A more decision-oriented and synergy-oriented paradigm for next-gen urban transportation

Urban dwellers in Canada, myself included, expect to witness exciting (and perhaps a bit disturbing) transformations in urban transportation as electric cars, autonomous vehicles, and drones are set on track to enable swifter, safer, and more sustainable ways for people and commodities to travel within cities. This transition toward smarter urban transportation is being rightly reflected in the federal government of Canada’s strategic plan, Transportation 2030, for upgrading Canada’s transportation system for the next generation. One theme of this plan, "Green and Innovative Transportation," aims “to improve Canadians’ lives by using new technologies, and reducing the environmental impacts of transportation, including greenhouse gas emissions and air pollution.” Although this strategic plan is timely, and the technologies involved are indeed maturing, the problem lies in the current general perception of green and smart urban transportation held by policy-makers and practitioners. Specifically, most of the existing government plans, such as Transportation 2030, focus on identifying what components are needed. Typical choices of the components include several emerging technologies, such as information and communication, emission efficiency, autonomous driving, and so on. Other components include policies and regulations concerning fuel standards and air traffic management, among others. Those “tech-oriented” and “policy-oriented” plans reflect the current stage of the urban transportation development, that is, new technology adoption and regulation. However, the next stage of development should put significant emphasis on HOW to maximize citywide benefits for a given portfolio of technologies and regulations. To achieve this transition, tech-oriented and policy-oriented plans should give way to more i) “decision-oriented” and ii) “synergy-oriented” strategies. Below are what those strategies are about: i) Decision-oriented strategies: Incrementing hardware capacity (such as drones and autonomous vehicles) is not what smart urban transportation is all about. What make urban mobility truly smart are decision-making methodologies, solution algorithms and managerial insights. For example, studies show that by smartly making real-time trip-vehicle assignment decisions, such as using 2000 cars (i.e. only 15 per cent of the taxi fleet) of 10 seats for ride-sharing, we can efficiently satisfy 98 per cent of the taxi trip demands in New York City. Such immense gains in transportation efficiency will be reaped at a faster pace if policy makers and practitioners invest in building more muscles of advanced analysis based on machine learning, statistics, and operations research. Another example: a recent study finds that ride-sharing services tend to significantly exacerbate traffic congestion in compact urban areas while alleviating traffic congestion in sprawling areas. Such insights could only be obtained from rigorous, data-driven analysis, and should be incorporated in our roadmap for building sustainable and livable cities. ii) Synergy-oriented strategies: Policy-makers should also broaden their planning scope beyond the traditional boundary of urban transportation. They should be fully conscious of the urban-scale system integration, such as the transportation-energy nexus. Accompanying the large-scale electric vehicle adoption is the tension between limited grid capacity and surging demand for fast battery charging. From a city’s scope, having smart urban power grids and mobility fleets does not automatically imply a smart city. Being blind to either side of the challenge will incur a big loss. For example, earlier research has shown that constructing battery charging stations that satisfy only electric vehicle demands could easily overload power grids. The consequence would be significant remedial investment in capacity expansion of substation transformers and distribution lines. On the other hand, if properly orchestrated, electric vehicles will become a blessing to grids, providing precious support in matching electricity supply and demand, stabilizing power voltage, and retiring carbon-intensive generation units. They can also discharge their batteries during power outages. In other words, the transportation sector should prepare to play a bigger role in enabling a more sustainable and resilient urban grid. In summary, policy-makers and practitioners should adopt the notion of integrated decision scope, within which, planning decisions are coordinated at the urban scale, backed by rigorous and advanced quantitative analysis, and reflective of diverse needs (e.g., efficiency, resilience and sustainability). Only by taking such decision-oriented and synergy-oriented approaches can we collectively build towards a smart-city future. Wei Qi is an associate professor in operations management at the Desautels Faculty of Management at McGill University. He is also a faculty adviser of the China’s Energy Group at the Lawrence Berkeley National Laboratory in California, U.S. His work has contributed to smart-city operations concerning urban energy, mobility, and retail logistics. He earned a PhD from University of California, Berkeley. The Hill Times

A more decision-oriented and synergy-oriented paradigm for next-gen urban transportation

Tech-oriented and policy-oriented plans should give way to more 'decision-oriented' and 'synergy-oriented' strategies.

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A more decision-oriented and synergy-oriented paradigm for next-gen urban transportation

Tech-oriented and policy-oriented plans should give way to more 'decision-oriented' and 'synergy-oriented' strategies.

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