Regional Dynamic Traffic Assignment Framework for Macroscopic Fundamental Diagram Multi-regions Models
Published Online:16 Sep 2019https://doi.org/10.1287/trsc.2019.0921
References
- (2019) Approximative network partitioning for MFDs from stationary sensor data. Transportation Res. Record 2673(6):94–103.Crossref, Google Scholar
- (2016) Data fusion algorithm for macroscopic fundamental diagram estimation. Transportation Res. Part C: Emerging Tech. 71:184–197.Google Scholar
- (2013) A bathtub model of downtown traffic congestion. J. Urban Econom. 76:110–121.Google Scholar
- (1993) An algorithm for the ranking of shortest paths. Eur. J. Oper. Res. 69:97–106.Google Scholar
- (2018) Introduction of multi-regional mfd-based models with route choices: the definition of regional paths. PLURIS 2018—8th Luso-Brazilian Congress Urban, Regional, Integrated and Sustainable Planning, Coimbra, Portugal.Google Scholar
- (2019) Estimation of regional trip length distributions for the calibration of the aggregated network traffic models. Transportation Res. Part B: Methodological 122:192–217.Google Scholar
- (2018) Effects of users bounded rationality on a traffic network performance: A simulation study. J. Advanced Transportation 2018: Article 9876598.Google Scholar
- (2018) Trip length estimation for the macroscopic traffic simulation: scaling microscopic into macroscopic networks. 97th Annual Meeting Transportation Research Board, Washington, DC.Google Scholar
- (2001) Stochastic user equilibrium formulation for the generalized nested logit model. Transportation Res. Record 1752(1):84–90.Google Scholar
- (2002) Adaptation of logit kernel to route choice situation. Transportation Res. Record 1805(1):78–85.Google Scholar
- (1999) Discrete choice methods and their applications to short term travel decisions. Hall RW, ed. Handbook of Transportation Science (Springer, Boston, MA), 5–33.Crossref, Google Scholar
- (1984) Modeling interurban route choice behaviour. Volmuller J, Hamerslag R, eds. Proc. 9th Internat. Symp. Transportation and Traffic Theory (VNU Science Press BV, Utrecht, Netherlands), 299–330.Google Scholar
- (2012) A dynamic traffic assignment model for highly congested urban networks. Transportation Res. Part C: Emerging Tech. 24:62–82.Google Scholar
- (2005) Route choice models with subpath components. Proc. 5th Swiss Transport Research Conf., Ascona, Switzerland.Google Scholar
- (2007) Some properties and implications of stochastically generated route choice sets. Proc. 6th Tristan Conf., Pukhet, Thailand.Google Scholar
- (1999) A practical technique to estimate multinomial probit models in transportation. Transportation Res. Part B 33(1):63–79.Google Scholar
- (2008) The factor of revised path size: an alternative derivation. Transportation Res. Record 2076(1):132–140.Google Scholar
- (2018) Aggregation and travel time calculation over large scale traffic networks: An empiric study on the Grenoble city. Transportation Res. Part C: Emerging Tech. 95:713–730.Google Scholar
- (2001) Transportation Systems Engineering: Theory and Methods (Springer, Boston).Crossref, Google Scholar
- (1996) A modified logit route choice model overcoming path overlapping problems: specification and some calibration results for interurban networks. Proc. 13th Internat. Symp. Transportation and Traffic Theory Lyon, France, 697–711.Google Scholar
- (2012) Examining the scaling effect and overlapping problem in logit-based stochastic user equilibrium models. Transportation Res. Part A 46(8):1343–1358.Google Scholar
- (2014) A generalized random regret minimization model. Transportation Res. Part B: Methodological 68:224–238.Google Scholar
- (1989) A paired combinatorial logit model for travel demand analysis. Proc. 5th World Conf. Transportation Research, Ventura, CA, 295–309.Google Scholar
- (2012) Non-unique flows in macroscopic first-order intersection models. Transportation Res. Part B: Methodological 46(3):343–359.Google Scholar
- (1982) Unconstrained extremal formulation of some transportation equilibrium problems. Transportation Sci. 16(3):332–360.Google Scholar
