Modelling and assessing inter-regional transportation routing activities of trucks in Canada

作为西半球最大的国家，加拿大依靠广泛的高速公路网在城市和地区之间运送人员和货物。事实上，运输和仓储加起来直接或间接占加拿大GDP的10%。卡车运输是最大的货运方式(按货运量计算占国内货物运输量的72%)，但有关长途卡车运输的信息受到数据收集的巨大成本以及车辆跨越市、区、省和联邦边界时涉及多个司法管辖区的困难的限制。 拟议的研究计划依赖于申请者以前使用GPS数据的经验，以提供急需的长途卡车运动的基本数据，并利用这些信息开发加拿大地区间卡车模式的模型。这项拟议的研究将分析加拿大境内的卡车路线，并开发路线选择模型，以衡量路线因素(时间、可靠性等)的影响。这些模型将帮助我们预测各种经济和政策变化对未来交通需求的影响。该研究计划还将提出一套旨在评估长途卡车性能及其使用的路线的衡量标准。这些措施的分类包括关键程度(每条道路连接有多重要？)、冗余(是否有合适的替代路线可用？)和可靠性(公路网上发生延误的频率和地点？)。此外，研究还将探索卡车模式和路线选择如何受到各种土地用途(仓库、多式联运设施等)的影响。以及采用互联和自动驾驶汽车(CAV)技术。Cavs的潜在影响还没有被很好地了解，但随着这项技术的广泛采用，预计将导致运输模式的戏剧性变化。 这项工作将对其他研究领域有价值，包括(1)创建加拿大版的美国货运分析框架；(2)与经济模型整合；(3)研究卡车旅行(多行程旅行)和供应链模型(跟踪不同旅行方式的货物)；(4)长途卡车的环境排放评估。由于货物流动对加拿大经济的重要性，这项研究的结果将为未来交通投资的决策提供重要的见解。这项工作的成果将对包括运输专业人员、公共部门政策制定者和参与运输的私营部门公司在内的许多各方都很有价值。此外，该研究计划将培训六名高素质的个人，他们将为加拿大应对未来交通领域挑战的努力做出贡献。

As the largest country in the western hemisphere, Canada relies on an extensive highway network to move people and goods between cities and regions. Indeed, transportation and warehousing together account for 10% of Canada's GDP directly or indirectly. Trucking is the largest mode of freight transportation (transporting 72% of domestic goods by volume), but information on long-haul truck movements is limited by substantial costs of data collection and difficulties arising from multiple jurisdictions involved as vehicles cross municipal, regional, provincial, and federal boundaries. The proposed research program relies on the applicant's previous experience using GPS data to supply much needed basic data on long-haul truck movements and utilize this information to develop models of inter-regional truck patterns in Canada. The proposed research will analyze truck routes across Canada and develop route choice models to measure the influence of route factors (time, dependability, etc.). The models will help us predict the impact of various economic and policy changes on future transportation needs. The research program will also suggest a set of measures designed to evaluate the performance of long-haul trucks and the routes they use. Classifications of these measures include criticality (how important is each road link?), redundancy (are there suitable alternative routes available?), and dependability (how often and where do delays occur on the road network?). In addition, the research will explore how truck patterns and route choices are influenced by various land uses (warehouses, multi-modal facilities, etc.) and the adoption of connected and autonomous vehicle (CAV) technology. The potential impacts of CAVs are not well understood, yet expected to incur dramatic changes to transportation patterns as the technology becomes widely adopted. The work will be valuable to other research areas including (1) the creation of a Canadian version of the U.S. Freight Analysis Framework; (2) integration with economic models; (3) research into truck tours (multi-leg trips) and supply chain models (tracking goods across various travel modes); and (4) the evaluation of environmental emissions from long-haul trucks. Due to the significance of goods movement to the Canadian economy, the results of this research will provide vital insights to inform decision making on future transportation investments. The outputs of this work will be valuable to many varied parties including transportation professionals, public sector policy makers and private sector firms involved in transportation. In addition, the research program will train six highly qualified individuals who will contribute towards Canadian efforts to tackle future challenges in the transportation sector.