway 407 in Toronto. Transp Res Rec 1649:17–25
Merchant DK, Nemhauser GL (1978) A Model And An Algorithm For The Dynamic Traffic Assignment Problems. Transp Sci 12(3):183–199
Merchant DK, Nemhauser GL (1978) Optimality Conditions For A Dynamic Traffic Assignment Model. Transp Sci 12(3):200–207
Minderhoud MM, Elefteriadou L (2003) Freeway Weaving: Comparison of Highway Capacity Manual 2000 and Dutch Guidelines. Transp Res Rec 1852:10–18
Moskowitz K (1956) California Method for Assigning Directed Traffic to Proposed Freeways. Bull Highw Res Board 130:1–26
Munnich LW Jr, Hubert HH et al (2007) L-394 MnPASS high-occupancy toll lanes planning and operational issues and outcomes (lessons learning in year 1). Transp Res Rec 1996:49–57
Murchland JD (1970) Braess's Paradox of Traffic Flow. Transp Res 4:391–394
Nagel K (1996) Particle Hopping Model and Traffic Flow Theory. Phys Rev E 53 (5):4655–4672
Nagel K, Schrekenberg M (1992) Cellular Automaton Model for Freeway Traffic. J Phys 2(20):2212–2229
Nagel K, Schrekenberg M (1995) Traffic Jam Dynamics in Stochastic Cellular Automata. US D Energy, Los Alamos National Laboratory, LA-UR-95-2132, Los Alamos
Nakayama S, Kitamura R (2000) Route choice model with inductive learning. Transp Res Rec 1725:63–70
Nakayama S, Kitamura R et al (2001) Drivers' route choice rules and network behavior: Do drivers become rational and homogeneous through learning? Transp Res Rec 1752:62–68
Newell GF (1965) Approximation Methods for Queues with Application to the Fixed-Cycle Traffic Light. SIAM Rev 7:223–240
Newell GF (1999) Delays caused by a queue at a freeway exit ramp. Transp Res Part B Methodol 33(5):337–350
Nguyen S (1969) An Algorithm for the Assignment Problem. Transp Sci 8:203–216
Nie Y, Zhang HM et al (2005) Inferring origin‐destination trip matrices with a decoupled GLS path flow estimator. Transp Res Part B Methodol 39(6):497–518
Noonan J, Shearer O (1998) Intelligent Transportation Systems Field Operational Test: Cross‐Cutting Study Advance Traveler Information Systems. US Department of Transportation, Federal Highways Administration, Intelligent Transportation System,Washington, DC
Okutani I (1987) The Kalman Filtering Approaches in Some Transportation and Traffic Problems. In: Proceedings of the Tenth International Symposium on Transportation and Traffic Theory. Elsevier, New York
Park B (2002) Hybrid neuro-fuzzy application in short-term freeway traffic vol forecasting. Transp Res Rec 1802:190–196
Park D, Rilett LR (1998) Forecasting multiple‐period freeway link travel times using modular neural networks. Transp Res Rec 1617:163–170
Park D, Rilett LR (1999) Forecasting freeway link travel times with a multilayer feedforward neural network. Comput‐Aided Civ & Infrastruct Eng 14(5):357–367
Park D, Rilett LR et al (1998) Forecasting multiple‐period freeway link travel times using neural networks with expanded input nodes. In: Proceedings of the 1998 5th International Conference on Applications of Advanced Technologies in Transportation, Newport Beach and Proceedings of the International Conference on Applications of Advanced Technologies in Transportation Engineering 1998, ASCE, Reston
Park D, Rilett LR et al (1999) Spectral basis neural networks for real-time travel time forecasting. J Transp Eng 125(6):515–523
Park S, Rakha H (2006) Energy and Environmental Impacts of Roadway Grades. Transp Res Rec 1987:148–160
Pavlis Y, Papageorgiou M (1999) Simple decentralized feedback strategies for route guidance in traffic networks. Transp Sci 33(3):264–278
Peeta S (1994) System Optimal Dynamic Traffic Assignment in Congested Networks with Advanced Information Systems. University of Texas, Austin
Peeta S, Bulusu S (1999) Generalized singular value decomposition approach for consistent on-line dynamic traffic assignment. Transp Res Rec 1667