- (2007) Urban gridlock: Macroscopic modeling and mitigation approaches. Transportation Res. Part B: Methodological 41(1):49–62.Google Scholar
- (1977) On stochastic models of traffic assignment. Transportation Sci. 11(3):253–274.Google Scholar
- (1993) Multidimensional path search and assignment. Proc. 21st PTRC Summer Annual Meeting, Manchester, UK, 307–320.Google Scholar
- (2014) Braess paradox under the boundedly rational user equilibria. Transportation Res. Part B: Methodological 67:86–108.Google Scholar
- (2013) Boundedly rational user equilibria (brue): Mathematical formulation and solution sets. Transportation Res. Part B: Methodological 57:300–313.Google Scholar
- (2016) Boundedly rational route choice behavior: A review of models and methodologies. Transportation Res. Part B: Methodological 85:142–179.Google Scholar
- (1971) A probabilistic multipath traffic assignment model which obviates path enumeration. Transportation Res. 5(2):83–113.Google Scholar
- (2013) Metropolis-Hastings sampling of paths. Transportation Res. Part B: Methodological 48:53–66.Google Scholar
- (2015) Congestion in the bathtub. Econom. Transportation 4(4):241–255.Crossref, Google Scholar
- (2007) Capturing correlation with subnetworks in route choice models. Transportation Res. Part B: Methodological 41(3):363–378.Google Scholar
- (2009) Sampling of alternatives for route choice modelling. Transportation Res. Part B: Methodological 43(10):984–994.Google Scholar
- (2008) Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings. Transportation Res. Part B: Methodological 42(9):759–770.Google Scholar
- (2011) Hysteresis phenomena of a macroscopic fundamental diagram in freeway networks. Procedia – Soc. Behavioral Sci. 17:213–228.Google Scholar
- (1969) The mechanism of a road network. Traffic Eng. Control. 11(8):323–327.Google Scholar
- (1979) A two-fluid approach to town traffic. Science 204(4389):148–151.Google Scholar
- (2011) Multiple equilibria in a dynamic traffic network. Transportation Res. Part B: Methodological 45(6):867–879.Google Scholar
- (2016) The morning commute in urban areas: Insights from theory and simulation. Transportation Res. Board 95th Annual Meeting, Washington, DC.Google Scholar
- (2017) Minimal parameter formulations of the dynamic user equilibrium using macroscopic urban models: Freeway vs city streets revisited. Transportation Res. Part B: Methodological 117:676–686.Google Scholar
- (2007) Hybrid approaches to the solutions of the “Lighthill-Whitham-Richards” model. Transportation Res. Part B: Methodological 41(7):701–709.Google Scholar
- (2013) Estimating MFDs in simple networks with route choice. Transportation Res. Part B: Methodological 57:468–484Crossref, Google Scholar
- (2017) Dynamic macroscopic simulation of on-street parking search: A trip-based approach. Transportation Res. Part B: Methodological 101:268–282.Google Scholar
- (2016) A regret theory-based route choice model. Transportmetrica A: Transportation Sci. 13:250–272.Google Scholar
- (2017) Empirics of multi-modal traffic networks using the 3D macroscopic fundamental diagram. Transportation Res. Part C: Emerging Tech. 82:88–101.Google Scholar
- (2017) Revealing the day-to-day regularity of urban congestion patterns with 3D speed maps. Scientific Rep. 7(1):1–11.Google Scholar
- (2008) A bi-criterion dynamic user equilibrium traffic assignment model and solution algorithm for evaluating dynamic road pricing strategies. Transportation Res. Part C: Emerging Tech. 16(4):371–389.Google Scholar
- (1987) On boundedly rational user equilibrium in transportation systems. Transportation Sci. 21(2):89–99.Google Scholar
- (2013) Urban network gridlock: Theory, characteristics, and dynamics. Transportation Res. Part C: Emerging Tech. 36:480–497.Google Scholar
- (1984) Investigation of network-level traffic flow relationships: Some simulation results. Transportation Res. Record: J. Transportation Res. Board 971:121–130.Google Scholar
- (2019) Flow exchanges in multi-reservoir systems with spillbacks. Transportation Res. Part B: Methodological 122:327–349.Google Scholar
