Hamilton Truck Route Study

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1 Prepared for the City of Hamilton March 2012

2

3 Pavlos S. Kanaroglou, Ph.D. Vivek Korikanthimath, Ph.D. McMaster Institute of Transportation and Logistics McMaster University Hamilton, Ontario March 2012 mitl.mcmaster.ca

4

5 Table of Contents Table of Contents... i Tables... i Figures... ii Executive Summary Introduction Methodology The TRAFFIC Model Street Network Trip Assignment Procedure Origin-Destination Vehicle Trips Bus Traffic Flows Scenario Development Analysis of Assignment Results Scenario 2 vs. Scenario Scenario 3 vs. Scenario Conclusions References Appendix Tables Table 1: Assignment Summary Table A.2: Vehicle Flows: Fruitland Rd between Barton and Highway Table A.3: Vehicle Flows: Dundrun St S. between King and York Table A.4: Vehicle Flows: Upper Ottawa St, South of Mountain Brow Table A.5: Vehicle Flows: Kenilworth Ave S, South of Central Ave Table A.6: Vehicle Flows: Bay St N. between King and York WS Table A.7: Vehicle Flows: Queen St S. between York and King St Table A.8: Vehicle Flows: Mountain Brow Blvd, West of Upper Ottawa St Table A.9: Vehicle Flows: Red Hill Valley Parkway Table A.10: Vehicle Flows: King St W McMaster Institute for Transportation and Logistics Page i

6 Figures Figure 1: Main Window of the Traffic Software for Hamilton... 7 Figure 2: TRAFFIC Modelling Framework... 9 Figure 3: Scenario 1-Heavy Vehicle Flow, 8-9 am Figure 4: Scenario 2-Heavy Vehicle Flow, 8-9 am Figure 5: Scenario 3-Heavy Vehicle Flow, 8-9 am Figure 6: Scenario 1-Medium Vehicle Flow, 8-9 am Figure 7: Scenario 2-Medium Vehicle Flow, 8-9 am Figure 8: Scenario 3- Medium Vehicle Flow, 8-9 am Page ii McMaster Institute for Transportation and Logistics

7 Executive Summary The McMaster Institute for Transportation and Logistics (MITL) undertook this study to analyze and quantify the impacts of temporary removal of truck route locations in Hamilton, in accordance with an agreement between City of Hamilton and McMaster University. The study presents an analysis of scenarios pertaining to the configuration of truck routes, and helps in understanding the resulting variations in commercial vehicle flow patterns in the region from modifications to the truck route system. A previous study conducted by the City of Hamilton to develop an equitable truck route system for its residents and the industry, resulted in revisions to the Hamilton truck network, approved by the City Council in September While the new truck route plan facilitates efficient movement of goods in the Hamilton region, the traffic impacts of the modifications have not been assessed. This study attempts to measure the effects of these changes, and the effects of potential changes at three other locations. Three scenarios, corresponding to the Original Truck Route (prior to the 2010 changes), Modified Truck Route (with the 2010 changes), and Modified Truck Route with Removals (potential modifications), are modelled here. Using a GIS based, in-house travel demand modelling and forecasting software, the study estimates link-level hourly traffic flows on the Hamilton road network for year Flows are estimated for various categories of vehicles, including passenger cars; heavy, medium, and light duty commercial vehicles; and buses. The estimated volumes of commercial vehicles are validated against the 2010 count data. A comparison of the model-assigned commercial vehicle volumes between the three scenarios, helps in understanding the impacts of the truck route changes. Hourly flows for commercial vehicles on Hamilton s road network are presented using traffic flow maps and tables, included in the report. The modeling results provide a snapshot of commercial vehicle movements under the various truck route scenarios. They also identify diversions of commercial vehicle flows, based on truck route restrictions. For the Modified Truck Route scenario, diversions of heavy and medium commercial vehicles from Burlington St to Barton St and Cannon St were found as a section of Barton St from Wentworth St to Queen St was eliminated (Figures 4 and 7). Other major impacts include, increase in commercial vehicle flow on Red Hill Valley Parkway and Main St W, and decrease in flows on Upper Ottawa St, south of Mountain Brow Blvd, and Kenilworth Ave, south of Central Ave. For the Modified Truck Route with Removals scenario, diversions of heavy and medium commercial vehicles to Red Hill Valley Parkway were found due to closure of Kenilworth Access (Figures 5 and 8). A further decrease in heavy and medium commercial flow on Upper Ottawa St, south of Mountain Brow Blvd was also observed due to the removal Kenilworth Access. The closure of Dundurn St N between King St W and York Blvd would cause a decrease west bound heavy and medium vehicle movement on York Blvd, result in an increase in movement on King St W. The conversion of Fruitland Road between Barton St and Highway 8 to parttime, seems to have no significant impact on commercial vehicle movement. A summary of the model assigned total daily commercial vehicle flows against the 2010 average weekday truck count data is presented below. Page 3 McMaster Institute for Transportation and Logistics

