出行者向诱导转移的委托代理模型研究
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摘要
交通诱导的关键在于确定诱导分流的最优路径,从而尽快分流拥堵车辆,减少拥堵所带来的损失和影响.目前面临的难题为交通系统的诱导接受率问题,路径诱导接受率指提供的路径规划是否满足出行者的出行需求.利用委托代理理论,将管理者作为委托人,出行者作为代理人,建立管理者–出行者的委托代理模型,并对管理者实施政策的成本系数、激励系数、出行者的风险规避度、努力成本系数以及产出的不确定性对结果的影响进行数值实验,分析了其对路径诱导接受率的影响,研究表明管理者应尽可能以低成本有针对性的让区域内尽可能多的出行者接受路径诱导,实现政策的高效性,以提高诱导接受率.
The key problem for the traffic guidance is to determine the optimal induced path,and shunt vehicles as soon as possible, which can reduce the loss and impact caused by congestion. Currently, the problem facing the induced traffic system is the acceptance rate measuring whether the induced paths meet the traveler's needs. In this paper, we establish the principalagent model of the manager-traveler by treating the manager as the principal and the traveler as the agent. The impact of the cost coefficient, the incentive coefficient, the risk aversion degree,the effort cost coefficient and the uncertainty of the output on the results are also discussed.A numerical experiment was carried out to analyze the impact on the acceptance rate of route guidance. The study shows that managers should make as many travelers in the region accept route guidance as possible with low cost and pertinence so as to achieve a high efficiency of the policy and to improve the acceptance rate of route guidance.
The key problem for the traffic guidance is to determine the optimal induced path,and shunt vehicles as soon as possible, which can reduce the loss and impact caused by congestion. Currently, the problem facing the induced traffic system is the acceptance rate measuring whether the induced paths meet the traveler's needs. In this paper, we establish the principalagent model of the manager-traveler by treating the manager as the principal and the traveler as the agent. The impact of the cost coefficient, the incentive coefficient, the risk aversion degree,the effort cost coefficient and the uncertainty of the output on the results are also discussed.A numerical experiment was carried out to analyze the impact on the acceptance rate of route guidance. The study shows that managers should make as many travelers in the region accept route guidance as possible with low cost and pertinence so as to achieve a high efficiency of the policy and to improve the acceptance rate of route guidance.
引文
[1] Shimizu H, Kobayashi M, Yonezaw Y. A route guidance system of a traffic network[C]//Proceedings of the 34th SICE Annual Conference, International Session Papers, 1995:1549-1552
[2] Shimizu H, Nanba T, Narumi A. Time and space variations of dynamic traffic information on a traffic control system[C]//Proceedings of the 35th SICE Annual Conference, International Session Papers, 1996:1337-1342
[3]赵丹,邵春福,王军利,等.多方式诱导下通勤出行链交通方式组合选择行为模型[J].吉林大学学报(工学版),2015, 45(6):1763-1770Zhao D, Shao C F, Wang J L, et al. Modelling combined mode choice behavior of commute trip chain under multi-modal guidance[J]. Journal of Jilin University(Engineering and Technology Edition), 2015, 45(6):1763-1770
[4]龙琼,胡列格,张谨帆,等.不确定性环境下个性化路径选择的多属性决策方法[J].中国公路学报,2014, 27(9):105-110Long Q, Hu L G, Zhang J F, et al. Multi-attribute decision-making for personalized route selection under uncertain condition[J]. China Journal of Highway and Transport, 2014, 27(9):105-110
[5] Fonzone A, Schm¨ocker J D, Ma J S, et al. Link-based route choice considering risk aversion, disappointment,and regret[J]. Journal of the Transportation Research Record, 2012, 2322(1):119-128
[6] Papinski D, Scott D M. A GIS-based toolkit for route choice analysis[J]. Journal of Transport Geography,2011, 19(3):434-442
[7]龚,李苏剑,刘启生.驾驶员分类的路径诱导系统及评价指标[J].武汉理工大学学报,2013, 35(1):75-81Gong Y, Li S J, Liu Q S. Route guidance system and evaluation index based on drivers’ classification[J].Journal of Wuhan University of Technology, 2013, 35(1):75-81
[8] Song D, Peeta S, Hsu Y T. Role of psychological effects of real-time travel information provision on en route traveler route choice decisions[C]//Driving Assessment Cconference, Iowa, 2017:277-283
[9]徐天东,孙立军,郝媛,等.不同交通信息下网络交通动态路径选择行为[J].同济大学学报(自然科学版),2009,37(8):1029-1033Xu T D, Sun L J, Hao Y, et al. Influence of different traffic information on drivers’ dynamic route choice behavior in urban road network level[J]. Journal of Tongji University(Natural Science), 2009, 37(8):1029-1033
