Mixed Platoon Flow Dispersion Model Based on Speed-Truncated Gaussian Mixture Distribution

A mixed traffic flow feature is presented on urban arterials in China due to a large amount of buses. Based on field data, a macroscopic mixed platoon flow dispersion model (MPFDM) was proposed to simulate the platoon dispersion process along the road section between two adjacent intersections from the flow view. More close to field observation, truncated Gaussian mixture distribution was adopted as the speed density distribution for mixed platoon. Expectation maximum (EM) algorithm was used for parameters estimation. The relationship between the arriving flow distribution at downstream intersection and the departing flow distribution at upstream intersection was investigated using the proposed model. Comparison analysis using virtual flow data was performed between the Robertson model and the MPFDM. The results confirmed the validity of the proposed model

Designing robust schedule coordination scheme for transit networks with safety control margins

We propose a robust schedule coordination scheme which combines timetable planning with a semi-flexible departure delayed control strategy in case of disruptions. The flexibility is provided by allowing holding for the late incoming bus within a safety control margin (SCM). In this way, the stochastic travel time is addressed by the integration of real-time control and slacks at the planning phase. The schedule coordination problem then jointly optimises the planning headways and slack times in the timetable subject to SCM. Analytical formulations of cost functions are derived for three types of operating modes: uncoordinated operation, departure punctual control and departure delayed control. The problem is formulated as a stochastic mixed integer programming model and solved by a branch-and-bound algorithm. Numerical results provide an insight into the interaction between SCM and slack times, and demonstrate that the proposed model leads to cost saving and higher efficiency when SCM is considered. Compared to the conventional operating modes, the proposed method also presents advantages in transfer reliability and robustness to delay and demand variation

A continuum model with traffic interruption probability and electronic throttle opening angle effect under connected vehicle environment

The electronic throttle system is the key component of the intelligent control system of connected and automated vehicles (CAVs). Although CAVs are expected to be commercialized in the near future, in practice the disturbances and interruptions are not uncommon along the road. In this paper, we propose a new continuum model considering the traffic interruption probability and the electronic throttle opening angle effect. Based on the linear stability analysis, the stability condition of the proposed model is obtained. The KdV-Burgers equation of the new continuum model is further obtained in the nonlinear analysis. The density solution obtained by solving the above equation can be used to describe the evolution characteristics of traffic flow near the neutral stability curve. Results show that the traffic interruption probability and the electronic throttle opening angle effect has a considerable impact on the stability of traffic flow

Genetic Algorithm for Optimizing Routing Design and Fleet Allocation of Freeway Service Overlapping Patrol

The freeway service patrol problem involves patrol routing design and fleet allocation on freeways that would help transportation agency decision-makers when developing a freeway service patrols program and/or altering existing route coverage and fleet allocation. Based on the actual patrol process, our model presents an overlapping patrol model and addresses patrol routing design and fleet allocation in a single integrated model. The objective is to minimize the overall average incident response time. Two strategies—overlapping patrol and non-overlapping patrol—are compared in our paper. Matrix encoding is applied in the genetic algorithm (GA), and to maintain population diversity and avoid premature convergence, a niche strategy is incorporated into the traditional genetic algorithm. Meanwhile, an elitist strategy is employed to speed up the convergence. Using numerical experiments conducted based on data from the Sioux Falls network, we clearly show that: overlapping patrol strategy is superior to non-overlapping patrol strategy; the GA outperforms the simulated annealing (SA) algorithm; and the computational efficiency can be improved when LINGO software is used to solve the problem of fleet allocation

Predicting peak load of bus routes with supply optimization and scaled Shepard interpolation: A newsvendor model

The peak load of a bus route is essential to service frequency determination. From the supply side, there exist ineffective predicted errors of peak load for the optimal number of trips. Whilst many studies were undertaken to model demand prediction and supply optimization separately, little evidence is provided about how the predicted results of peak load affect supply optimization. We propose a prediction model for the peak load of bus routes built upon the idea of newsvendor model, which explicitly combines demand prediction with supply optimization. A new cost-based indicator is devised built upon the practical implication of peak load on bus schedule. We further devise a scaled Shepard interpolation algorithm to resolve discontinuities in the probability distribution of prediction errors arising from the new indicator, while leveraging the potential efficacy of multi-source data by adding a novel quasi-attention mechanism (i.e., scaling feature space and parameter optimization). The real-world application showed that our method can achieve high stability and accuracy, and is more robust to predicted errors with higher capacity. Our method can also produce a larger number of better trip supply plans as compared to traditional methods, while presenting stronger explanatory power in prioritizing the relative contribution of influential factors to peak load prediction