Commercial Vehicle Survey: Traffic and Vehicle Classification Summary

Transcription

1 TRANSPORTATION Final Report The Preparation of a Northern Ontario and Commercial Vehicle Origin-Destination Survey Commercial Vehicle Survey: Traffic and Vehicle Classification Summary Submitted to Ministry of Transportation, Ontario by IBI Group October 3, 213

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3 Table of Contents 1. Introduction Field Traffic Count Collection Equipment Selection and Installation Days of Raw Count Data Collected Count Standardization and Validation Standardization/Categorization of Vehicle Classification Data... 9 Categorization of Loop Data (Length-Based Vehicle Classification) 1 Mapping Length-Based Truck Classifications to Classification Groupings 14 Categorization of Tube Data (Axle-Based Vehicle Classification) Visual Inspection of Traffic Count Data Development of Average Weekly Traffic Profile Traffic Count Summary and Trends Geographic and Historical Trends (21 211) Summary and Conclusions Appendix A: Traffic Classification Count Inventory Appendix B: Detailed ATR/Manual/Video Counts Comparisons Appendix C: Hourly Traffic Plots for Data Collection Period Appendix D: Traffic Count Adjustments Appendix E: Average Weekly Traffic Profiles OCTOBER 3, 213 i

4 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Table of Contents (continued) List of Exhibits Exhibit 1.1: Commercial Vehicle Survey and Traffic Classification Count Locations... 2 Exhibit 2.1: Summary of Traffic Count Locations and Schedule... 5 Exhibit 3.1: Vehicle Classification Systems by Count Type... 9 Exhibit 3.2: Manual Traffic Classification Counts (3-Hour Count s) Exhibit 3.3: ATR Traffic Classification Counts vs. Manual Traffic Classification, 3-Hour s Exhibit 3.4: Vehicle Classification System Equivalencies Exhibit 4.1: Summary of Final Average Weekly Traffic Count Volumes by DCS Exhibit 4.2: Weekly Traffic Volumes and Growth Rates by DCS, Exhibit 4.3: Weekly Traffic Volumes and Growth Rates by Highway Corridor, OCTOBER 3, 213 ii

5 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY 1. Introduction The Growth Plan for Northern Ontario directs the Ministry of Transportation (MTO) to develop a Northern Ontario Multimodal Transportation Strategy. This strategy will chart a long-term course for future planning, policy, programs, and infrastructure investment opportunities. An important starting point to developing a sound strategy is having an accurate and comprehensive understanding of travel patterns and characteristics in the region. MTO has retained IBI Group to conduct OD surveys of passenger and commercial vehicles at a number of sites in Northern Ontario on the provincial highway network and at international border crossings. The survey program consists of three components: a commercial vehicle survey; a passenger vehicle survey; and traffic counts to allow for the data expansion of the surveys. This report describes the traffic classification counts related to the commercial vehicle survey (CVS) portion of the study, and includes the following: description of field traffic count collection, including equipment selection and count scheduling; description of the process of standardization of raw count data from various original vehicle classification systems into broader vehicle categories for analysis purposes, and development of weekly traffic profiles; and summaries of final traffic classification results. Other aspects of the study are documented separately, including survey design and conduct, data processing, and travel profile reports. The CVS was conducted at 37 directional Data Collection Sites (DCSs), shown in Exhibit 1.1. These include the 4 Canada-USA border crossings (8 directional sites),as well as 15 additional locations (29 directional sites). The commercial vehicle surveys took place between September 12 and November 3, 211, with 2 to 1 survey days at each location, and with survey shifts scheduled over a variety of days and time periods to capture a representative truck sample for each site. Traffic classification counts coincided with commercial vehicle survey activities to the extent possible. OCTOBER 3, 213 1

6 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 1.1: Commercial Vehicle Survey and Traffic Classification Count Locations OCTOBER 3, 213 2

7 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY IBI Group engaged Traffic Survey Analysis (TSA) to perform vehicle counts and classifications at each survey site with analysis of counts and classifications, and expansion of data conducted by IBI Group. The goal for the traffic data collection was to conduct two weeks of vehicle classification counts, aggregated to half-hour intervals, at each survey site, to provide a basis for developing a reliable one-week profile of typical traffic conditions at each site. Traffic counts were conducted at each site using Automatic Traffic Recorders (ATRs) appropriate to site conditions and validated by 5 hours of video footage and 3 hours of manual classification counts within the ATR data collection period. A key aspect of the analysis of the traffic count data for this study was to develop a customized methodology to account for large passenger vehicles automobiles/pick-up trucks with trailers, and recreational vehicles which are especially prevalent in Northern Ontario compared to Southern Ontario, at about 7 % of total passenger vehicles. Any automatic traffic count technology tends to have difficulty correctly classifying such vehicles, as they appear very similar to straight trucks or small commercial trucks with trailers, but are used for very different purposes. The state-of-practice in analysis of traffic classification count data typically does not include any particular accounting of these types of passenger vehicles, and typically they remain in large part mixed in with commercial vehicles in the final datasets. Development of this customized methodology, explained in Chapter 3, helps ensure that the resulting count data are reliable for analysis of traffic and travel in Northern Ontario. OCTOBER 3, 213 3

