Park, PeterGingerich, KevinNevland, Erik Alexander2020-08-112020-08-112020-012020-08-11http://hdl.handle.net/10315/37681Collisions involving trucks have increased fatality risks compared to passenger vehicles. Hours-of-Service (HOS) laws exist to reduce fatalities where truck driver fatigue is a contributing factor. Electronic logging devices (ELD) are being mandated to automatically track HOS and enforce compliance, creating a greater urgency for adequate truck parking. A lack of truck parking is often identified throughout North America; however, these studies are often limited to public rest areas despite evidence that drivers often utilize other types of parking. To adequately compare truck parking supply and demand, an exhaustive truck parking classification scheme is developed based on important location attributes identified through extensive literature review. This scheme can be systematically implemented using available geospatial data. This data is then used to develop a truck parking supply model based on a negative binomial regression. The Region of Peel is used as the study area due to its considerably large freight industry.Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.Geographic information scienceElectronic Thesis or Dissertation2020-08-11FreightParkingFreight ParkingTruck ParkingHeavy Commercial VehiclesHCVParking SupplyTruck Parking SupplyHours-of-ServiceElectronic Logging DevicesDriver FatigueGPS DataNegative Binomial RegressionTruck Parking ClassificationTruck Parking Supply ModelTransportation EngineeringTransportation PlanningRegion of PeelPeel Region