Peeta S, Mahmassani HS (1995) Multiple user classes real-time traffic assignment for online operations: a rolling horizon solution framework. Transp Res Part C Emerg Technol 3C(2):83
Peeta S, Mahmassani HS (1995) System optimal and user equilibrium time‐dependent traffic assignment in congested networks. Ann Oper Res 60:81–113
Peeta S, Mahmassani HS et al (1991) Effectiveness of real-time information strategies in situations of non‐recurrent congestion. In: Proceedings of the 2nd International Conference on Applications of Advanced Technologies in Transportation Engineering, Minneapolis. ASCE, New York
Peeta S, Paz A (2006) Behavior‐consistent within‐day traffic routing under information provision. In: IEEE Intelligent Transportation Systems Conference, Toronto,pp 212–217
Peeta S, Ramos JL (2006) Driver response to variable message signs-based traffic information. Intell Transp Syst 153(1):2–10
Peeta S, Ramos JL, Pasupathy R (2000) Content of Variable Message Signs and On-line Driver Behavior. Transp Res Rec 1725:102–108
Peeta S, Yang T-H (2000) Stability of Large-scale Dynamic Traffic Networks under On-line Control Strategies. In: 6th International Conference on Applications of Advanced Technologies in Transportation Engineering, Singapore,paperno. 11 (eProceedings on CD), p 9
Peeta S, Yang T-H (2003) Stability Issues for Dynamic Traffic Assignment. Automatica 39(1):21–34
Peeta S, Yu JW (2004) Adaptability of a Hybrid Route Choice Model to Incorporating Driver Behavior Dynamics Under Information Provision. In: IEEE Transactions On Systems, Man, And Cybernetics Part A: Systems And Humans 34(2):243–256
Peeta S, Yu JW (2006) Behavior‐based consistency‐seeking models as deployment alternatives to dynamic traffic assignment models. Transp Res Part C Emerg Technol 14(2):114–138
Peeta S, Zhou C (1999) On-Line Dynamic Update Heuristics for Robust Guidance. In: International Conference Modeling and Management in Transportation, Cracow, October 1999
Peeta S, Zhou C (1999) Robustness of the Off-line A Priori Stochastic Dynamic Traffic Assignment Solution for On-Line Operations. Transp Res Part C: Emerg Technol 7C(5):281–303
Peeta S, Ziliaskopoulos AK (2001) Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future. Netw Spat Econ 1(3-4):233
Rakha H (1990) An Evaluation of the Benefits of User and System Optimised Route Guidance Strategies. In: Civil Engineering. Queen's University, Kingston
Rakha H, Ahn K (2004) Integration modeling framework for estimating mobile source emissions. J transp eng 130(2):183–193
Rakha H, Ahn K et al (2004) Development of VT-Micro model for estimating hot stabilized light duty vehicle and truck emissions. Transp Res Part D Transport and Environment 9(1):49–74
Rakha H, Arafeh M (2007) Tool for calibrating steady‐state traffic stream and car‐following models. In: Transportation Research Board Annual Meeting, Washington,22–25 Jan 2008
Rakha H, Crowther B (2002) Comparison of Greenshields, Pipes, and Van Aerde car‐following and traffic stream models. Transp Res Rec 1802:248–262
Rakha H, Flintsch AM et al (2005) Evaluating alternative truck management strategies along interstate 81. Transp Res Rec 1925:76–86
Rakha H, Kang Y-S et al (2001) Estimating vehicle stops at undersaturated and oversaturated fixed-time signalized intersections. Transp Res Rec 1776:128–137
Rakha H, Lucic I (2002) Variable power vehicle dynamics model for estimating maximum truck acceleration levels. J Transp Eng 128(5):412–419
Rakha H, Lucic I et al (2001) Vehicle dynamics model for predicting maximum truck acceleration levels. J Transp Eng 127(5):418–425
Rakha H, Medina A et al (2000) Traffic signal coordination across jurisdictional boundaries: Field evaluation of efficiency, energy, environmental, and safety impacts. Transp Res Rec 1727:42–51