- (2017) Macroscopic urban dynamics: Analytical and numerical comparisons of existing models. Transportation Res. Part B: Methodological 101:245–267.Google Scholar
- (1978) Modelling the choice of residential location. Karlqvist A, Snickars F, Weibull J, eds. Spatial Interaction Theory and Planning Models (MIT Press, Cambridge, MA), 75–96.Google Scholar
- (1978a) A model and an algorithm for the dynamic traffic assignment problems. Transportation Sci. 12(3):183–199.Google Scholar
- (1978b) Optimality conditions for a dynamic traffic assignment model. Transportation Sci. 12(3):200–207.Google Scholar
- (2010) Solving the dynamic user optimal assignment problem considering queue spillback. Networks Spatial Econom. 10(1):49–71.Google Scholar
- (2000) A stochastic transit assignment model considering differences in passengers utility functions. Transportation Res. Part B: Methodological 34(5):377–402.Google Scholar
- (2002) A stochastic route choice model for car travellers in the Copenhagen region. Networks Spatial Econom. 2(4):327–346.Google Scholar
- (2001) Foundations of dynamic traffic assignment: The past, the present and the future. Networks Spatial Econom. 1(3–4):233–265.Google Scholar
- (1998) Investigation of stochastic network loading procedures. Transportation Res. Record 1645(1):94–102.Google Scholar
- (2000) Congestion, stochastic, and similarity effects in stochastic user equilibrium. Transportation Res. Record 1733(1):80–87.Google Scholar
- (2009) Route choice modelling: Past, present and future research directions. J. Choice Modelling 2(1):65–100.Google Scholar
- (2006) Applying branch and bound techniques to route choice set generation. Transportation Res. Record 1985(1):19–28.Google Scholar
- (2002) Network knowledge and route choice. Unpublished PhD thesis, Massachusetts Institute of Technology, Cambridge.Google Scholar
- (2016) Clustering of heterogeneous networks with directional flows based on “snake” similarities. Transportation Res. Part B: Methodological 91:250–269.Google Scholar
- (2017) Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks. Transportation Res. Part B: Methodological 105:193–211.Google Scholar
- (2007) Efficient implementation of method of successive averages in simulation-based dynamic traffic assignment models for large-scale network applications. Transportation Res. Record: J. Transportation Res. Board 2029(1):22–30.Google Scholar
- (2018) Calibration and validation of a simulation-based dynamic traffic assignment model for a large-scale congested network. Simulation Modelling Practice Theory 86:169–186.Google Scholar
- (1985) Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods (Prentice Hall, Englewood Cliffs, NJ).Google Scholar
- (1957) A Behavioral Model of Rational Choice (John Wiley & Sons, New York).Google Scholar
- (1966) Theories of Decision-Making in Economics and Behavioural Science (Palgrave Macmillan, London).Crossref, Google Scholar
- (2005) Path enumeration by finding the constrained k-shortest paths. Transportation Res. Part B: Methodological 39(6):545–563.Google Scholar
- (2010) New Developments in Transport Planning: Advances in Dynamic Traffic Assignment (Edward Elgar, Cheltenham UK).Google Scholar
- (1997) The cross-nested logit model: An application to mode choice in the Tel Aviv metropolitan area. Transportation Res. Record 1607(1):13–20.Google Scholar
- (1952) Some theoretical aspects of road traffic research. Proc. Institute Civil Engrg. 1(5):325–378.Google Scholar
- (2002) The existence, uniqueness and computation of an arc-based dynamic network user equilibrium formulation. Transportation Res. Part B: Methodological 36(10):897–918.Google Scholar
- (2014) Approximating dynamic equilibrium conditions with macroscopic fundamental diagrams. Transportation Res. Part B: Methodological 70:186–200.Google Scholar
- (2013) Dynamic pricing, heterogeneous users and perception error: Probit-based bi-criterion dynamic stochastic user equilibrium assignment. Transportation Res. Part C: Emerging Tech. 27:189–204.Crossref, Google Scholar
- (2015) Do people use the shortest path? An empirical test of Wardrop’s first principle. PLoS ONE 10(8):e0134322.Google Scholar

