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TRB Planning Applications Conference 2017

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Presentation on theme: "TRB Planning Applications Conference 2017"— Presentation transcript:

1 TRB Planning Applications Conference 2017
Getting the Most out of your data: Applying Passively Collected Travel Demand Management Data to Transportation Planning in El Paso TRB Planning Applications Conference 2017 May 17, 2017

2 Texas Department of Transportation (TxDOT):
Project Team 10/8/2015 Texas Department of Transportation (TxDOT): Project Management: Thelma Ramirez, Gus Sanchez, Rebecca Pinto PE CDM Smith: Project Management: Akila Thamizharasan PE PTOE; Ram Maddali, PE; Transportation Planner/Modeler: Roberto Miquel, AICP; Michael Penic Metropia: VP and Project Manager: Vassilis Papayannoulis, Ph.D.  Advisor: Marybeth Stevens Technical Analysist: Ye Tian Community Manager: Tania Chozet DRAFT

3 Project Scope: Study Area (El Paso MPO)

4 Data Analyses: Time of Day Traffic

5 arterial and Intersection analyses

6 Data Analyses: Metropia Arterial Analysis
SB NB SB NB Loop 375 AM Peak Period (7-9 AM) PM Peak Period (4-6 PM) N Moon Rd Horizon Blvd Alameda Ave This segment of Alameda Avenue is a radial corridor in a partially developed suburban fringe area.

7 Data Analyses: Metropia Arterial Analysis
SB NB SB NB I-10 Interchange AM Peak Period (7-9 AM) PM Peak Period (4-6 PM) N Loop Dr N Zaragoza Rd Zaragoza Road is situated in a nearly fully developed suburban area. SB NB SB NB

8 Data Analyses: Comparison of HCS and Metropia Arterial Analysis
Metropia LOS measurements were compared with analysis results based on Highway Capacity Manual analysis procedures. As indicated in this table, the degree of consistency is generally good. Differences thus indicate situations where HCM analysis inputs may not have been consistent with actual field conditions, or may not be sensitive to actual operational issues that occur in the field.

9 Data Analyses: Metropia Intersection Analysis
DEFINITIONS AND METHODOLOGY APPROACH LENGTH: Distance from nearest upstream traffic signal CONTROL DELAY: Average of difference between congested and free flow travel time of each trip AVERAGE INTERSECTION DELAY: Trip weighted average delay on all intersection approaches. LEVEL OF SERVICE CRITERIA: Highway Capacity Manual Exhibit (see below) CONGESTION CRITERIA (LOS F): Based on control delay only (Metropia sample can not measure total demand or capacity)

10 Data Analyses: Metropia Intersection Analysis

11 Data Analyses: TxDOT Dashboard update
Added Planning Time Index metric TTI represents the level of congestion and is calculated as follows TTI =  (Travel Time)/(Free Flow Travel Time) PTI represents the time a traveler should allow to ensure on-time arrival and it is calculated as follows PTI=(95th-percentile Travel Time)/(Free Flow Travel Time)

12 Construction zone analyses

13 Data Analyses: Future Construction Zone Analyses
I-10/Hawkins Blvd Ramp Improvements Phase 3 Stage 1 during construction

14 Data Analyses: Transportation Roadway Systems Analysis
Long-Range Planning : Assess the performance of the transportation system in terms of strategies, policies and infrastructure changes consistent with a long- term vision or strategic plan. This type of analysis is best supported by Travel Demand Forecasting Models (TDFM). Detailed Operations : Assess the performance of the transportation system in terms of strategies and infrastructure changes consistent with a plan to enhance operations. This type of analysis is best supported by Micro-simulation models .  Planning for Operations:    Assess the performance of the transportation system in terms of strategies and policies enabled primarily by technology and consistent with a regional collaborative plan to enhance operations. This type of analysis is best supported by Mesoscopic models .

15 Data Analyses: Multi-Resolution Model Application
. Meso Micro Macro Multi-Resolution Models reflect an integrated or linked suite of models that could be used either as a “diagnostic tool”, to identify critical areas, or as an “assessment tool” to evaluate short or long- term strategies, policies or infrastructure changes.

16 Data Analyses: Future Construction Zone Analyses
728 zones, 3170 nodes, 6727 links. 24 hr time horizon. 2.53M auto trips, 0.33M truck trips. 2013 Network, 2013 Demand. Provided by TTI El Paso office. Network refinement to reflect the change from 2013 to 2017: Added one more lane on I-10 WB Service Rd between Hawkins and Airway (before the off ramp and the on ramp). DUE – Dynamic User Equilibrium These scenarios demonstrate the change in performance of the corridor before and after construction, and performance during the construction phase with the greatest construction impacts.

17 Data Analyses: Future Construction Zone Analyses
DUE – Dynamic User Equilibrium These scenarios demonstrate the change in performance of the corridor before and after construction, and performance during the construction phase with the greatest construction impacts.

18 Data Analyses: Future Construction Zone Analyses
A bottleneck due to work zone Lowest possible speed defined in traffic flow model DUE – Dynamic User Equilibrium These scenarios demonstrate the change in performance of the corridor before and after construction, and performance during the construction phase with the greatest construction impacts.

19 Data Analyses: Future Construction Zone Analyses
Pre vs During Construction Overall reduction in demand in both directions on the I-10 freeway due to construction constraints Reduction in frontage road traffic that occurs due to ramp closures, or the reduction in the number of frontage road lanes, Increase in frontage road traffic downstream of the closed entrance ramps Construction activity has a significant impact on frontage road speeds throughout the daytime hours and into the early night period DUE – Dynamic User Equilibrium These scenarios demonstrate the change in performance of the corridor before and after construction, and performance during the construction phase with the greatest construction impacts.

20 Data Analyses: Future Construction Zone Analyses
Pre vs After Construction Small increases in daily I-10 throughput illustrate the cumulative benefits of traffic patterns that most likely diverted from other routes (the improvements do not involve much freeway mainline capacity) For the WB frontage road, a major reduction in the morning peak period delays is indicated DUE – Dynamic User Equilibrium These scenarios demonstrate the change in performance of the corridor before and after construction, and performance during the construction phase with the greatest construction impacts.

21 Data Analyses: Implemented Construction Zone Analyses
Paisano Closure (June 12, Winter 2017) I-10 Mesa Paisano Executive Center Sunland Park Closure on Paisano between just east of Sunland Park and Executive Center. Possible detour route: I-10 and Mesa.

22 Data Analyses: Implemented Construction Zone Analyses
Paisano NB before Closure Origins: Primarily UTEP/downtown Destinations: Primarily Westside 45% from Executive Center 55% from Paisano

23 Data Analyses: Implemented Construction Zone Analyses
Traffic from Paisano NB just South Executive Center Paisano between Executive and Sunland Park is still open to local business after the closure. Travelers on Paisano NB South of Executive Center have to divert to Executive Center and then Mesa for detour. BEFORE CLOSURE AFTER CLOSURE 42% continue on Paisano 58% goes to Executive 4% continue on Paisano 96% goes to Executive/Mesa

24 Data Analyses: Implemented Construction Zone Analyses
Traffic from Executive Center WB Now travelers on Executive Center WB are those who intent to turn left to Paisano SB and then go to downtown area. BEFORE CLOSURE AFTER CLOSURE 90% turn right to Paisano NB 93% turn left to Paisano SB 4% turn left to Paisano SB

25 Questions/Feedback/Recommendations THANK YOU
Thelma Ramirez, TxDOT Project Manager (915) Akila Thamizharasan, CDM Smith Project Manager (512)


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