基于D-S证据理论的出租车减排策略评价
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摘要
针对目前出租车污染减排策略效果的评价缺少数据支持的问题,研究了基于层次分析法及D-S证据理论的评价模型。通过文献梳理筛选了出租车维护保养、提高燃油标准、减少出租车空驶里程、定期更换尾气净化装置、推广新能源汽车等5种出租车污染减排策略。随后从经济、环境、社会和技术4个方面,建立了出租车减排策略效果评价的指标体系。运用层次分析法获得了子准则层指标权重,运用D-S证据理论从公众、政府管理者、研究人员、专家等多主体角度综合分析了不同减排策略的效果。结果表明,推广清洁能源汽车策略效果的评价值比提高燃油标准策略高9.35%,比定期更换尾气净化装置策略高11.59%,比车辆维修与保养策略高16.56%,比减少出租车空驶里程策略高21.29%。
An evaluation model based on analytic hierarchy process(AHP) and Dempster-Shafer(D-S) evidence theory is studied to evaluate issues that effectiveness of pollution reduction strategies lacks data support. Five kinds of reduction strategies for taxi emission, including maintenance of taxis, improvement of fuel standards, reduction of taxi mileage, regular replacement of exhaust gas purification devices, and promotion of new energy vehicles are analyzed through former studies. From four aspects of economy, environment, society, and technology, an indicator system for evaluating effectiveness of reduction strategies for taxi emission is established. An analytic hierarchy process is used to obtain sub-criteria level index weights. The D-S evidence theory is used to comprehensively analyze effects of different strategies from perspectives of the public, government administrators, researchers, and experts. The results show that the evaluation value of the strategy of promoting clean energy vehicles is 9.35% higher than that of the fuel improvement strategy; 11.59% higher than the strategy of regularly replacing the exhaust gas purification device; 16.56% higher than the strategy of vehicle repair and maintenance; and 21.29% higher than the strategy of reducing driving mileage of taxi.
An evaluation model based on analytic hierarchy process(AHP) and Dempster-Shafer(D-S) evidence theory is studied to evaluate issues that effectiveness of pollution reduction strategies lacks data support. Five kinds of reduction strategies for taxi emission, including maintenance of taxis, improvement of fuel standards, reduction of taxi mileage, regular replacement of exhaust gas purification devices, and promotion of new energy vehicles are analyzed through former studies. From four aspects of economy, environment, society, and technology, an indicator system for evaluating effectiveness of reduction strategies for taxi emission is established. An analytic hierarchy process is used to obtain sub-criteria level index weights. The D-S evidence theory is used to comprehensively analyze effects of different strategies from perspectives of the public, government administrators, researchers, and experts. The results show that the evaluation value of the strategy of promoting clean energy vehicles is 9.35% higher than that of the fuel improvement strategy; 11.59% higher than the strategy of regularly replacing the exhaust gas purification device; 16.56% higher than the strategy of vehicle repair and maintenance; and 21.29% higher than the strategy of reducing driving mileage of taxi.
引文
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[15] LATHAM S, BOULTER P, MCCRAE I, TURPIN K, et al. A best practice guide for reducing emissions from taxi in London: PPR 349[R]. Wokingham: Transport Research Laboratory TRLLimited, 2008.
[16] KONG D Y, MA D, WANG M M. A simulation study of upgrading urban gasoline taxis to electric taxis[J]. EnergyProcedia,2016(104):390-395.
[17] TEIXEIRA A C R, SODRE J R. Simulation of the impacts on carbon dioxide emissions from replacement of a conventional Brazilian taxi fleet by electric vehicles[J]. Energy, 2016(115):1617-1622.
[18] FALCAO E A M, TEIXEIRA A C R, SODRE J R. Analysis of CO2 emissions and techno-economic feasibility of an electric commercial vehicle[J]. AppliedEnergy, 2017(193):297-307.
