Zhengbing He

Mapping to Cells: A Simple Method to Extract Traffic Dynamics from Probe Vehicle Data

In the era of big data, mining data instead of collecting data are a new challenge for researchers and engineers. In the field of transportation, extracting traffic dynamics from widely existing probe vehicle data is meaningful both in theory and practice. Therefore, this article proposes a simple mapping-to-cells method to construct a spatiotemporal traffic diagram for a freeway network. The method partitions a network region into small square cells and represents a real network inside the region by using the cells. After determining the traffic flow direction pertaining to each cell, the spatiotemporal traffic diagram colored according to traffic speed can be well constructed. By taking the urban freeway in Beijing, China, as a case study, the mapping-to-cells method is validated, and the advantages of the method are demonstrated. The method is simple because it is completely based on the data themselves and without the aid of any additional tool such as Geographic Information System software or a digital map. The method is efficient because it is based on discrete space-space and time-space homogeneous cells that allow us to match the probe data through basic operations of arithmetic. The method helps us understand more about traffic congestion from the probe data, and then aids in carrying out various transportation researches and applications.

An anisotropic continuum model and its calibration with an improved monkey algorithm

ABSTRACT This study proposes an anisotropic continuum model derived from a simplified Hellys model. Its admissibility of a wide cluster solution is then analyzed by the nonlinear weak solution theory. After that, it is calibrated by a monkey algorithm with dynamic adaptation (DAMA) under two cases, and it is concluded that (1) DAMA makes the performance index and model parameters converge to their optimal values in limited iterations; (2) this calibrated model well reproduces the traffic congestions originating from a rubberneck effect within US101 site, besides of those propagated from the downstream boundary; (3) this proposed model with relations of Del Castillo and Benitez, or Greedshields gets better calibration and validation results; (4) the performance index is more sensitive to density-related parameters than to speed-related parameters. In summary, this anisotropic model calibrated by DAMA can well reproduce real traffic waves, and DAMA is a promising algorithm for the higher-order model calibration.

Electric Vehicle Routing Problem with Charging Time and Variable Travel Time

An electric vehicle routing problem with charging time and variable travel time is developed to address some operational issues such as range limitation and charging demand. The model is solved by using genetic algorithm to obtain the routes, the vehicle departure time at the depot, and the charging plan. Meanwhile, a dynamic Dijkstra algorithm is applied to find the shortest path between any two adjacent nodes along the routes. To prevent the depletion of all battery power and ensure safe operation in transit, electric vehicles with insufficient battery power can be repeatedly recharged at charging stations. The fluctuations in travel time are implemented to reflect a dynamic traffic environment. In conclusion, a large and realistic case study with a road network in the Beijing urban area is conducted to evaluate the model performance and the solution technology and analyze the results.

Day-to-day rerouting modeling and analysis with absolute and relative bounded rationalities

ABSTRACT In contrast to a large number of studies in the route choice behavior with absolute bounded rationality, little concern is laid on that with relative bounded rationality which is hypothetically suggested in this paper and can also be an indispensable component of the bounded rationality. This study is conducted to investigate travelers’ day-to-day rerouting behaviors with the above two bounded rationalities. Along this line, an absolute and a relative boundedly rational swapping process (abbreviated as ABRSP and RBRSP, respectively) model are proposed in the frame of nonlinear pairwise swapping rule. It is found that both ABRSP and RBRSP show satisfactory properties. The numerical results suggest that ABRSP and RBRSP share some general similarity in macroscopic convergence, while still showing obvious distinctions in swapping process, and RBRSP cannot be approximated or substituted by ABRSP or its extensions. Therefore, the suggested relative bounded rationality, even if it is hypothetical, still deserves to be taken seriously.

Selfish routing equilibrium in stochastic traffic network: A probability-dominant description

This paper suggests a probability-dominant user equilibrium (PdUE) model to describe the selfish routing equilibrium in a stochastic traffic network. At PdUE, travel demands are only assigned to the most dominant routes in the same origin-destination pair. A probability-dominant rerouting dynamic model is proposed to explain the behavioral mechanism of PdUE. To facilitate applications, the logit formula of PdUE is developed, of which a well-designed route set is not indispensable and the equivalent varitional inequality formation is simple. Two routing strategies, i.e., the probability-dominant strategy (PDS) and the dominant probability strategy (DPS), are discussed through a hypothetical experiment. It is found that, whether out of insurance or striving for perfection, PDS is a better choice than DPS. For more general cases, the conducted numerical tests lead to the same conclusion. These imply that PdUE (rather than the conventional stochastic user equilibrium) is a desirable selfish routing equilibrium for a stochastic network, given that the probability distributions of travel time are available to travelers.