Multimodal Data Analytics Comparative Visualization Tool: Case Study of Pedestrian Crossing Design

• Published in: Transportation research record Vol. 2557; no. 1; pp. 44 - 54
• Main Authors: Khoshmagham, Shayan, Head, K. Larry, Feng, Yiheng, Zamanipour, Mehdi
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 2016
• ISSN: 0361-1981; 2169-4052
• DOI: 10.3141/2557-05

The purpose of this paper is to define a visualization method to evaluate the performance of a multimodal traffic signal system. Previous studies have concentrated on performance assessment for single modes, such as delay, travel time of passenger vehicles, and transit running times. The methodology presented in this paper considers an integrated approach to multimodal performance assessment. A tool, called a multimodal performance dashboard, was developed to visualize the relationship between various performance measures and multiple modes. Dashboards can be used to characterize the performance of an existing system and also for before-and-after studies when a new design is implemented. Radar diagrams are the basic element of the multimodal performance dashboard and are constructed for performance measures (e.g., passenger vehicle travel time, transit delay, pedestrian volume, and truck stops) and for each movement at an intersection. An arterial corridor in the SMARTDrive test bed of the Maricopa County, Arizona, Department of Transportation was analyzed with the Vissim microsimulation model to study the effects of different designs and signal timing strategies on several performance measures for vehicles and pedestrians. According to the results of this study, choosing an appropriate control strategy can affect the different movements of different modes (including pedestrians) in a variety of ways. The more modes involved in the system, the more challenging it is to determine the proper control strategy. Using this comparative tool, alongside statistical models, makes it easier for decision makers to understand, visualize, and analyze data.