8 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY 2. Field Traffic Count Collection This section describes the count equipment used for the traffic data collection in the field, and summarizes the dates of raw traffic classification count data collection at each site. A summary of the count technology, count location coordinates, and the dates and the duration of usable traffic count data at each commercial vehicle DCS is provided in Exhibit 2.1. A detailed traffic count inventory, showing the dates and duration of automatic, manual, and video counts per day is included in Appendix A. 2.1 Equipment Selection and Installation Three types of ATRs were considered for this study, as follows: Permanent loop detectors: Induction loop detector hardware is permanently installed in the road pavement surface at numerous locations throughout the provincial road network. Where the loops are suitably located in relation to the survey sites, and the loop hardware is good maintenance and is functional, recording equipment can be plugged into the loops to collect length-based vehicle classification data. This method for collecting classification count data was used where possible, especially for high-speed roadway locations. Nu-Metric counters: These flat, portable units can be temporarily installed on top of the roadway surface and also classify vehicles based on length. For the 26 CVS, MTO found Nu-Metric counters produced more reliable traffic counts than tubes (discussed below). Nu-Metric counters have disadvantages including safety (because they have a raised profile, they can be dangerous for motorcyclists), low durability (given the high cost of the equipment, this can make their use quite costly), and the need for more elaborate and costly traffic control to install, monitor, and remove the equipment safely on high-speed roadways. Each counter must also be properly calibrated to ensure that vehicles are classified correctly. Pneumatic Tube Counters: TSA has had very good experience with tube pneumatic road tube counters, when configured and installed correctly, with two tubes dedicated to each lane of traffic. Tube counters are able to provide vehicle classification that takes into account the number and spacing of vehicle axles and can classify into the standard FHWA thirteen-category system. Tube counters cannot be used on high-speed roadways (9 km or greater), as the tube equipment cannot withstand the wear and tear. They can also be damaged by heavy construction equipment and snowploughs. OCTOBER 3, 213 4

9 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 2.1: Summary of Traffic Count Locations and Schedule Data Collection Site Hwy Count Type Latitude Longitude Start Date End Date Days of Usable Counts Border Crossings ON12 Fort Frances Northbound Sept. 23 Oct Tube ON121 Fort Frances Southbound Sept. 23 Oct ON153 Pigeon River Northbound Loop Sept. 2 Oct. 3 ON154 Pigeon River Southbound 14 ON155 Rainy River Eastbound Tube Sept. 22 Oct. 5 ON156 Rainy River Westbound 14 ON279 Sault Ste. Marie Southbound 14 17B Tube Sept. 19 Oct. 2 ON28 Sault Ste. Marie Northbound 8.2 Other Sites ON14 Cochrane Eastbound Tube Sept. 13 Sept. 27 ON15 Cochrane Westbound 14 ON117 Dryden Eastbound Loop Sept. 22 Oct. 5 ON118 Dryden Westbound 13.1 ON132 Hearst Eastbound 7 11 Loop Sept. 29 Oct. 6 ON133 Hearst Westbound 7 ON134 Heyden Northbound Loop Sept. 8 Sept. 21 ON135 Heyden Southbound 14 ON14 Kirkland Lake Eastbound Tube Sept. 13 Sept. 26 ON141 Kirkland Lake Westbound 14 ON144 New Liskeard Northbound Loop Sept. 13 Sept. 26 ON145 New Liskeard Southbound 14 ON146 North Bay Westbound 17 Loop Sept. 12 Sept ON147 Northshore Eastbound Tube Sept. 8 Sept. 21 ON148 Northshore Westbound 14 ON15 Parry Sound Northbound Loop Sept. 23 Oct. 7 ON151 Parry Sound Southbound ON157 Red Rock Eastbound* 11& 14 Loop Sept. 2 Oct. 3 ON158 Red Rock Westbound* ON157 Red Rock Eastbound* 11& 14 Tube Sept. 2 Oct. 3 ON158 Red Rock Westbound* ON159 ON26 Rush Bay Eastbound Loop Sept. 22 Oct. 5 Rush Bay Westbound 14 ON262 nder Bay Hwy 12 EB Loop Sept. 2 Oct. 3 ON263 nder Bay Hwy 12 WB 14 ON264 nder Bay Hwy 11/17 EB 11& 14 Loop Sept. 2 Oct. 3 ON265 nder Bay Hwy 11/17 WB ON271 Wasi Northbound 27 adj.** 27 adj.** n/a 11 Loop ON272 Wasi Southbound** Oct. 23,212 Nov. 5, ON6 Timmins Eastbound Loop Sept. 13 Sept. 26 ON61 Timmins Westbound 14 Notes: * Counts at Red Rock were conducted both by loop and tube counters to allow for comparison between technologies. ** Traffic classification counts had been conducted in 211 for the Wasi DCS, but these were far south of the survey station due to nonfunctioning loops closer to the DCS. Southbound counts were repeated closer to the DCS in fall 212; northbound loops were not functioning at this time; northbound counts were synthesized by adjusting northbound counts from the previous CVS, conducted in April 27. OCTOBER 3, 213 5