Rakha H, Paramahamsan H et al (2005) Comparison of Static Maximum Likelihood Origin‐Destination Formulations. Transportation and Traffic Theory: Flow, Dynamics and Human Interaction. In: Proceedings of the 16th International Symposium on Transportation and Traffic Theory (ISTTT16), pp 693–716
Rakha H, Pasumarthy P et al (2004) Modeling longitudinal vehicle motion: issues and proposed solutions. In: Transport Science and Technology Congress, Athens, Sep 2004
Rakha H, Pasumarthy P et al (2004) The INTEGRATION framework for modeling longitudinal vehicle motion. TRANSTEC, Athens
Rakha H, Snare M et al (2004) Vehicle dynamics model for estimating maximum light-duty vehicle acceleration levels. Transp Res Rec 1883:40–49
Rakha H, Van Aerde M et al (1989) Evaluating the benefits and interactions of route guidance and traffic control strategies using simulation. In: First Vehicle Navigation and Information Systems Conference - VNIS '89, Toronto. IEEE, Piscataway
Rakha H, Van Aerde M et al (1998) Construction and calibration of a large-scale microsimulation model of the Salt Lake area. Transp Res Rec 1644:93–102
Rakha H, Zhang Y (2004) INTEGRATION 2.30 framework for modeling lane‐changing behavior in weaving sections. Transp Res Rec 1883:140–149
Rakha H, Zhang Y (2004) Sensitivity analysis of transit signal priority impacts on operation of a signalized intersection. J Transp Eng 130(6):796–804
Rakha HA, Van Aerde MW (1996) Comparison of simulation modules of TRANSYT and integration models. Transp Res Rec 1566:1–7
Ran B, Boyce DE (1996) A link-based variational inequality formulation of ideal dynamic user‐optimal route choice problem. Research Part C Emerg Technol 4C(1):1–12
Ran B, Boyce DE (1996) A link-based variational inequality formulation of ideal dynamic user‐optimal route choice problem. Research Part C (Emerging Technologies) 4C(1):1–11
Ran B, Boyce DE, LeBlanc LJ (1993) A new class of instantaneous dynamic user‐optimal traffic assignment models. Oper Res 41(1):192–202
Ran B, Hall RW, Boyce DE (1996) A link-based variational inequality model for dynamic departure time/route choice. Transp Res Methodol 30B(1):31–46
Ran B, Shimazaki T (1989) A general model and algorithm for the dynamic traffic assignment problems. In: Fifth World Conference on Transport Research, Transport Policy, Management and Technology Towards, Yokohama, 2001
Ran B, Shimazaki T (1989) Dynamic user equilibrium traffic assignment for congested transportation networks. In: Fifth World Conference on Transport Research, Yokohama, 1989
Randle J (1979) A Convergence Probabilistic Road Assignment Model. Traffic Eng Control 11:519–521
Richards PI (1956) Shock waves on the highway. Oper Res 4:42–51
Rilett L, Aerde V (1993) Modeling Route Guidance Using the Integration Model. In: Proceedings of the Pacific Rim Trans Tech Conference, Seattle, 1993 and Proceedings of the ASCE International Conference on Applications of Advanced Technologies in Transportation Engineering. ASCE, New York
Rilett L, Van Aerde M (1991) Routing based on anticipated travel times. In: Proceedings of the 2nd International Conference on Applications of Advanced Technologies in Transportation Engineering, Minneapolis. ASCE, New York
Rilett LR, Van Aerde M et al (1991) Simulating the TravTek route guidance logic using the integration traffic model. In: Vehicle Navigation & Information Systems Conference Proceedings Part 2 (of 2). Dearborn, 1991. In: Proceedings - Society of Automotive Engineers n P-253, SAE. Warrendale
Rilett LR, van Aerde MW (1991) Modelling distributed real-time route guidance strategies in a traffic network that exhibits the Braess paradox. In: Vehicle Navigation & Information Systems Conference Proceedings Part 2 (of 2). Dearborn, 1991. Proceedings - Society of Automotive Engineers n P-253. SAE, Warrendale
Rouphail NM (1988) Delay Models for Mixed Platoon and Secondary Flows. J Transp Eng 114(2):131–152
