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

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.

[1]  Robert B. Noland,et al.  Trade-Offs Between Vehicular and Pedestrian Traffic Using Micro-Simulation Methods , 2007 .

[2]  Zong Tian,et al.  Pedestrian Timing Alternatives and Impacts on Coordinated Signal Systems Under Split-Phasing Operations , 2001 .

[3]  Xuan Wang,et al.  Pedestrian Delay Models at Signalized Intersections Considering Signal Phasing and Pedestrian Treatment Alternatives , 2009 .

[4]  Fred L. Mannering,et al.  Right Turns on Green and Pedestrian Level of Service: Statistical Assessment , 2009 .

[5]  Yiheng Feng,et al.  Connected Vehicle–Based Adaptive Signal Control and Applications , 2016 .

[6]  Michael Anderson,et al.  TRAFFIC SIMULATION SOFTWARE COMPARISON STUDY , 2004 .

[7]  Lars Leden,et al.  Pedestrian accidents and left-turning traffic at signalized intersections , 1993 .

[8]  Yue Liu,et al.  Multiobjective Optimization of Signal Timings for Two-Stage, Midblock Pedestrian Crosswalk , 2011 .

[9]  Robert B. Noland PEDESTRIAN TRAVEL TIMES AND MOTOR VEHICLE TRAFFIC SIGNALS , 1996 .

[10]  J B Kirschbaum,et al.  DESIGNING SIDEWALKS AND TRAILS FOR ACCESS, PART 2, BEST PRACTICES DESIGN GUIDE , 2001 .

[11]  Timothy J Lomax,et al.  Performance Measures for Multimodal Transportation Systems , 1996 .

[12]  Peter Vortisch,et al.  VALIDATION OF THE MICROSCOPIC TRAFFIC FLOW MODEL VISSIM IN DIFFERENT REAL-WORLD SITUATIONS , 2001 .

[13]  Lin Zhang,et al.  Signalized Intersection Level of Service Incorporating Safety Risk , 2003 .

[14]  I Made Brunner,et al.  Use of Safety Viewgrams to Visualize Driver and Pedestrian Interactions , 2007 .

[15]  M S Kaseko COMPARATIVE EVALUATION OF SIMULATION SOFTWARE FOR TRAFFIC OPERATIONS , 2002 .

[16]  Yang Xiaoguang Design method of pedestrian phases at multi-phase signal intersection , 2004 .

[17]  Ansie Harding,et al.  Using radar charts with qualitative evaluation , 2008 .

[18]  Zong Tian,et al.  SIGNAL TIMING STRATEGIES IN DEALING WITH PEDESTRIAN CROSSINGS , 1999 .

[19]  Darcy M. Bullock,et al.  Integration of Real-Time Pedestrian Performance Measures into Existing Infrastructure of Traffic Signal System , 2008 .

[20]  Yiheng Feng,et al.  Efficient Priority Control Model for Multimodal Traffic Signals , 2016 .