10 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Where loop detectors hardware was not available or not well situated relative to the survey site, pneumatic tubes were used for counts, where feasible. The traffic counters and classifiers used were Diamond Unicorn classifiers, which are able to plug into either permanent loop detectors or pneumatic road tube input. Data can then be directly downloaded to computer. Each classifier is capable of recording up to four lanes of data, and able to classify traffic using road tube, piezo, and/or loop presence sensors. In consultation with MTO, it was decided to conduct a comparison of count technologies by installing all three technologies simultaneously at one of the locations, Red Rock on Highway 11 & 17 east of nder Bay. However, due to water damage to the Nu-Metric counters caused by rain during the count period, the count data could not be extracted from the Nu-Metric counters. Traffic control and road safety precautions based on OTM Book 7 were followed to ensure the safety of the traffic count survey crews during the installation and monitoring of the count equipment and/or counters. Installation of equipment included the following: At permanent loop detector sites, the traffic recording equipment was plugged into the roadside connections immediately beside each set of loops; and At sites where pneumatic tube counters were used, a straight, flat section of roadway in the vicinity of the survey was first identified for optimum performance of the tube counter, and also for the safety of the crew during installation and removal of the counter. Hilly locations were avoided to prevent the tubes from rolling or being pulled as vehicles passed over them. Immediately prior to installation, the tubes were checked for general condition and to ensure they were free of debris. End plugs were inserted into the end not plugged into the traffic recorder. The tubes were then laid across the roadway and the tubes were nailed to the pavement. 2.2 Days of Raw Count Data Collected Traffic counts were generally conducted between mid-september and early October. To represent typical weekly patterns, surveys and counts were not conducted during holiday weekends (Labour Day, Thanksgiving). The goal for traffic data collection was to collect a full two weeks of raw traffic counts at each location, although a minimum of 7 days of counts can provide sufficient data for the development of a reliable one-week traffic count profile. The number of days of counts collected at each site was shown in Exhibit 2.1. A total of 6 directional sites had less than 14 days of data collected, but still had sufficient data to develop a reliable weekly traffic profile for each site: Dryden Eastbound (ON117) and Westbound (ON118): Traffic counts at these sites were less than one day shy of 14 days; OCTOBER 3, 213 6

11 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Fort Frances Northbound (ON12): Traffic counts were collected for 9.5 days; after which time the counter stopped functioning due to battery issues; Sault Ste. Marie Bridge Northbound (ON28): Tube counters installed at this site appear to have been damaged by heavy construction vehicles. Counters were reinstalled twice at this site, resulting in a total of 8.2 days of raw counts; Hearst Eastbound (ON132) and Westbound (ON133): Due to logistical considerations in reaching the Hearst DCS, the most remote of the sites, traffic counts were only recorded for a period of 7 days; and Wasi Northbound (ON271): Counts for the Wasi DCSs were originally conducted in fall 211 at a location significantly south of the actual survey location. Counts were repeated in fall 212 and summer 212 in support of passenger vehicle survey work. The northbound loops were not functioning at this time, and northbound counts were therefore synthesized from available sources, including counts conducted for Wasi northbound for the 26 CVS. Shorter data collection periods typically were due to damage to the tube count equipment when installed in the field, or due to counter battery issues. OCTOBER 3, 213 7

12 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY 3. Count Standardization and Validation The raw vehicle classification data have differing native classification systems, as shown in Exhibit 3.1. To standardize and analyse the classification count data, the raw data were categorized into the following broader groupings: (PV): this includes autos and light-duty vehicles including those with trailers, motorcycles and recreational vehicles; Buses: these are kept separate from other passenger vehicles in analysis; (SU); and (MU) (straight trucks with trailers or transport truck combinations). The process of categorizing the raw classification count data involved developing a good understanding of how large passenger vehicles in the traffic mix were picked up by the count equipment. This was made possible through the manual count data that were taken concurrently with 3 hours of the ATR data. After categorizing the counts into standard groupings that account for the large passenger vehicles, the validation and standardization process also included the following steps: The two-week counts were plotted to identify and exclude anomalous data, e.g. unusually low volumes that may be due to temporary traffic incidents; Other site-specific adjustments were made to the data as needed; and Only representative count data were carried forward to develop a one-week profile of traffic data. OCTOBER 3, 213 8

13 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 3.1: Vehicle Classification Systems by Count Type Manual Counts 1. Autos, small passenger and cargo vans( 2 axle, 4 tire), SUVs, pick-up trucks 2. Vans and pick-up trucks with trailers 3. Recreational 4. Buses 5. Small Straight Truck (cargo vans with 2 axles and 6 wheels) 6. Medium Straight (3 axles) 7. Large Straight (4 axles or more) 8. Straight Truck and Trailer ( other than the vehicles identified in Group 2) 9. Tractor Only (power unit of the tractor-trailer) 1. Tractor and Trailer 11. Tractor and 2Trailers. 12. Motorcycles Loop Counts ATR (Length-Based) Bin 1: 6.49 m cars (5.5 m on average), pick-ups, vans, SUVs, motorcycles Bin 2: m truck tractors, straight trucks, cars and pick-ups pulling trailers, recreational vehicles (RVs), school buses, city buses Bin 3: m most trucks or tractors with 1 trailer; intercity buses Bin 4: m a small proportion of tractor plus one trailer (esp. floats, car carriers),; some truck tractors with 2 trailers Bin 5: greater than 23.1 m truck tractors with 2+ trailers Tube Counts ATR (Axle-Based) 1. Motorcycles 2. cars (with or without one or two-axle trailer) 3. Two axle, four tire vehicles (with or without one or two-axle trailer) 4. Buses 5. Two axle, six tire single unit 6. Three axle single unit 7. Four or more axle single unit 8. Three or four axle single-trailer 9. Five axle single-trailer 1. Six or more axle single-trailer 11. Five or fewer axle multi-trailer 12. Six axle multi-trailer 13. Seven or more axle vehicles 3.1 Standardization/Categorization of Vehicle Classification Data Only manual classification of vehicles can reliably identify large passenger vehicles in the traffic mix, as ATR counts tend to identify these as trucks, i.e. for commercial purposes, which have very different travel patterns from passenger vehicles. Analysis of the manual classification counts conducted during a portion of the ATR classification counts was key to developing the method of categorizing the raw ATR data into broader groupings of passenger vehicle, bus, single-unit truck, and multi-unit truck. The process used for grouping the detailed original vehicle classification systems to the standardized analysis categories is described in the subsections below. A summary of the 3-hour manual classification counts is included as Exhibit 3.2, and includes the ratios of large passenger vehicles RVs and automobiles/pickups with trailers to straight automobiles/pick-ups without trailers; these ratios are used in categorizing length-based classification data, described below. More detailed manual/video/atr comparisons are included in Appendix B, including counts by half-hour interval. Manual and video counts were conducted at all DCSs with the exception of the Sault Ste. Marie border due to security concerns of the Canadian Border Services Agency. At each DCS, three hours of manual classification counts were conducted on a sday, nesday or rsday, and where possible OCTOBER 3, 213 9