Rouphail NM, Akcelik R (1992) Preliminary model of queue interaction at signalised paired intersections. In: Proceedings of the 16th ARRB Conference, Perth, 9–12 November 1992. Congestion Management Proceedings - Conference of the Australian Road Research Board, Australian Road Research Board, Nunawading
Schofer AJKFSKJL (1993) Stated preferences for investigating commuters' diversion propensity. Transportation 20(2):107–127
Sheffi Y (1985) Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods, Prentice Hall,Englewood Cliffs
Sheffi Y, Powell W (1981) A Comparison of Stochastic and Deterministic Traffic Assignment over Congested Networks. Transp Res 15B:65–88
Shen W, Nie Y et al (2006) Path-based System Optimal Dynamic Traffic Assignment Models: Formulations and Solution Methods. In: IEEE Intelligent Transportation Systems Conference. IEEE, Toronto, pp 1298–1303
Sherali HD, Arora N, Hobeika AG (1997) Parameter optimization methods for estimating dynamic origin‐destination trip‐tables. Transp Res Part B Methodol 31B(2):141–157
Sherali HD, Desai J et al (2006) A discrete optimization approach for locating Automatic Vehicle Identification readers for the provision of roadway travel times. Transp Res Part B 40:857–871
Simon H (1957) Models of Man, Social and Rational. Adm Sci Q 2(2)
Simon HA (1947) Administrative Behavior. Am Political Sci Rev 41(6)
Simon HA (1955) A Behavioral Model of Rational Choice. Q J Econ 69(1):99–118
Sivanandan R, Dion F et al (2003) Effect of Variable‐Message Signs in Reducing Railroad Crossing Impacts. Transp Res Rec 1844:85–93
Smock R (1962) An Iterative Assignment Approach to Capacity‐Restraint on Arterial Networks. Bulleton Highw Res Board 347:226–257
Srinivasan KK, Mahmassani HS (2000) Modeling inertia and compliance mechanisms in route choice behavior under real-time information. Transp Res Rec 1725:45–53
Srinivasan KK, Mahmassani HS (2000) Modeling inertia and compliance mechanisms in route choice behavior under real-time information. Transp Res Rec 1725:45–53
Steinberg R, Zangwill WI (1983) The Prevalence of Braess' Paradox. Transp Sci 17:301–318
Stewart N (1980) Equilibrium versus System‐Optimal Flow: Some Examples. Transp Res 14A:81–84
Talaat H, Abdulhai B (2006) Modeling Driver Psychological Deliberation During Dynamic Route Selection Processes. In: 2006 IEEE Intelligent Transportation Systems Conference, Toronto, pp 695–700
Tarko A, Rouphail N et al (1993) Overflow delay at a signalized intersection approach influenced by an upstream signal. An analytical investigation. Transp Res Rec 1398:82–89
Van Aerde M (1985) Modelling of Traffic Flows, Assignment and Queueing in Integrated Freeway/Traffic Signal Networks. In: Civil Engineering. Ph D, University of Waterloo, Waterloo
Van Aerde M, Rakha H (1989) Development and Potential of System Optimized Route Guidance Strategies. In: IEEE Vehicle Navigation and Information Systems Conference. IEEE, Toronto, pp 304–309
Van Aerde M, Rakha H (2007) INTEGRATION © Release 2.30 for Windows: User's Guide - vol I: Fundamental Model Features. M Van Aerde & Assoc, Ltd, Blacksburg
Van Aerde M, Rakha H (2007) INTEGRATION © Release 2.30 for Windows: User's Guide - vol II: Advanced Model Features. M Van Aerde & Assoc, Ltd, Blacksburg
Van Aerde M, Rakha H et al (2003) Estimation of Origin‐Destination Matrices: Relationship between Practical and Theoretical Considerations. Transp Res Rec 1831:122–130
Van Aerde M, Yagar S (1988) Dynamic Integrated Freeway/Traffic Signal Networks: A Routeing‐Based Modelling Approach. Transp Res 22A(6):445–453
Van Aerde M, Yagar S (1988) Dynamic Integrated Freeway/Traffic Signal Networks: Problems and Proposed Solutions. Transp Res 22A(6):435–443
Van Aerde, M, Hellinga BR et al (1993) QUEENSOD: A Method for Estimating Time Varying Origin‐Destination Demands For Freeway Corridors/Networks. In: 72nd Annual Meeting of the Transportation Research Board, Washington DC, 1993
