The current practice of road safety attributes traffic crash costs to the location of traffic crashes. Therefore it is challenging to estimate the economic cost of traffic crashes and individuals who are more prone to the burden of traffic crashes. To address this limitation, this study used the home address of individuals who were involved in traffic crashes in the Knoxville Regional Travel Model (KRTM) region between 2015 and 2016. After geocoding the home addresses, 110,312 individuals were assigned to the Traffic Analysis Zone (TAZ) corresponding to their home address and the economic cost of traffic crashes per capita (ECCPC) was calculated for each TAZ. The average ECCPC in the study area was $1,250. The KRTM output was used for extracting travel behavior data elements for modeling ECCPC at the zonal level. This study also established an index to measure average zonal activity in the transportation system for each TAZ. Analysis indicates that the burden of traffic crashes was more tangible in the TAZs with lower-income households and higher average zonal activities. To account for spatial autocorrelation, a Spatial Autoregressive model (SAR) and a spatial error model (SEM) were used. The SAR model was more suitable compared with SEM and ordinary least squares regression. Findings indicate that average zonal activity and traffic exposure have a significant positive association with ECCPC. The ECCPC could be used as an index for allocating proper countermeasures and interventions to groups and areas where the burden of traffic crashes is more tangible.

道路安全的当前实践将交通事故成本归因于交通事故的位置。因此，估算交通事故的经济成本以及更容易承受交通事故负担的个人具有挑战性。为了解决这一限制，本研究使用了2015年至2016年间在诺克斯维尔地区旅行模型（KRTM）地区发生交通事故的个人的家庭住址。对家庭住址进行地理编码后，将110,312个人分配到了交通分析区对应于其家庭住址的TAZ）和每个TAZ的人均交通事故的经济损失（ECCPC）。研究区域的平均ECCPC为$ 1,250。KRTM输出用于提取旅行行为数据元素，以便在区域级别对ECCPC进行建模。这项研究还建立了一个指标，用于测量每个TAZ在运输系统中的平均区域活动。分析表明，在收入较低的家庭和平均区域活动较高的TAZ中，交通事故的负担更为明显。为了说明空间自相关，使用了空间自回归模型（SAR）和空间误差模型（SEM）。与SEM和普通最小二乘回归相比，SAR模型更为合适。研究结果表明平均区域活动和交通暴露与ECCPC有显着的正相关。ECCPC可以用作为交通事故负担更明显的群体和地区分配适当对策和干预措施的指标。分析表明，在收入较低的家庭和平均区域活动较高的TAZ中，交通事故的负担更为明显。为了说明空间自相关，使用了空间自回归模型（SAR）和空间误差模型（SEM）。与SEM和普通最小二乘回归相比，SAR模型更为合适。研究结果表明平均区域活动和交通暴露与ECCPC有显着的正相关。ECCPC可以用作为交通事故负担更明显的群体和地区分配适当对策和干预措施的指标。分析表明，在收入较低的家庭和平均区域活动较高的TAZ中，交通事故的负担更为明显。为了说明空间自相关，使用了空间自回归模型（SAR）和空间误差模型（SEM）。与SEM和普通最小二乘回归相比，SAR模型更为合适。研究结果表明平均区域活动和交通暴露与ECCPC有显着的正相关。ECCPC可以用作为交通事故负担更明显的群体和地区分配适当对策和干预措施的指标。使用空间自回归模型（SAR）和空间误差模型（SEM）。与SEM和普通最小二乘回归相比，SAR模型更为合适。研究结果表明平均区域活动和交通暴露与ECCPC有显着正相关。ECCPC可以用作为交通事故负担更明显的群体和地区分配适当对策和干预措施的指标。使用空间自回归模型（SAR）和空间误差模型（SEM）。与SEM和普通最小二乘回归相比，SAR模型更为合适。研究结果表明平均区域活动和交通暴露与ECCPC有显着的正相关。ECCPC可以用作为交通事故负担更明显的群体和地区分配适当对策和干预措施的指标。