14 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY during the hours of 1: a.m. and 4: p.m. Five hours of continuous video was also recorded that included the 3 hours counted manually. ATR counts for the 3-hour period corresponding to the manual counts are summarized and compared to the manual classification count totals in Exhibit 3.3, separately for loop count and tube count stations. Categorization of Loop Data (Length-Based Vehicle Classification) In the loop classification data, large passenger vehicles tend to be classified together with straight trucks in Length Bin 2 (6.5 to m). Proportions of large passenger vehicles vs. commercial vehicles in Bin 2 vary by location, by time of day and day of week. One method to separate the large passenger vehicles in Bin 2 from commercial vehicles is to assume them to be a constant proportion of Bin 2. However, this overestimates truck volumes on weekends, when there are more passenger vehicles relative to fewer commercial vehicles. Therefore, rather than assuming constant proportions of passenger vehicles vs. commercial vehicles in Bin 2, volumes of large passenger vehicles are assumed to be proportional to volumes of automobiles and light-duty vehicles (small passenger vehicles) in Bin 1. The method developed to categorize length-based traffic volumes so that the larger passenger vehicles are accounted for is as follows: Estimate large passenger vehicle and bus volumes based on Bin 1 volumes, even though these vehicles are actually in length Bin 2, using the ratios to Bin 1 volumes shown in Exhibit 3.2. Rather than using the precise proportion of larger passenger vehicles to straight autos for every site, which implies a false level of precision given the random variation in the relatively small sample size, general proportions indicative of a number of sites are used: Cars with trailers and RVs as a proportion of straight auto volumes: 4%, 6.6% or 9%, with lower proportions closer to urban areas and higher proportions in more remote areas; and Buses as a proportion of straight autos: to 1% per site, based on observed buses in the manual counts. Single-unit trucks are represented by Bin 2, subtracting the estimate of cars with trailers and RVs from the total. Multi-unit trucks are represented by the sum of Bins 3, 4 and 5, subtracting the estimate of buses from the total. OCTOBER 3, 213 1

15 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 3.2: Manual Traffic Classification Counts (3-Hour Count s) Location Manual Count Classification Single Multi- Auto Auto with -Unit Unit Auto Trailers and RVS as Buses as Cycle Only Trailer RV Buses % Autos-Only % Autos-Only Type (12) (1) (2) (3) (4) (5,6,7,9) (8,1,11) Veh. Observed Used Observed Used Border Crossings ON12 Fort Frances NB Tube ON121 Fort Frances SB ON153 Pigeon River Border NB Loop ON154 Pigeon River Border SB ON155 Rainy River Border EB Tube ON156 Rainy River Border WB Other Sites ON14 Cochrane EB Tube ON15 Cochrane WB ON117 Dryden EB Loop ON118 Dryden WB ON132 Hearst EB Loop ON133 Hearst WB ON134 Heyden NB Loop ON135 Heyden SB ON14 Kirkland Lake EB Tube ON141 Kirkland Lake WB ON144 New Liskeard NB Loop ON145 New Liskeard SB ON146 North Bay WB Loop 4 1, , , ON147 Northshore EB Tube ON148 Northshore WB ON15 Parry Sound NB * Loop ON151 Parry Sound SB , ON157 Red Rock EB Both ON158 Red Rock WB ON159 Rush Bay EB Loop ON26 Rush Bay WB ON262 nder Bay Hwy 12 EB Loop ON263 nder Bay Hwy 12 WB ON264 nder Bay Hwy 11/17 EB Loop ON265 nder Bay Hwy 11/17 WB ON271 Wasi NB (212) Synth , ON272 Wasi NB (212) Loop , ON6 Timmins EB Loop ON61 Timmins WB All Sites 19 12, , ,55 15, Notes: * Parry Sound Northbound manual counts seem to have been conducted at the wrong location and are not included. OCTOBER 3,

16 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 3.3: ATR Traffic Classification Counts vs. Manual Traffic Classification, 3-Hour s A. Loop Counts (Length-Based) Length Bin Counts Classification Groupings Comparison with Manual Classification from Length Bin Counts Difference Ratio > Location 6.49m 12.49m 21.9m 23.m 23.m PV SU MU Bus PV SU MU * PV SU MU * Border Crossings ON153 Pigeon River Border Northbound ON154 Pigeon River Border Southbound Other Sites ON117 Dryden Eastbound ON118 Dryden Westbound ON132 Hearst Eastbound ON133 Hearst Westbound ON134 Heyden Northbound ON135 Heyden Southbound ON144 New Liskeard Northbound ON145 New Liskeard Southbound ON146 North Bay Westbound 1, ,598 1, , ON151 Parry Sound Southbound , , ON157 Red Rock Eastbound ON158 Red Rock Westbound ON159 Rush Bay Eastbound ON26 Rush Bay Westbound ON262 nder Bay Hwy. 12 EB ON263 nder Bay Hwy. 12 WB ON264 nder Bay Hwy. 11/17 EB ON265 nder Bay Hwy. 11/17 WB ON6 Timmins Eastbound ON61 Timmins Westbound ON272 Wasi Southbound (212) , , All Sites 1, , , Notes: * also includes Buses OCTOBER 3,