8 Assignment Summary: 2010 Total Average Weekday Truck Counts vs Total Daily Model Assigned Scenario 1 Scenario 2 Scenario Total Counted 2011 Original 2011 Modified 2011 Modified Truck Route Trucks Truck Route Truck Route Model with Model Model Removals Location Fruitland Road Between Barton and Highway 8 1, Dundrun Street S Between King and York 1,737 1,809 1,813 1,774 Upper Ottawa Street, South of Mountain Brow 1, Mountain Brow Blvd, West of Upper Ottawa St 1, Kenilworth Ave S, South of Central Ave 3,244 2, Bay Street N. Between King and York St WS 1,055 2,037 1,422 1,428 Queen Street S Between York and King St 1,328 1,671 2,491 2,550 Total 11,359 10,010 8,916 8,592 Red Hill Valley Parkway - 3,021 3,207 3,680 Decrease Increase Page 4 McMaster Institute for Transportation and Logistics

9 1.0 Introduction Introduction The City of Hamilton, owing to its strategic location, serves as a major transportation hub in Ontario. Hamilton boasts a major port and airport that facilitate the movement of road and rail cargo to domestic and trans-border trade locations. While trucking has a significant effect on the city s economic growth and development, it also generates negative environmental and social impacts. Pursuant to the impetus of preserving economic vitality in the region while mitigating impacts to community and the environment, a comprehensive study was conducted. This study resulted in recommendations for future action, policies for truck route signage, and a methodology for dealing with truck route network issues in the future (City of Hamilton, 2010). Consequently, revisions were undertaken to the truck route system in September In view of the approved changes to the city s truck route network by the Hamilton City Council in 2010, further modifications at three truck route locations are being considered for an 18 month pilot evaluation period. In order to understand the traffic impacts of the changes made in 2010, and these prospective modifications, the McMaster Institute for Transportation and Logistics (MITL) undertook this study, in accordance with an agreement between City of Hamilton and McMaster University. Using an in-house travel demand modelling and forecasting software, TRAFFIC, the study simulates the traffic patterns in the region under various truck route scenarios pertaining to restrictions on truck movement. Link-level traffic flows resulting from the assignment procedures are used in quantifying the differences between the scenarios, and in capturing the regional impacts at specified time periods of the day. McMaster Institute for Transportation and Logistics Page 5

10 2.0 Methodology Methodology 2.1 The TRAFFIC Model TRAFFIC is a GIS-based travel demand forecasting and modelling software that is designed to simulate traffic flows. A Graphical User Interface (GUI) facilitates the design of scenarios, and the editing, and display of traffic assignment results. The software incorporates all major highways and arterials in the Hamilton-Burlington region. Trips originating and terminating in the region are represented by traffic analysis zones (TAZs). Figure 1 presents the TRAFFIC GUI for the Hamilton region. The model is sensitive to variations in specifications and inputs such as number of lanes, roadway capacity, speed, road closures, etc. Page 6 McMaster Institute for Transportation and Logistics

