HOV-scanner : adding PT route choice and optimizing the processing time

Motivation and research objective: The HOV-scanner can be used to indicate the effect on public transport (PT) share of changes in PT services, for example, a new PT line. The HOV-scanner is developed and used by MuConsult. The HOV-scanner in its current layout is facing some limitations: 1. In case of parallel PT connections all demand is assigned to the most attractive connection. It is likely to assume that the assignment is more nuanced in real life. 2. The HOV-scanner is used as a first indicator for the feasibility of a new PT connection, but using it for this purpose is complex due to the layout of the HOV-scanner. This results in an operation that is too labor-intensive. In this study both topics are studied and the HOV-scanner is improved accordingly. As a result the research objective is: “To implement PT route choice into the HOV-scanner to simulate parallel connections more realistic. Furthermore, the work load should be reduced to make the HOV-scanner more suitable as a first indication regarding the feasibility of a new PT system.” The objective of this research results in two research questions: 1. How should the HOV-scanner be designed to be able to model parallel PT connections? 2. How can the HOV-scanner be improved to reduce the work load? The HOV-scanner: The HOV-scanner is a tool that uses origin/destination (OD) matrices and utility functions to calculate a modal split. The HOV-scanner is programmed in MATLAB. It is designed according to the four-stage transportation model. The total trip distribution is calculated and aggregated to match the desired zone size. Then the modal split is modeled for the reference situation by using a Multinomial Logit choice model. Errors are calibrated if any occurred. The changes in the PT network in combination with the sensitivity toward changes results in a new utility for PT. This new PT utility is used to forecast the distribution for the new situation. The HOV-scanner is modeled according to the schedule based approach. Research approach: As part of the research the current HOV-scanner is analyzed and an introducing literature study has been performed. Thereafter a route set generation method for PT and a choice model are composed and elaborated. The route set generation method should improve processing time and include all attractive PT routes within the study area. A constrain set is proposed with which the PT route set must comply. Programs and methods are analyzed and the constrained enumeration method is selected as being the most suitable. The constrained enumeration method and the constraints are implemented in a MATLAB program. The program is applied on the “Duin en Bollenstreek” area and resulted in a processing time reduction of a factor five. This is a satisfying improvement over the manual method especially since the HOV-scanner is extended from a single route from towards a route set. In extension of the original HOV-scanner PT route choice is included and therefore the choice model is altered. A nested Logit model is proposed whereby the different PT routes are nested in the PT branch. To forecast the effect of a new PT scenario a four step approach is conducted: 1. Set up and apply the choice model for the reference situation. 2. Calibrate the outcome of the choice model for each OD relation and mode 3. Calculate the shift in utility for the PT system based upon information that is retrieved in the first step. 4. Forecast the use of the PT system for the scenario. To model the PT utility it is proposed that in vehicle time, waiting time, transfer time, access an egress time, number of transfers, frequency and PT modes should be included. During the implementation on the “Duin en Bollenstreek” data the frequency and PT mode deviation is neglected due to modeling errors. Furthermore the generalized cost for PT is used to improve the model. The generalized cost for PT consists of the selected parameters and a weight ratio that is retrieved from literature.

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