[10]高鹏.基于路网知识的驾驶员路径选择研究[D].长春:吉林大学,2012Gao P. Research on drivers’ route choice behavior based on network knowledge[D]. Changchun:Jilin University, 2012
[11]刘新民,鲁晓燕,孙秋霞.基于不同偏好的出行者路径选择行为研究[J].重庆交通大学学报(自然科学版),2017,36(10):102-106Liu X M, Lu X Y, Sun Q X. Traveler’s behavior of path selection based on different preferences[J]. Journal of Chongqing Jiaotong University(Natural Science), 2017, 36(10):102-106
[12]王健,程苑,张哲宁.基于演化博弈论的汽车共享与私家车博弈研究[J].交通信息与安全,2017, 35(2):89-93Wang J, Cheng Y, Zhang Z N. A game analysis between car-sharing and private cars based on evolutionary game theory[J]. Journal of Transport Information and Safety, 2017, 35(2):89-93
[13]潘驰,郭志达.社会互动效应下通勤者出行方式选择行为研究[J].交通运输系统工程与信息,2017, 17(6):101-106Pan C, Guo Z D. Commuter behavior mechanism of travel mode choice based on the perspective of social interaction[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(6):101-106
[14]丰景春,杨圣涛.基于公平偏好理论的PPP交通项目超额收益分配研究[J].软科学,2017, 31(17):120-124Feng J C, Yang S T. Research on excess return distribution of PPP traffic project based on the theory of fairness preference[J]. Soft Science, 2017, 31(17):120-124
[2] Shimizu H, Nanba T, Narumi A. Time and space variations of dynamic traffic information on a traffic control system[C]//Proceedings of the 35th SICE Annual Conference, International Session Papers, 1996:1337-1342
[3]赵丹,邵春福,王军利,等.多方式诱导下通勤出行链交通方式组合选择行为模型[J].吉林大学学报(工学版),2015, 45(6):1763-1770Zhao D, Shao C F, Wang J L, et al. Modelling combined mode choice behavior of commute trip chain under multi-modal guidance[J]. Journal of Jilin University(Engineering and Technology Edition), 2015, 45(6):1763-1770
[4]龙琼,胡列格,张谨帆,等.不确定性环境下个性化路径选择的多属性决策方法[J].中国公路学报,2014, 27(9):105-110Long Q, Hu L G, Zhang J F, et al. Multi-attribute decision-making for personalized route selection under uncertain condition[J]. China Journal of Highway and Transport, 2014, 27(9):105-110
[5] Fonzone A, Schm¨ocker J D, Ma J S, et al. Link-based route choice considering risk aversion, disappointment,and regret[J]. Journal of the Transportation Research Record, 2012, 2322(1):119-128
[6] Papinski D, Scott D M. A GIS-based toolkit for route choice analysis[J]. Journal of Transport Geography,2011, 19(3):434-442
[7]龚,李苏剑,刘启生.驾驶员分类的路径诱导系统及评价指标[J].武汉理工大学学报,2013, 35(1):75-81Gong Y, Li S J, Liu Q S. Route guidance system and evaluation index based on drivers’ classification[J].Journal of Wuhan University of Technology, 2013, 35(1):75-81
[8] Song D, Peeta S, Hsu Y T. Role of psychological effects of real-time travel information provision on en route traveler route choice decisions[C]//Driving Assessment Cconference, Iowa, 2017:277-283
[9]徐天东,孙立军,郝媛,等.不同交通信息下网络交通动态路径选择行为[J].同济大学学报(自然科学版),2009,37(8):1029-1033Xu T D, Sun L J, Hao Y, et al. Influence of different traffic information on drivers’ dynamic route choice behavior in urban road network level[J]. Journal of Tongji University(Natural Science), 2009, 37(8):1029-1033
[10]高鹏.基于路网知识的驾驶员路径选择研究[D].长春:吉林大学,2012Gao P. Research on drivers’ route choice behavior based on network knowledge[D]. Changchun:Jilin University, 2012
[11]刘新民,鲁晓燕,孙秋霞.基于不同偏好的出行者路径选择行为研究[J].重庆交通大学学报(自然科学版),2017,36(10):102-106Liu X M, Lu X Y, Sun Q X. Traveler’s behavior of path selection based on different preferences[J]. Journal of Chongqing Jiaotong University(Natural Science), 2017, 36(10):102-106
[12]王健,程苑,张哲宁.基于演化博弈论的汽车共享与私家车博弈研究[J].交通信息与安全,2017, 35(2):89-93Wang J, Cheng Y, Zhang Z N. A game analysis between car-sharing and private cars based on evolutionary game theory[J]. Journal of Transport Information and Safety, 2017, 35(2):89-93
[13]潘驰,郭志达.社会互动效应下通勤者出行方式选择行为研究[J].交通运输系统工程与信息,2017, 17(6):101-106Pan C, Guo Z D. Commuter behavior mechanism of travel mode choice based on the perspective of social interaction[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(6):101-106
[14]丰景春,杨圣涛.基于公平偏好理论的PPP交通项目超额收益分配研究[J].软科学,2017, 31(17):120-124Feng J C, Yang S T. Research on excess return distribution of PPP traffic project based on the theory of fairness preference[J]. Soft Science, 2017, 31(17):120-124
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