IDOT: Improving the Transit System for Seniors
Taha Hossein Rashidi, PhD Candidate, Advisor: Dr. Mohammadian
As a research assistant at the University of Illinois at Chicago, I am currently working on a project funded by Illinois Department of Transportation (IDOT) with the goal to improve the effectiveness of transit systems for seniors. We have conducted an opinion survey of seniors attempting to understand their transit use behavior. Given the aging population, this is an important problem to address (by 2030 number of seniors in the US will be doubled). The percentage of elderly transit users in Northeastern Illinois is low in comparison to the number of elderly who could utilize transit services. A survey of seniors in Chicago region was designed and conducted to collect the information required to analyze the effectiveness of strategies that have been implemented, or are being planned, to attract this age group.
The main goal of the study that I am working on is to enhance transit providers’ awareness on how to be more effective in attracting senior riders. For this purpose I have designed a questionnaire which consists of four main sections dealing with different trip purposes (Shopping, Doctor Visit, Social and Recreational, and Work trips) and different travel modes in Chicago region including three commonly used public transit modes of Metra, CTA and PACE, as well as a section asking general questions on respondents’ socio-economics, location, and built environment attributes. Survey respondents are also asked to provide their opinions about transit services within the region.
A stated preference analysis is then conducted using this information. The results of the analysis represent seniors’ preferred alternatives and effective strategies for system improvement. Discrete Choice models are used to estimate the probability of utilizing each mode for this age group. Furthermore, policy analysis using the modeling results introduces the effective factors that should be considered and applied to improve transit services that could encourage senior citizens to use public transportation facilities more often.
Developing and Validating a Household Travel Data Transferability Model
Yong-Ping Zhang, PhD Candidate, Advisor: Dr. Mohammadian
Traditionally, Metropolitan Planning Organizations are required to have their models calibrated on a continuing basis using new data. However, new survey data required to support these models do not exist in most urban areas. This makes it very difficult to calibrate existing models or develop new travel demand models using emerging modeling techniques. As a result, the need to assess potential approaches and develop knowledge on how to transfer information collected in one context and use it in another context is becoming critical.
The ultimate goal of my research is to develop and validate a household travel data transferability model that can facilitate the use of national household travel survey data to a local area. Furthermore, using the transferred estimates and synthesized population, the study will attempt to micro-simulate disaggregate household travel survey data. This can reduce or eliminate the need for a large data collection in the application context and will allow small MPOs to utilize transferred travel attributes from similar areas.
Additionally, in larger metropolitan areas where MPOs can afford carrying out a standard household travel survey, a small-scale survey can be conducted periodically for improving the quality of the simulated data by updating the parameters of the transferred data. Such a small sample can reduce the need for a regular full-scale survey and increase the time interval of the full-scale survey to every 6-7 years or even longer.
Development of an Improved Scheduling Model for use in Micro-simulation Modeling
Joshua Auld, PhD Candidate, Advisor: Dr. Mohammadian
For my research I am currently focusing on developing an improved activity scheduling model for use in regional microsimulation modeling. The activity scheduling model will eventually be used with other data sources to develop an activity-based travel demand model for the Chicago area. These models have the potential for greatly increasing the accuracy of future travel demand estimates. More accurate models would have a large impact on the planning and policy decisions for which these models are usually used.
At the current stage, I am using data mining techniques to identify patterns in individuals’ activity rescheduling behavior. This is done using activity scheduling process survey data, which includes information on how and when people schedule activities, as well as how they reschedule the activities when conflicts in the schedule arise. The patterns observed in the activity scheduling and rescheduling data will than be used to develop rules for how activity conflicts are resolved by different individuals. The use of rule-based conflict resolution will potentially improve the accuracy of activity scheduling models. In the future, the conflict resolution model will be combined with an activity generation model to create an activity scheduling simulator. This will then be used with activity survey data from several areas to initially check the transferability of the rescheduling rules, by comparing the simulated activity schedules against the actual schedules obtained from the survey data.