11 2.2 Street Network Figure 1: Main Window of the Traffic Software for Hamilton The street network for the Hamilton region is represented as a graph consisting of links and nodes to be used in the traffic assignment routine. Each link is associated with attributes such as length (km), posted travel speed (km/hr), and design capacity (passenger car/ hr) based on the number of lanes. The restriction of trucks, namely medium and heavy duty commercial vehicles on road links is identified by a variable (A flag TRKLN = 1 is assigned to all links used by trucks, otherwise TRKLN = 0 for restricted links). The GIS Shapefile representing the bus transit lines in the Census Metropolitan Area (CMA) of Hamilton were obtained from the City of Hamilton and municipality of Burlington. McMaster Institute for Transportation and Logistics Page 7

12 2.3 Trip Assignment Procedure Hourly traffic flows are estimated for five classes of vehicles as below: 1. Light Duty Passenger (LDPVs) 2. Light Duty (LDCVs) 3. Medium Duty (MDCVs) 4. Heavy Duty (HDCVs) 5. City Transit (i.e. Buses) With the exception of transit traffic flows, passenger and commercial flows are determined from hourly origin destination (OD) trip matrices that were derived from household travel surveys (in the case of passenger trips) and estimated from regression models (in the case of commercial trips). The origindestination zones are represented as polygons, corresponding to the census tracts in the Hamilton CMA. The traffic assignment used by the model to estimate link based traffic flows is the Stochastic User Equilibrium (SUE) traffic assignment. In this method, an OD matrix representing motorized passenger trips throughout pre defined, mutually exclusive traffic analysis zones (TAZs) in the city is used as input to the procedure. The SUE algorithm assigns trips to particular paths connecting origin i and destination j under the principle of user equilibrium. Under user equilibrium, travel time on all used paths in the city is less than or equal to travel time on any un used path. As such, no traveler would theoretically be able to reduce his or her travel times by unilaterally altering the used path. Using an iterative process, the SUE algorithm tries to simulate how travelers choose their paths to go from a given origin to a give destination. 2.4 Origin Destination Vehicle Trips The origin destination passenger vehicle trip data for Hamilton are based on the 2006 Transportation Tomorrow Survey (TTS) data. The data are based on a comprehensive travel survey conducted in the Greater Toronto and Hamilton Area (GTHA) once every five years, the latest being Besides collecting socio economic information on the surveyed travelers, the survey identifies the mode of transportation, departure time of the trip, and the origin destination zone for which the trip took place. This information is utilized to create OD matrices by hour of the day for motorized trips. The survey data were processed to extract the hourly OD matrices for Hamilton, and 24 matrices representing the trips taking place during the 24 hours of a typical day were created. Since Hamilton is represented by 223 mutually exclusive TAZs, each of the 24 hourly matrices is a 223 x 223 table. As data on commercial vehicle trips did not exist for the Hamilton study area, the commercial vehicle OD trips were created by using regression models. Utilizing the commercial vehicle OD matrices for the year 2006 in the City of Calgary, provided by Environment Canada, trip generation and trip distribution model parameters were estimated. Given, employment figures by type of occupation, as derived from the 2006 Canadian Census on place of work, it was possible to establish a statistical relation between the Page 8 McMaster Institute for Transportation and Logistics

13 observed commercial trips (by type of vehicle) for a given period of the day and employment by type of occupation. A set of trip generation and distribution models were specified and estimated. 2.5 Bus Traffic Flows Bus traffic flows for Hamilton, for the base year 2006, is based on information found in the time table of a given transit line. Typically, a given transit line is divided into several segments representing major stops (time points). Using the departure time of a bus at a given point, the number of buses travelling on each segment is derived from the time table. Once the number of buses are extracted and coded in the attribute table of the transit network, the total flows on a given line segment are added up to determine the total flow from all bus lines and all directions. The result is a database that provides the total number of buses by line segment on the road network. Figure 2 shows the modelling framework for TRAFFIC. Using 2006 as the base year, future year (2011, 2016, 2021, 2026 and 2031) OD matrices for all classes of vehicles are derived from population and employment projections in the Hamilton region. Figure 2: TRAFFIC Modelling Framework McMaster Institute for Transportation and Logistics Page 9

