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摘要: 为了对中国未来的交通安全形势做出科学预测, 分析了中国道路交通安全状况的评价指标和主要影响因素, 建立了以机动车保有量、人口、公路里程、客货运输周转量和国家控制力度为参数的道路交通事故死亡人数预测模型, 并对1991~2004年各年的死亡人数进行了计算和未来年份死亡人数进行了预测。预测结果表明: 预测模型精度高, 平均预测误差为3.9%;得出2010年和2020年中国道路交通事故死亡人数的预测值分别为14万人和17万人, 死亡人数由上升转为下降的转折点出现时间约在2010年到2015年之间。Abstract: In order to scientifically predict the future traffic safety situation in China, a prediction model of traffic accident death toll was built based on the analysis of evaluation indices and main influence factors of Chinese road traffic safety situation, which several factors were taken as parameters, including motor vehicle amount, population, highway mileage, passengers and goods transport volume, and government policy. According to the model, the annual death toll from 1991 to 2004 was calculated, and the future death toll was predicted.Prediction result shows that the precision of the model is higher, the average predicting error is 3.9%;the predicting values of accident death toll in 2010 and 2020 are 14 ten thousand people and 17 ten thousand people respectively; the turning time is during 2010 to 2015 when the death toll changes from rising to descending.
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Key words:
- traffic safety /
- road traffic accident /
- death toll /
- prediction model
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表 1 道路交通安全评价指标特性
Table 1. Properties of evaluation indices for road traffic safety
评价指标 可测性 代表性 可比性 死亡人数 好 好 好 受伤人数 好 一般 差 事故次数 好 好 一般 经济损失 好 一般 差 表 2 相关影响因素
Table 2. Relative influence factors
影响因素 各历史年份数据 预测年份数据 1980 1985 1990 1995 2000 2004 2010 2020 机动车保有量/104 veh 208.8 655.6 1476.3 3179.8 6639.9 10779.0 12400.0 公路里程/104 km 88.83 94.24 102.83 115.70 140.30 187.70 210.00~230.00 260.00~300.00 人口/108人 9.87 10.59 11.43 12.11 12.63 12.99 13.77 14.72 旅客周转量/(108人·km) 729.5 1725.0 2620.0 4603.0 6657.0 8748.0 12416.0 货物周转量/(108 t·km) 851.8 1903.0 3358.0 4695.0 6129.0 7841.0 10457.0 表 3 影响因素组合系数
Table 3. Combination coefficiens of influence factors
人车路因素 周转量因素 政策性因素 0.2514 0.2700 0.4786 表 4 死亡人数预测结果
Table 4. Prediction result of death toll
年份 交通事故年死亡人数/人 相对误差/% 实际值 模型Ⅰ 模型Ⅱ 模型Ⅲ 模型Ⅳ 1991 53292.00 58740.83 54115.56 53783.27 55119.32 4.0301 1992 58729.00 62115.98 57305.56 57609.76 58660.49 2.5533 1993 63508.00 65848.63 61137.57 61589.76 62538.35 2.9913 1994 66362.00 69960.03 65081.76 65713.20 66610.36 2.1757 1995 71494.00 74086.64 69286.12 69967.93 70819.28 2.4482 1996 73665.00 77579.26 73397.93 74339.73 74899.86 2.0671 1997 73861.00 81118.60 78608.14 78812.52 79337.09 7.5928 1998 78067.00 86404.97 81865.53 83368.47 83726.05 7.3965 1999 83529.00 89583.57 89002.91 87988.35 88663.32 6.3218 2000 93853.00 92728.21 94289.62 92651.75 93113.20 0.9330 2001 105928.00 112372.10 101026.60 97337.50 102113.26 5.6054 2002 109381.00 114545.00 109640.40 102024.00 107228.21 3.4131 2003 104372.00 112998.40 100849.20 106689.60 106698.72 4.0225 2004 99217.00 113626.10 107543.20 111313.20 110876.76 3.5141 2010 149906.20 137416.80 137119.30 140414.25 2020 155339.70 183163.40 167914.70 172600.22 -
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