17 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 3.3: ATR Traffic Classification Counts vs. Manual Traffic Classification, 3-Hour s (continued) B. Tube Counts (Axle-Based) Classification Groupings Comparison with Manual Classification Axle-Based Counts (FHWA Classes)* from Axle-Based Counts Difference Ratio Location 1,2,3 4 5,6,7 8 9,1,11,12 13 PV SU MU Bus PV SU MU * PV SU MU ** Border Crossings ON12 Fort Frances Northbound ON121 Fort Frances Southbound ON155 Rainy River Border EB ON156 Rainy River Border WB Other Sites ON14 Cochrane Eastbound ON15 Cochrane Westbound ON14 Kirkland Lake Eastbound ON141 Kirkland Lake Westbound ON147 Northshore Eastbound ON148 Northshore Westbound ON157 Red Rock Eastbound ON158 Red Rock Westbound All Sites 3, , Note: * Descriptions of detailed classes are included in Exhibit 3.1. ** also includes Buses. OCTOBER 3,

18 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Mapping Length-Based Truck Classifications to Classification Groupings For length-based classification counts, Length Bin 2, 6.5 to m, captures a variety of both commercial vehicles and larger passenger vehicles, and proportions of each can vary by the general vehicle mix at each location, as well as by time of day and day of week. The method developed to mapping traffic volumes into the broader vehicle classifications so that the larger passenger vehicles are accounted for is as follows: Estimate RVs, car with trailers and bus volumes: while these vehicles are in length Bin 2, the volumes of these types of vehicles is estimated based on the volume of straight cars, i.e. Bin 1; the proportion of these types of vehicles compared to straight cars was included in Exhibit 3.2. Rather than using the precise proportion of larger passenger vehicles to straight autos for every site, which implies a false level of precision given the random variation in the relatively small sample size, general proportions indicative of a number of sites are used: Cars with trailers and RVs as a proportion of straight auto volumes: generally 1.8% to 9%, with lower proportions closer to urban areas and higher proportions in more remote areas. Hearst (and Cochrane) have a significantly higher proportion of large passenger vehicles westbound; generally these are pick-up trucks with trailers carrying various equipment. For Hearst westbound 3% large passenger vehicle volumes relative to straight autos is used (a lower proportion of 6.6% eastbound). Buses as a proportion of straight autos: to 1% per site, based on observed buses in the manual counts. Single-unit trucks are represented by Bin 2, subtracting the estimate of cars with trailers and RVs from the total. Multi-unit trucks are represented by the sum of Bins 3, 4 and 5, subtracting the estimate of buses from the total. Categorization of Tube Data (Axle-Based Vehicle Classification) Tube count classification is based on the number and spacing of axles, and therefore can identify at least a portion of the automobiles/pick-ups with trailers and include them in Class 2 or 3 (automobile or light truck with or without trailer). (See full list of axle-based vehicle classes in Exhibit 3.1.) However, at least a portion of large passenger vehicles tend to be classified with trucks in the raw tube count data. Two axle-based classifications tend to contain more than one vehicle category, and are dealt with as follows: Class 8 (three-or four-axle single-trailer trucks); Class 8 tends to contain true multi-unit trucks, as well single-unit trucks with similar OCTOBER 3,

19 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY axle spacing, plus automobiles with trailers. Class 8 vehicles are the least common truck types among single-unit trucks and multiunit trucks. The volume of vehicles classified as Class 8 representing more than one-third the total volume of Class 5, 6, and 7 vehicles (other single-unit trucks) plus one-third the total volume of Class 9 and 1 vehicles, (other multi-unit single-trailer trucks), are assumed to be large passenger vehicles. Class 13 (seven or more axle multi-trailer vehicles): Large multitrailer vehicles are not very common among multi-unit trucks. The volume of Class 13 vehicles more than 12% relative to the total volume of Classes 11 and 12 vehicles (other multi-unit multi-trailer trucks) is taken to be misclassified automobiles spaced closely together, and multiplied by 3 to estimate total automobiles. The categorization of axle-based vehicle classes can be represented as follows: (PV) = Class 1 + Class 2 + Class 3 + remainder of Class 8 after allocation to trucks + remainder of Class 13 after allocation to trucks x 3 (i.e. misclassification of closely-spaced cars) Bus = Class 4 (SU) = Class 5 + Class 6 + Class 7 + up to 33% additional trucks from Class 8 (MU) (one-trailer) = Class 9 + Class 1 + up to 33% additional trucks from Class 8 (MU) (multi-trailer) = Class 11 + Class 12 + up to 12% additional trucks from Class 13 The methods for mapping the raw data from the original vehicle classifications into broader vehicle classification groupings are summarized in Exhibit 3.4. After mapping/grouping of ATR vehicle classifications to broader standardized vehicle groupings as described above, the results compare well to manual count totals, as was seen in Exhibit 3.3, and support the reliability of the traffic count data for purposes of the Northern Ontario survey data expansion and analysis. At the Red Rock DCS, where both tube and loop equipment was used to provide a comparison between the two count methodologies. While both types of counters worked well, the tube counts were carried forward for further analysis and for data expansion, due to a slightly better validation against manual counts after vehicle categorization. OCTOBER 3,