[19] BICKERT S, KAMPKER A, GREGER D. Developments of CO2-emissions and costs for small electric and combustion engine vehicles in Germany[J]. Transportation Research Part D, 2015(36):138-151.
[20] HU J N, WU Y, WANG Z S, LI Z H. Real-world fuel efficiency and exhaust emissions of light-duty diesel vehicles and their correlation with road conditions[J]. Journal of Environmental Sciences, 2012,24(5):865-874.
[21] SLOWA A P, TATICCHI P. Technology, policy and management for carbon reduction: A critical and global review with insights on the role played by the Chinese Academy[J]. Journal of Cleaner Production, 2015(103):601-619.
[22] WALTZ E, LLINAS J. Multisensor data fusion[M]. Boston: Artech house, 1990:11-27
[23] YAGER R R. Comparing approximate reasoning and probabilistic reasoning using the Dempster-Shafer framework[J]. International Journal of Approximate Reasoning, 2009,50(5):812-821
[24] BASIR O, YUAN X H. Engine fault diagnosis based on multi-sensor information fusion using Dempster-Shafer evidence theory[J]. Information Fusion, 2007,8(4):379-386.
[25] 石红国,贺玉娇,基于D-S证据理论的城市轨道交通线网规划评价研究[J].铁路运输与经济,2018,40(2):87-93 SHI Hongguo, HE Yujiao. Urban rail transit network planning evaluation based on D-S evidence theory[J]. Railway Transportation and Economy, 2018,40(2):87-93.(in Chinese)
[2] 石磊,王岐东,付明亮,等.应用居民出行状况估算北京市机动车污染排放量[J].北京工商大学学报(自然科学版),2009,27(2):12-15. SHI Lei, WANG Qidong, FU Mingliang, et al. Application of situation of residents travel to estimate vehicles emission in Bejing[J]. Journal of Beijing Technology and Business University(Natural Science Edition), 2009,27(2):12-15. (inChinese)
[3] 李洪亮,邹本存,金世洲,等.基于使用年限的汽车排气污染物检测结果分析[J].武汉理工大学学报(交通科学与工程版),2015,39(4):738-742 LI Hongliang, ZOU Bencun, JIN Shizhou, et al. Exhaust pollutants test results analysis of vehicle basedon useful life[J]. Journal of Wuhan University of Technology (Transportation Science & Engineering Edition), 2015,39(4):738-742. (inChinese)
[4] 刘四建.应重视出租车污染问题[N].中国环境报,2014-01-22. LIU Sijian.Attention should be paid to the problem of taxi pollution[N]. China Environment News, 2014-01-22.(inChinese)
[5] 赵敏,张卫国,俞立中,等.上海市居民出行方式与城市交通CO2排放及减排对策[J].环境科学研究,2009,22(6):747-752. ZHAO Min, ZHANG Weiguo, YU Lizhong, et al. Resident travel modes and CO2 emissions by trafficin Shanghai city[J]. Research of Environmental Sciences, 2009,22(6):747-752. (inChinese)
[6] 黄宇,吴晓煦.武汉市道路交通业CO2排放与减排潜力分析[J].环境保护科学,2012,38(6):9-13. HUANG Yu, WU Xiaoxu. CO2 emission from road transport and the emission reduction potential in Wuhan city[J]. Environmental Protection Science, 2012,38(6):9-13. (inChinese)
[7] BARNETT A G, KNIBBS L D. Higher fuel prices are associated with lower air pollution levels[J]. Environment International, 2017(66):88-91.
[8] 于匡员.基于预约模式的出租车合乘路径优化[D].哈尔滨:哈尔滨工业大学,2015. YU Kuangyuan. Taxi pooling routing optimization based on reserve pattern[D]. Harbin:Harbin Institute of Technology, 2015. (inChinese)
[9] LAU J, HUNG W.T, CHEUNG C.S. On-board gaseous emissions of LPG taxis and estimation of taxi fleet emissions[J]. Science of the Total Environment, 2011(409):5292-5300.
