Analysis of Urban Public Transit Pricing Adjustment Program Evaluation Based on Trilateral Game

AbstractEstablishment and implementation of the urban transportation pricing adjustment program will have great impacts on holistic development of urban transportation. The paper establishes a trilateral game model on pricing adjustment program participants, including governments, public transport enterprise and passengers. Through analyzing trilateral benefits, the model can conclude if an adjustment program succeeds or not. Furthermore, adopting the modeling method of Stackelberg oligopoly model, applying backward induction method in model analysis, the model presents an evaluation method for estimating whether the public transit pricing adjustment program is successful or not. The work provides a research method for studying the feasibility of an urban transportation pricing adjustment program

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

Effect of salinity on the biochemical characteristics and antioxidant activity of exopolysaccharide of Porphyridium purpureum FACHB 806

Porphyridium exopolysaccharide (EPS) is a kind of high-value biopolymer with various biological activities secreted by microalgae belonging to Porphyridium genus. Salinity is one of the important environmental factors affecting the growth of microalgae. In order to study the effect of salinity, the yield, biochemical characteristics and antioxidant activity of EPS in Porphyridium purpureum FACHB 806 cultured at four salinity levels (5‰, 20‰, 35‰ and 50‰) were investigated in this study. The results demonstrated that P. purpureum FACHB 806 could grow at all salinity levels. The highest cell density and EPS yield per cell were 6.6 × 107 cells·mL-1 and 29.1 pg·cell-1, which were obtained in the 20‰ and 50‰ salinity, respectively. With the increase of salinity, the percentage of xylose and galactose decreased while the percentage of glucose increased. Among all salinity levels, the 5‰ salinity group achieved the maximum contents of total carbohydrate and uronic acid of EPS, and the 50‰ salinity obtained the highest protein content of EPS. Compared to the 20‰ and 35‰ salinity groups, EPS of the 5‰ and 50‰ salinity showed stronger hydroxyl radical scavenging ability. These results indicated that salinity could influence the yield, biochemical composition and antioxidant activity of EPS, which will provide a new strategy to improve the yield and antioxidant activity of EPS

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

Analysis of Urban Car Owners Commute Mode Choice Based on Evolutionary Game Model

With the aggravation of the traffic congestion in the city, car owners will have to give up commuting with private cars and take the public transportation instead. The paper uses the replication dynamic mechanism to simulate the learning and adjustment mechanism of the automobile owners commuting mode selection. The evolutionary stable strategy is used to describe the long-term evolution of competition game trend. Finally we simulate equilibrium and stability of an evolution of the game under a payoff imbalance situation. The research shows that a certain proportion of car owners will choose public transit under the pressure of public transport development and heavy traffic, and the proportion will be closely related to the initial conditions and urban transportation development policy

Optimization Method of Locomotive Working Diagram Layout

Rational scheduling of locomotive paths (the locus of the locomotive point in the train working diagram) is an important step in drawing a locomotive working diagram by a computer. But there are some problems in this process, such as the computer usually drawing a locomotive path that overlaps with another locomotive path (in the circumstances, the actual users of the locomotive working diagrams often misread the locomotive planning). At present, there are many studies about assigning sets of locomotives to each train in a preplanned train schedule; in contrast, the studies of visualizing the locomotive planning are relatively rare. Through investigating the locomotive working diagram users, this paper points out that the layout of locomotive paths should put the distance between lines being as large as possible and should put the number of the intersection between lines being as few as possible as the optimization aim which is based to solve the problem of the lines overlap or the problem of the lines beyond the margins for drawing the locomotive paths. This paper also builds the optimization model of locomotive working diagram layout. Based on determining the position of locomotive paths which can be delineated, a genetic algorithm is used to solve the optimizing model of locomotive working diagram layout in this paper. An example of a train working diagram with 36 trains is given at the end of the paper, which indicates that the optimization model of locomotive working diagram layout can better solve the problem of locomotive planning visualization

Scheduling Combination Optimization Research for Bus Lane Line

Different scheduling forms can be adopted in bus lane system to meet passengers’ travel demand well and improve operational efficiency. Therefore, this paper researched the optimal headway and bus scheduling combination of a bus lane line. Bus scheduling combination is composed of a sequence of full-length, express bus and short-turn. We established a model to minimize passengers’ waiting cost and vehicles’ operation cost and to optimize headway and bus scheduling combination, under the constraint of the headway restriction for each stop, the minimum number of vehicle trips in one hour and the proportion of short-turn and express bus trips in total trips. The model was solved by improved genetic algorithm, and the optimal solution was obtained by repeating the operation of genetic algorithm L times. The results of numerical example show that the whole cost can be saved by 21.77% at most after optimization, which indicate the model and algorithm we presented are reasonable and practicable. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.316

Model and Algorithm of Regional Bus Scheduling with Grey Travel Time

The regional bus scheduling is the future trend of urban public transport development. It focuses on assigning trips belonged to several routes to buses located at different depots to reduce fleet size and operating costs. With consideration of the emergencies in reality interfering with vehicles to complete a trip on time, this paper studies regional bus scheduling problem with grey travel time to meet some side constraints such as multi-vehicle-type, depots capacities and fuelling, etc. The model is resolved by the improved ant colony algorithm to prepare a lowest-cost scheduling scheme. The proposed scheduling method is easily operated and can be used for different situations. At the last section, an example proves the correctness and effectiveness of the model and algorithm

A Platoon Dispersion Model Based on a Truncated Normal Distribution of Speed

Understanding platoon dispersion is critical for the coordination of traffic signal control in an urban traffic network. Assuming that platoon speed follows a truncated normal distribution, ranging from minimum speed to maximum speed, this paper develops a piecewise density function that describes platoon dispersion characteristics as the platoon moves from an upstream to a downstream intersection. Based on this density function, the expected number of cars in the platoon that pass the downstream intersection, and the expected number of cars in the platoon that do not pass the downstream point are calculated. To facilitate coordination in a traffic signal control system, dispersion models for the front and the rear of the platoon are also derived. Finally, a numeric computation for the coordination of successive signals is presented to illustrate the validity of the proposed model

A Bi-level Programming Model for Uncertain Regional Bus Scheduling Problems

Regional bus scheduling is the future trend in public transportation which deals with allocating trips belonged to several routes to buses located at different depots to reduce the size of bus fleets and their operating costs. Considering many emergency events which may affect on-time vehicle arrivals, a bi-level programming model is applied to address the relationship between bus scheduling and its procurement scheme from an overall perspective. The model takes into consideration several constraints such as depot capacities, fueling, and emissions of polluting gases. Solutions to different situations of the upper and lower model are obtained by using a genetic algorithm. Based on some established criteria for a satisfactory solution, a series of lower solutions meeting the established criteria are generated as inputs for the upper model. Thereby, the best lower and the corresponding upper solutions are generated by comparing them. Finally, an example is illustrated to prove the accuracy and effectiveness of our model and its algorithm