20 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 3.4: Vehicle Classification System Equivalencies Source (Native Classification) Survey Analysis Classification System Vehicle Truck Truck Buses Manual/Video Counts 1. Autos, small passenger and cargo vans( 2 axle, 4 tire), SUVs, pick-up trucks 2. Vans and pick-up trucks with trailers 3. Recreational 5. Small Straight Truck (cargo vans with 2 axles and 6 wheels) 6. Medium Straight (3 axles) 7. Large Straight (4 axles or more) 8. Straight and Trailer 1. Tractor and Trailer 11. Tractor and 2 Trailers. 4. Buses 12. Motorcycles 9. Tractor Only (power unit of the tractortrailer) Loop Detectors (Length Bins) Bin 1: 6.49 m (includes motorcycles, cars and light-duty trucks/ vans without trailers) Car with Trailer + RV estimate: 1.3% to 2.5% of Bin 1, subtracted from Bins 2-4 (% in Exhibit 3.2) Bin 2: m Less Car with Trailer + RV estimate Bin 3: m Bin 4: m Bin 5: other greater than 23.1 m Less Bus estimate.1% to.5% of Bin 1, subtracted from Bin 3 (% in (% in Exhibit 3.2). Tube Counters (FHWA Scheme F) 1. Motorcycles 2. cars 3. Two axle, four tire vehicles + Remainder of: 8. Three or four axle single-trailer after allocation to singleunit and multi-unit trucks 5. Two axle, six tire single unit 6. Three axle single unit 7. Four or more axle single unit + up to 33% additional trucks from 8. Three or four axle single-trailer 9. Five axle single-trailer 1. Six or more axle singletrailer + up to 33% additional single-trailer trucks from 8. Three or four axle single-trailer after allocation to singleunit trucks 11. Five or fewer axle multitrailer 4. Buses + Remainder of: 13. Seven or more axle multi-trailer x 3 after allocation to multitrailer trucks 12. Six axle multi-trailer + up to 12% (25% for Red Rock) additional multitrailer trucks from 13. Seven or more axle multi-trailer OCTOBER 3,

21 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY 3.2 Visual Inspection of Traffic Count Data For each DCS, plots of hourly traffic volumes for the count duration were prepared by vehicle class: passenger vehicle, single-unit truck, and multi-unit truck, and total vehicles. These plots are included as Appendix C. The plots allow a visual check of the data to ensure that daily volume patterns were realistic - e.g. weekday morning commuting peaks in one direction balanced by afternoon commuting peaks in the opposite direction. The plots also allow anomalies in the data to be identified, e.g. to traffic incidents or count equipment malfunction or irregularities. Anomalies were flagged and excluded from developing the average weekly profiles so that the weekly profiles would be based on typical conditions only. Classification count data at certain locations required adjustments so that the data would more accurately reflect conditions at the count location. These adjustments are described in Appendix D, and include the following locations: Hearst eastbound (ON132) and westbound (ON133); Kirkland Lake eastbound (ON14) and westbound (ON141); Parry Sound northbound (ON15); Sault Ste. Marie Bridge to Canada (ON28) and to USA (ON279); Timmins eastbound (ON6) and westbound (ON61); Wasi northbound (ON271). 3.3 Development of Average Weekly Traffic Profile All available data that seem to represent typical traffic conditions were carried forward toward developing weekly traffic profile for each DCS using the average of each day-of-week and half-hour of the day. The formula used to obtain the average traffic profile by vehicle category can be represented as follows: where: i: Day of the week i (1 to 7) j: Half-hour of day j ( to 23) V ij : Volume for vehicle category in day i in half-hour j N ij : Number of records for day i in half-hour j. OCTOBER 3,

22 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY 4. Traffic Count Summary and Trends A detailed weekly traffic profile is provided for each DCS in Appendix E, including hourly plots of traffic counts and daily summary statistics by vehicle type. Final average weekly volumes by vehicle category for each DCS are summarized in Exhibit 4.1. Exhibit 4.1: Summary of Final Average Weekly Traffic Count Volumes by DCS Average Weekly Volumes Data Collection Site Type Pass. Vehicle Single- Unit Truck Truck * % Border Crossings ON12 Fort Frances NB Tube 7, , ON121 Fort Frances SB 8, , ON153 Pigeon River NB Loop 5, , ON154 Pigeon River SB 5, , ON155 Rainy River EB Tube 3, , ON156 Rainy River WB 3, , ON28 ON279 Sault Ste. Marie NB Tube 19, , Sault Ste. Marie SB 18, , Other Sites ON14 Cochrane EB Tube 6, ,876 2,329 8, ON15 Cochrane WB 6, ,494 3,79 9, ON117 Dryden EB Loop 18, ,32 4,233 22, ON118 Dryden WB 18, ,414 5,322 24, ON132 Hearst EB Loop 7, ,844 2,833 1, ON133 Hearst WB 8,16 1,118 2,39 3,427 11, ON134 Heyden NB Loop 12, ,412 3,155 15, ON135 Heyden SB 12, ,794 2,48 15, ON14 Kirkland Lake EB Tube 8, , ON141 Kirkland Lake WB 8, , ON144 New Liskeard NB Loop 17, ,36 4,228 22, ON145 New Liskeard SB 17, ,648 3,354 21, ON146 North Bay WB Loop 51,947 1,83 1,669 2,752 54, ON147 Northshore EB Tube 11, ,184 2,744 14, ON148 Northshore WB 12, ,374 3,956 16, ON15 Parry Sound NB Loop 44,793 1,143 4,641 5,783 5, ON151 Parry Sound SB 41,856 1,562 3,567 5,128 47, ON157 Red Rock EB Tube 12, ,48 3,843 16, ON158 Red Rock WB 12, ,617 5,288 17, ON159 Rush Bay EB Loop 11, ,843 4,396 15, ON26 Rush Bay WB 11, ,845 5,433 16, ON262 nder Bay Hwy 12 EB Loop 11, ,219 2,823 14, ON263 nder Bay Hwy 12 WB 11, ,376 3,948 15, ON264 nder Bay Hwy 11/17 EB Loop 18, ,443 2,392 21, ON265 nder Bay Hwy 11/17 WB 18,449 1,195 1,853 3,47 21, ON271 Wasi NB (212) Loop 29,799 1,164 4,55 5,714 35, ON272 Wasi NB (212) 29,738 1,216 3,749 4,965 34, ON6 Timmins EB Loop 7, ,324 8, ON61 Timmins WB 6, ,339 8, Note: * also includes Buses. OCTOBER 3,

