Investigating the Potential of Ridesharing to Reduce Vehicle Emissions

Abstract

As urban populations grow, cities need new strategies to maintain a good standard of living while enhancing services and infrastructure development. A key area for improving city operations and spatial layout is the transportation of people and goods. While conventional transportation systems (i.e., fossil fuel based) are struggling to serve mobility needs for growing populations, they also represent serious environmental threats. Alternative-fuel vehicles can reduce emissions that contribute to local air pollution and greenhouse gases as mobility needs grow. However, even if alternative-powered vehicles were widely employed, road congestion would still increase. This paper investigates ridesharing as a mobility option to reduce emissions (carbon, particulates and ozone) while accommodating growing transportation needs and reducing overall congestion. The potential of ridesharing to reduce carbon emissions from personal vehicles in Changsha, China, is examined by reviewing mobility patterns of approximately 8,900 privately-owned vehicles over two months. Big data analytics identify ridesharing potential among these drivers by grouping vehicles by their trajectory similarity. The approach includes five steps: data preprocessing, trip recognition, feature vector creation, similarity measurement and clustering. Potential reductions in vehicle emissions through ridesharing among a specific group of drivers are calculated and discussed. While the quantitative results of this analysis are specific to the population of Changsha, they provide useful insights for the potential of ridesharing to reduce vehicle emissions and the congestion expected to grow with mobility needs. Within the study area, ridesharing has the potential to reduce total kilometers driven by about 24% assuming a maximum distance between trips less than 10 kilometers, and schedule time less than 60 minutes. For a more conservative maximum trip distance of 2 kilometers and passenger schedule time of less than 40 minutes, the reductions in traveled kilometers could translate to the equivalent of approximately 4.0 tons CO 2 emission reductions daily.

Urban smart mobility in the scientific literature — bibliometric analysis

“…• developing new heuristic algorithms to measure, evaluate and minimise CO2, NOx, and CO emissions in multi-depot Green Vehicle Routing problems (Turkensteen, 2017) with economic and social applicability; • applying machine learning algorithms in solving Ridesharing problems to reduce vehicle emissions, maintaining too of decent living standards through development of infrastructure and qualitative services (Jalali et al, 2017); • developing Breath Journey software applications that combine GPS track with air quality for travel planning which can show the distance information, data regarding the pollution levels on the respective routes. Thus, the programming paradigm will change from Software as a Service (SaaS) to Mobility as a Service (MaaS), providing very accurate, real-time, customised, wireless mobility information services regarding travel planning, journey time, air quality, online booking and payment facilities (Florea & Berntzen, 2017).…”

“…Such initiatives aim integrating quality services with improved accessibility into the urban transport network, providing passengers with real-time multimodal information, enhanced comfort (Gaggi et al, 2013). The essential direction of future research trends should concentrate on improving the integration of new shared mobility services with traditional public transport services, autonomous vehicles, car park management and car sharing services, which have already reshaped our life and another various smart mobility services (Yue, Chye & Hoy, 2017;Fagnant & Kockelman, 2015;Jalali et al, 2017) and solving environmental problems caused mainly by traffic congestion (Florea & Berntzen, 2017).…”

Research on Affective Interaction in Mini Public Transport Based on IPA-FMEA

“…One of the best approaches is making full use of the seats of the vehicle in principle, and encouraging and normalizing sharing transport in practice [10]. After reviewing related research, mini public transport, such as mini buses and ridesharing, is regarded as the most balanced transport between sustainability and efficiency [11][12][13].…”