[10] 朱传勇,胡京南,鲍晓峰,等.高里程出租车的排放控制措施[J].环境科学研究,2012,25(3):265-269. ZHU Chuanyong, HU Jingnan, BAO Xiaofeng, et al. Methods for controlling emissions from high mileage taxis[J]. Research of Environmental Sciences, 2012,25(3):265-269. (inChinese)
[11] AN S, HU X W, WANG J. Urban taxis and air pollution: A cases tudy in Harbin, China[J]. Journal of Transport Geography, 2011,19(4):960-967.
[12] 徐慧智,裴玉龙,王连震,等.城市客运交通引入电动汽车二氧化碳减排量研究:以哈尔滨市为例[J].交通信息与安全,2018,36(1):111-117 XU Huizhi, PEI Yulong, WANG Lianzhen, et al. Emission reduction of CO2 caused by BEV in urban passenger transport: a case study of Harbin[J]. Journal of Transport Information and Safety. 2018,36(1):111-117.(inChinese)
[13] GAO H.O, KITIRATTRAGARN V. Taxi owners′ buying preferences of hybridelectric vehicles and their implications for emissions in New York City[J]. Transportation Research Part A, 2008(42):1064-1073.
[14] 周程,王磊,陶君成.考虑不同低碳政策影响的物流配送优化决策[J].武汉理工大学学报(交通科学与工程版),2015,39(3):479-483. ZHOU Cheng, WANG Lei, TAO Juncheng. Research on logistics distribution routing optimization underthe different carbon emission policies[J]. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2015,39(3):479-483.(in Chinses)
[15] LATHAM S, BOULTER P, MCCRAE I, TURPIN K, et al. A best practice guide for reducing emissions from taxi in London: PPR 349[R]. Wokingham: Transport Research Laboratory TRLLimited, 2008.
[16] KONG D Y, MA D, WANG M M. A simulation study of upgrading urban gasoline taxis to electric taxis[J]. EnergyProcedia,2016(104):390-395.
[17] TEIXEIRA A C R, SODRE J R. Simulation of the impacts on carbon dioxide emissions from replacement of a conventional Brazilian taxi fleet by electric vehicles[J]. Energy, 2016(115):1617-1622.
[18] FALCAO E A M, TEIXEIRA A C R, SODRE J R. Analysis of CO2 emissions and techno-economic feasibility of an electric commercial vehicle[J]. AppliedEnergy, 2017(193):297-307.
[19] BICKERT S, KAMPKER A, GREGER D. Developments of CO2-emissions and costs for small electric and combustion engine vehicles in Germany[J]. Transportation Research Part D, 2015(36):138-151.
[20] HU J N, WU Y, WANG Z S, LI Z H. Real-world fuel efficiency and exhaust emissions of light-duty diesel vehicles and their correlation with road conditions[J]. Journal of Environmental Sciences, 2012,24(5):865-874.
[21] SLOWA A P, TATICCHI P. Technology, policy and management for carbon reduction: A critical and global review with insights on the role played by the Chinese Academy[J]. Journal of Cleaner Production, 2015(103):601-619.
[22] WALTZ E, LLINAS J. Multisensor data fusion[M]. Boston: Artech house, 1990:11-27
[23] YAGER R R. Comparing approximate reasoning and probabilistic reasoning using the Dempster-Shafer framework[J]. International Journal of Approximate Reasoning, 2009,50(5):812-821
[24] BASIR O, YUAN X H. Engine fault diagnosis based on multi-sensor information fusion using Dempster-Shafer evidence theory[J]. Information Fusion, 2007,8(4):379-386.
[25] 石红国,贺玉娇,基于D-S证据理论的城市轨道交通线网规划评价研究[J].铁路运输与经济,2018,40(2):87-93 SHI Hongguo, HE Yujiao. Urban rail transit network planning evaluation based on D-S evidence theory[J]. Railway Transportation and Economy, 2018,40(2):87-93.(in Chinese)