23 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY At each location, weekly volumes by vehicle category are roughly balanced by direction. The exception is multi-unit truck volumes, with several hundred to a thousand or more heavy trucks travelling northbound/westbound through Northern Ontario between Southern Ontario and Manitoba weekly than eastbound/southbound, or roughly 25 to 5% more northbound/westbound multi-unit trucks per location. This can be seen at all locations except the Timmins DCSs on Highway 11 and the Kirkland Lake DCSs on Highway 66. This coincides with the opposite trend observed at several provincial highway locations in Southern Ontario (from counts conducted for the MTO Waterloo- Wellington-Brant Vehicle Survey), where there are more multi-unit trucks eastbound than westbound. A likely explanation for this imbalance is that long-distance trucks drive from Southern Ontario and Eastern Canada to Western Canada through Northern Ontario when loaded with goods, then return to Southern Ontario via the United States when empty. The route through the United States is shorter but involves two international border crossings, and there are fewer potential issues and delays when crossing the border with an empty truck than with a loaded one. Fuel costs are also lower in the United States compared to Canada. 4.1 Geographic and Historical Trends Of the 37 DCS surveyed in Northern Ontario in 211, 28 were also surveyed in 26; and 23 were also surveyed in 21 as part of the Ontario CVS program. The 21, 26, and 211 volumes by year and percentage growth for these sites are shown in Exhibit 4.2. The same information is shown in Exhibit 4.3 for survey locations along Highway 11 and Highway 17 listed in order from west to east, to facilitate identifying trends along these key corridors that span the region. The 211 counts were conducted in September/ October 211, while the 26 counts for the same stations were conducted between April and July 27 (Provincial Commercial Vehicle Travel Profile Reference Report, March 21). As such, a portion of the historic variation in volumes, especially passenger vehicle volumes, may be due to seasonal effects. The 211 counts were more thoroughly validated than 26, as manual and video classification counts could be used for validation of 211 counts, which was not the case for 26. A portion of the variation between 26 and 211 may therefore also be due to differences in accuracy of count data between years. The directional imbalance in multi-unit trucks that was noted above for 211, with more multi-unit trucks northbound/westbound through Northern Ontario between Southern Ontario and Manitoba, can be seen in the 26 counts, but the directional differences are less pronounced. Truck volumes in 21 are very closely balanced by direction. The 5-year trend at most provincial highway locations has been a decrease in passenger-vehicle volumes of about 5% or more, with the exception of the most south-easterly locations (North Bay 62% increase, Wasi 4% increase, and Parry Sound - steady). Conversely, at Northern Ontario border crossings, passenger vehicle volumes increased from 26 levels. OCTOBER 3,

24 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 4.2: Weekly Traffic Volumes and Growth Rates by DCS, Average Weekly Volumes 26 Average Weekly Volumes 211 Average Weekly Volumes Growth (%) Growth (%) DCS Pass. SU MU Pass. SU MU Pass. SU MU Pass. Pass. DCS Name Dir Code Hwy Veh. Truck Truck Truck Veh. Truck Truck Truck Veh. Truck Truck Truck Veh. Truck Veh. Truck Border Crossings Fort Frances NB ON , , SB ON , , Pigeon River NB ON153 4,72 1 1,436 1,437 6,157 4, ,631 5, , Border SB ON154 4,842-1,383 1,383 6,225 4, ,52 5, , Rainy River EB ON , , WB ON , , Sault Ste. NB ON28 18, ,223 1,323 19,867 16, ,175 1,271 17,799 19, , B Marie SB ON279 18, ,64 1,128 19,838 16, ,22 1,83 17,76 18, , Other Sites Cochrane EB ON14 9, ,978 2,214 11,462 7, ,466 1,82 9,545 6, ,876 2,329 8, WB ON15 9, ,966 2,222 11,467 7, ,766 2,218 1,34 6, ,494 3,79 9, Dryden EB ON117 18, ,741 4,139 23,19 22,997 1,17 3,424 4,441 27,438 18, ,32 4,233 22, WB ON118 18, ,761 4,164 23,16 24,899 1,292 3,462 4,754 29,653 18, ,414 5,322 24, Hearst EB ON132 15, ,771 2,49 17,589 12, ,567 2,5 14,89 7, ,844 2,833 1, WB ON133 15, ,786 2,68 17,584 13, ,871 2,441 15,596 8,16 1,118 2,39 3,427 11, Heyden NB ON134 1, ,376 1,534 11,999 25, ,512 3,293 28,944 12, ,412 3,155 15, SB ON135 1, ,371 1,496 11,991 25, ,982 2,792 28,13 12, ,794 2,48 15, Kirkland EB ON , , Lake WB ON , ,897 8, , New NB ON144 19, ,319 3,761 23,542 18, ,669 3,212 22,194 17, ,36 4,228 22, Liskeard SB ON145 19, ,356 3,81 23,538 19, ,293 2,833 22,328 17, ,648 3,354 21, North Bay WB ON , ,76 3,546 27,92 32, ,673 2,533 34,592 51,947 1,83 1,669 2,752 54, Northshore EB ON147 11, ,195 3,62 14,971 12, ,982 3,74 16,49 11, ,184 2,744 14, WB ON148 11, ,174 3,571 14,968 13, ,58 4,291 17,631 12, ,374 3,956 16, Parry Sound NB ON ,155 1,617 4,56 6,177 49,332 44,793 1,143 4,641 5,783 5, SB ON ,727 1,464 3,996 5,46 5,186 41,856 1,562 3,567 5,128 47, Red Rock EB ON , ,943 3,279 14,615 13, ,528 4,462 17,891 12, ,48 3,843 16, WB ON158 &17 11, ,936 3,238 14,62 13, ,136 5,125 19,39 12, ,617 5,288 17, Rush Bay EB ON , ,55 4,422 17,429 11, ,843 4,396 15, WB ON , ,13 4,868 18,3 11, ,845 5,433 16, nder Bay EB ON262 67, ,446 4,37 71,39 31,561 1,556 1,843 3,399 34,959 11, ,219 2,823 14, Highway 12 WB ON263 67, ,421 3,995 71,317 25, ,313 3,37 29,182 11, ,376 3,948 15, nder Bay EB ON , ,443 2,392 21, Hwy 11/17 WB ON265 & ,449 1,195 1,853 3,47 21, Wasi (212) NB ON271 25, ,94 3,494 29,137 28, ,968 3,685 32,217 29,799 1,164 4,55 5,714 35, SB ON272 25, ,919 3,59 29,144 28, ,748 3,573 32,21 29,738 1,216 3,749 4,965 34, Timmins EB ON , ,324 8, WB ON , ,339 8, OCTOBER 3, 213 2