Van Der Zijpp NJ, De Romph E (1997) A dynamic traffic forecasting application on the Amsterdam beltway. Int J Forecast 13:87–103
Van Vliet D (1976) Road Assignment. Transp Res 10:137–157
Van Vliet D (1982) SATURN - A Modern Assignment Model. Traffic Eng Control 12:578–581
Van Zuylen JH, Willumsen LG (1980) The most likely trip matrix estimated from traffic counts. Transp Res 14B:281–293
Walker N, Fain WB et al (1997) Aging and Decision Making: Driving‐Related Problem Solving. J Hum Factors Ergon Soc 39(3):438–444(7)
Waller ST (2000) Optimization and Control of Stochastic Dynamic Transportation Systems: Formulations, Solution Methodologies, and Computational Experience. Ph D, Northwestern University, Evanston
Waller ST, Ziliaskopoulos AK (2006) A chance‐constrained based stochastic dynamic traffic assignment model: Analysis, formulation and solution algorithms. Transp Res Part C Emerg Technol 14(6):418–427
Wardrop J (1952) Some Theoretical Aspects of Road Traffic Research. Institute of Civil Engineers, pp 325–362
Webster F (1958) Traffic Signal Settings. HMsSO Road Research Laboratory, London
Webster FV, Cobbe BM (1966) Traffic Signals. HMsSO Road Research Laboratory, London
Wie BW (1991) Dynamic Analysis Of User‐Optimized Network Flows With Elastic Travel Demand. Transp Res Rec 1328:81–87
Willumsen LG (1978) Estimation of an O-D matrix from traffic counts: A review. Institute for Transport Studies, Working paper no 99, Leeds University, Leeds
Wilson AG (1970) Entropy in Urban and Regional Modelling. Pion, London
Wu J, Chang G-L (1996) Estimation of time‐varying origin‐destination distributions with dynamic screenline flows. Transp Res Part B Methodol 30B(4):277–290
Yagar S (1971) Dynamic Traffic Assignment by Individual Path Minimization and Queueing. Transp Res 5:179–196
Yagar S (1974) Dynamic Traffic Assignment by Individual Path Minimization and Queueing. Transp Res 5:179–196
Yagar S (1975) CORQ - A Model for Predicting Flows and Queues in a Road Corridor. Transp Res 553:77–87
Yagar S (1976) Measures of the Sensitivity and Effectiveness of the CORQ Traffic Model. Transp Res Rec 562:38–48
Yang Q, Ben-Akiva ME (2000) Simulation laboratory for evaluating dynamic traffic management systems. Transp Res Rec 1710:122–130
Yang T-H (2001) Deployable Stable Traffic Assignment Models for Control in Dynamic Traffic Networks: A Dynamical Systems Approach. Ph D, Purdue University, West Lafayette
Zhou X, Mahmassani HS (2006) Dynamic origin‐destination demand estimation using automatic vehicle identification data. In: IEEE Transactions on Intell Transp Syst 7(1):105–114
Zhou Y, Sachse T (1997) A few practical problems on the application of OD‐estimation in motorway networks. TOP 5(1):61–80
Ziliaskopoulos A, Wardell W (2000) Intermodal optimum path algorithm for multimodal networks with dynamic arc travel times and switching delays. Eur J Oper Res 125(3):486–502
Ziliaskopoulos AK (2000) A linear programming model for the single destination system optimum dynamic traffic assignment problem. Transp Sci 34(1):37–49
Ziliaskopoulos AK, Waller ST (2000) An Internet‐based geographic information system that integrates data, models and users for transportation applications. Transp Res Part C EmergTechnol 8C:1–6
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag
About this entry
Cite this entry
Rakha, H., Tawfik, A. (2009). Traffic Networks: Dynamic Traffic Routing, Assignment, and Assessment. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_562
Download citation
DOI: https://doi.org/10.1007/978-0-387-30440-3_562
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-75888-6
Online ISBN: 978-0-387-30440-3
eBook Packages: Physics and AstronomyReference Module Physical and Materials ScienceReference Module Chemistry, Materials and Physics