14 3.0 Scenario Development Scenario Development In order to discern the effects of modifications to the Hamilton truck route system, three scenarios were simulated for the study: Original Truck Route (prior to September 2010 revisions) New Truck Route (incorporates September 2010 revisions) New Truck Route with Removals (includes September 2010 revisions and three potential changes) Using an incremental approach, the study quantifies the impacts of the truck route changes by comparing the assignment results, obtained by implementing the TRAFFIC model, between the three scenarios. The SUE algorithm, discussed previously, played an important role in deriving hourly estimates of link-based traffic flows in the Hamilton CMA. As the model year closest to 2010, during which the traffic count data were collected in Hamilton, is 2011, it was essential to validate the 2011 year TRAFFIC model against the 2010 count data. For this purpose, mid-block volume count data for various classes of vehicles (based on FHWA Classification) collected in July 2010 were obtained from the City of Hamilton. Further, count data pertaining to trucks were extracted and compared against the assigned, hourly commercial vehicle link flows at the same locations. Table 1 presents a comparison of the model assigned total daily commercial vehicle flows against the 2010 average weekday truck count Page 10 McMaster Institute for Transportation and Logistics

15 data. The total assigned commercial vehicle flows at the count locations matched the data with an efficiency of 88%. This underestimation is expected as the Hamilton TRAFFIC model does not represent trips originating and terminating outside of the Hamilton-Burlington region (e.g., trips from Kitchener, Niagara, USA, and east GTA regions). Consequently, the external trips that pass through the count locations are not captured by the model. However, the validation suffices to the extent of justifying the Hamilton TRAFFIC model s ability to replicate the average weekday flow patterns of commercial vehicles in the region, and lend to the analyses of the scenarios 2 and 3, considered in the study. Table 1: Assignment Summary: 2010 Total Average Weekday Truck Counts vs Total Daily Model Assigned Scenario 1 Scenario 2 Scenario Total Counted 2011 Original 2011 Modified 2011 Modified Truck Route Trucks Truck Route Truck Route Model with Model Model Removals Location Fruitland Road Between Barton and Highway 8 1, Dundrun Street S Between King and York 1,737 1,809 1,813 1,774 Upper Ottawa Street, South of Mountain Brow 1, Mountain Brow Blvd, West of Upper Ottawa St 1, Kenilworth Ave S, South of Central Ave 3,244 2, Bay Street N. Between King and York St WS 1,055 2,037 1,422 1,428 Queen Street S Between York and King St 1,328 1,671 2,491 2,550 Total 11,359 10,010 8,916 8,592 Red Hill Valley Parkway - 3,021 3,207 3,680 Decrease Increase McMaster Institute for Transportation and Logistics Page 11

16 4.0 Analysis of Assignment Results Analysis of Assignment Results Figures 3-8 present the flow patterns of heavy and medium commercial vehicles for the three scenarios between 8 am to 9 am, when the commercial vehicle movement in Hamilton is the highest. As the truck route restrictions apply to the movement of trucks over 4.5 tonnes, the assignment results for only heavy and medium commercial vehicles have been shown here. Because the class of light commercial vehicles in the model is not subjected to truck route restrictions, the impact of route modifications has not been significant. The redistributions of commercial vehicle traffic based on the restrictions are summarized in the subsequent sections, by comparing scenarios 1 and 2, and scenarios 2 and 3. Although the magnitude of variations in assigned volumes is different for heavy and medium commercial vehicles, the trends are similar. While the diagrams provide a snapshot of the movement of commercial vehicles, specific hourly variations for each class of commercial vehicle may be obtained by referring to the summary tables provided in the appendix. McMaster Institute for Transportation and Logistics Page 12