25 IBI GROUP FINAL REPORT: COMMERCIAL VEHICLE SURVEY: TRAFFIC AND VEHICLE CLASSIFICATION SUMMARY Exhibit 4.3: Weekly Traffic Volumes and Growth Rates by Highway Corridor, Average Weekly Volumes 26 Average Weekly Volumes 211 Average Weekly Volumes Growth (%) Growth (%) DCS Pass. SU MU Pass. SU MU Pass. SU MU Pass. Pass. DCS Name Dir Code Hwy Veh. Truck Truck Truck Veh. Truck Truck Truck Veh. Truck Truck Truck Veh. Truck Veh. Truck Highway 11, West to East Rainy River EB ON , , WB ON , , nder Bay EB ON , ,443 2,392 21, Hwy 11/17 WB ON265 & ,449 1,195 1,853 3,47 21, Red Rock EB ON , ,943 3,279 14,615 13, ,528 4,462 17,891 12, ,48 3,843 16, WB ON158 &17 11, ,936 3,238 14,62 13, ,136 5,125 19,39 12, ,617 5,288 17, Hearst EB ON132 15, ,771 2,49 17,589 12, ,567 2,5 14,89 7, ,844 2,833 1, WB ON133 15, ,786 2,68 17,584 13, ,871 2,441 15,596 8,16 1,118 2,39 3,427 11, Cochrane EB ON14 9, ,978 2,214 11,462 7, ,466 1,82 9,545 6, ,876 2,329 8, WB ON15 9, ,966 2,222 11,467 7, ,766 2,218 1,34 6, ,494 3,79 9, New NB ON144 19, ,319 3,761 23,542 18, ,669 3,212 22,194 17, ,36 4,228 22, Liskeard SB ON145 19, ,356 3,81 23,538 19, ,293 2,833 22,328 17, ,648 3,354 21, Wasi (212) NB ON , ,94 3,494 29,137 28, ,968 3,685 32,217 29,799 1,164 4,55 5,714 35, SB ON272 25, ,919 3,59 29,144 28, ,748 3,573 32,21 29,738 1,216 3,749 4,965 34, Highway 17, West to East ON-MB EB , ,515 3,748 15, border* WB , ,576 4,852 16, Rush Bay EB ON , ,55 4,422 17,429 11, ,843 4,396 15, WB ON , ,13 4,868 18,3 11, ,845 5,433 16, Dryden EB ON117 18, ,741 4,139 23,19 22,997 1,17 3,424 4,441 27,438 18, ,32 4,233 22, WB ON118 18, ,761 4,164 23,16 24,899 1,292 3,462 4,754 29,653 18, ,414 5,322 24, nder Bay EB ON , ,443 2,392 21, Hwy 11/17 WB ON265 & ,449 1,195 1,853 3,47 21, Red Rock EB ON , ,943 3,279 14,615 13, ,528 4,462 17,891 12, ,48 3,843 16, WB ON158 &17 11, ,936 3,238 14,62 13, ,136 5,125 19,39 12, ,617 5,288 17, Heyden NB ON134 1, ,376 1,534 11,999 25, ,512 3,293 28,944 12, ,412 3,155 15, SB ON135 1, ,371 1,496 11,991 25, ,982 2,792 28,13 12, ,794 2,48 15, Northshore EB ON147 11, ,195 3,62 14,971 12, ,982 3,74 16,49 11, ,184 2,744 14, WB ON148 11, ,174 3,571 14,968 13, ,58 4,291 17,631 12, ,374 3,956 16, North Bay WB ON , ,76 3,546 27,92 32, ,673 2,533 34,592 51,947 1,83 1,669 2,752 54, West of EB , ,432 1,756 13, Mattawa* WB , ,66 1,917 13, Note: * Mattawa and ON-MB border counts were also conducted in Fall 211 for the Northern Ontario passenger-vehicle survey, documented separately. OCTOBER 3,