17 4.1 Scenario 2 (2011 Modified Truck Route Model) vs. Scenario 1(2011 Original Truck Route Model): Diversion of heavy and medium commercial vehicle flow from Burlington St to Barton St and Cannon St as access on Barton from Wentworth St to Queen St is eliminated. Increase in heavy and medium commercial vehicle flow on Queen St South as it provides access from Cannon St to King St W and Highway 403. Increase in heavy and medium commercial vehicle flow on Main St W as it provides inbound access. Decrease in heavy and medium commercial vehicle flow on Bay St North as access to Burlington St is removed. Decrease in heavy and medium commercial vehicle flow on streets west of Wellington St (James St N and John St N) providing access to King St and York St. Increase in heavy and medium commercial vehicle flow from Red Hill Valley Parkway to Barton St East. Decrease in heavy and medium commercial vehicles on Upper Ottawa St, south of Mountain Brow Blvd, and on Kenilworth Ave south of Central Ave, due to changes at south of Highway 8 and King St E, including removal of a section of Gage Ave and Ottawa St S. No significant change in passenger vehicle traffic in downtown core as these flows are not at capacity. Slight increase in passenger vehicle traffic on Burlington St and Bay St North. McMaster Institute for Transportation and Logistics Page 13

18 Figure 3: Scenario 1 (2011 Original Truck Route: Heavy Vehicle Flow, 8-9 am) Figure 4: Scenario 2 (2011 Modified Truck Route: Heavy Vehicle Flow, 8-9 am) Page 14 McMaster Institute for Transportation and Logistics

19 Figure 5: Scenario 3 (2011 Modified Truck Route with Removals: Heavy Vehicle Flow, 8-9 am) 4.2 Scenario 3 (2011 Modified Truck Route Model with Removals) vs. Scenario 2 (2011 Modified Truck Route Model): No significant change in heavy and medium commercial vehicles on Fruitland Road between Barton St and Highway 8. Increase in heavy and medium vehicle flow on King St W due to closure of Dundurn St N between King St W and York Blvd. Also, decrease in west bound flow on York Blvd as the access from Cannon St to Dundurn St S through Dundurn St N is eliminated. Diversion of commercial vehicle to Red Hill Valley Parkway due to closure of Kenilworth Access. Further decrease in heavy and medium commercial vehicles on Upper Ottawa St, south of Mountain Brow Blvd due to removal of Kenilworth Access. McMaster Institute for Transportation and Logistics Page 15

20 Figure 6: Scenario 1 (2011 Original Truck Route: Medium Vehicle Flow, 8-9 am) Figure 7: Scenario 2 (2011 Modified Truck Route: Medium Vehicle Flow, 8-9 am) Page 16 McMaster Institute for Transportation and Logistics

21 Figure 8: Scenario 3 (2011 Modified Truck Route with Removals: Medium Vehicle Flow, 8-9 am) McMaster Institute for Transportation and Logistics Page 17

22 5.0 Conclusions Conclusions The Hamilton Truck Route Study presents an analysis of the effects of modifications to the Hamilton truck route network. By utilizing travel demand modelling and forecasting techniques, it has attempted to quantify the impacts of these changes, and show the redistribution of commercial vehicle traffic in the region. The key findings of the study are as below: The removal of the section on Barton St between Wentworth St to Queen St diverts traffic from Burlington St to Barton St, east of Wentworth, and to Cannon St. Given the proximity of this section to the Industrial yards, it is expected that heavy and medium commercial vehicles will reroute for access. To this end, the removal only serves to redistribute commercial vehicle traffic. While it alleviates the removed section of Barton St, it also leads to increases in commercial vehicle flows on Queen St South, Cannon St, and Main St W. The removal of Kenilworth Access leads to a major diversion of heavy and medium commercial vehicles to Red Hill Valley Parkway. This modification serves to shift commercial vehicle traffic from arterials (Gage Ave, Ottawa St, and Kenilworth Ave N) passing through residential sections of the city. Page 18 McMaster Institute for Transportation and Logistics

23 The designation of Fruitland Road between Barton St and Highway 8 as part-time seems to have little impact on the movement of heavy and medium commercial vehicle vehicles as very little commercial vehicle activity occurs outside of the peak-hours. The closure of Dundurn St N between King St W and York Blvd has leads to increase in heavy and medium vehicle flow on King St W, and decrease in west bound flow on York Blvd as the access from Cannon St to Dundurn St S through Dundurn St N is eliminated. Overall, the modifications to the truck route network would not lead to a significant change in passenger vehicle traffic in downtown core as these flows are not at capacity. McMaster Institute for Transportation and Logistics Page 19

24 6.0 References References City of Hamilton (2010). "City of Hamilton Truck Roue Master Plan Study." Retrieved March 27, 2012, from udy.htm Page 20 McMaster Institute for Transportation and Logistics

25 7.0 Appendix Appendix Model Assigned Vehicle Hourly Flows McMaster Institute for Transportation and Logistics Page 21

26 Table A.2: Vehicle Flows: Fruitland Rd between Barton and Highway 8 Time Period Heavy 2011 Original Truck Route Model Light Total Medium 2010 Total Counted Weekday Heavy 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Medium Light Total Heavy Medium Light Total 00: : : : : : : : : : : : : : : : : : : : : : : : Total , Page 22 McMaster Institute for Transportation and Logistics

27 Table A.3: Vehicle Flows: Dundrun St S. between King and York Time Period Heavy 2011 Original Truck Route Model 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Light Total Heavy Medium Light Total Heavy Medium Light Total Medium 2010 Total Counted Weekday 00: : : : : : : : : : : : : : : : : : : : : : : : Total ,809 1, , ,774 McMaster Institute for Transportation and Logistics Page 23

28 Table A.4: Vehicle Flows: Upper Ottawa St, South of Mountain Brow Time Period Heavy 2011 Original Truck Route Model 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Light Total Heavy Medium Light Total Heavy Medium Light Total Medium 2010 Total Counted Weekday 00: : : : : : : : : : : : : : : : : : : : : : : : Total , Page 24 McMaster Institute for Transportation and Logistics

29 Table A.5: Vehicle Flows: Kenilworth Ave S, South of Central Ave Time Period Heavy 2011 Original Truck Route Model 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Light Total Heavy Medium Light Total Heavy Medium Light Total Medium 2010 Total Counted Weekday 00: : : : : : : : : : : : : : : : : : : : : : : : Total ,016 3, McMaster Institute for Transportation and Logistics Page 25

30 Table A.6: Vehicle Flows: Bay St N. between King and York WS Time Period Heavy 2011 Original Truck Route Model 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Light Total Heavy Medium Light Total Heavy Medium Light Total Medium 2010 Total Counted Weekday 00: : : : : : : : : : : : : : : : : : : : : : : : Total ,037 1, , ,428 Page 26 McMaster Institute for Transportation and Logistics

31 Table A.7: Vehicle Flows: Queen St S. between York and King St Time Period Heavy 2011 Original Truck Route Model 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Light Total Heavy Medium Light Total Heavy Medium Light Total Medium 2010 Total Counted Weekday 00: : : : : : : : : : : : : : : : : : : : : : : : Total ,671 1, , , , ,550 McMaster Institute for Transportation and Logistics Page 27

32 Table A.8: Vehicle Flows: Mountain Brow Blvd, West of Upper Ottawa St Time Period Heavy 2011 Original Truck Route Model 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Light Total Heavy Medium Light Total Heavy Medium Light Total Medium 2010 Total Counted Weekday 00: : : : : : : : : : : : : : : : : : : : : : : : Total , Page 28 McMaster Institute for Transportation and Logistics

33 Table A.9: Vehicle Flows: Red Hill Valley Parkway Time Period Heavy 2011 Original Truck Route Model Medium Light Total Heavy 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Medium Light Total Heavy Medium Light Total 00: : : : : : : : : : : : : : : : : : : : : : : : Total 882 1,100 1,039 3, ,213 1,076 3,207 1,055 1,549 1,076 3,680 McMaster Institute for Transportation and Logistics Page 29

34 Table A.10: Vehicle Flows: King St W Time Period 2011 Original Truck Route Model 2011 Modified Truck Route Model 2011 Modified Truck Route Model with Removals Heavy Medium Light Total Heavy Medium Light Total Heavy Medium Light Total 00: : : : : : : : : : : : : : : : : : : : : : : : Total , , ,522 Page 30 McMaster Institute for Transportation and Logistics

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