美国加州连续型和限制型HOV高承载车道性能评价
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摘要
高承载车道(HOV车道)是在高速公路中为多载的客车和轻型商用车预留的专用车道,已被视为一个有效的和环保的方法来提高大城市的流动和高速公路系统的生产率。
根据2008年和2009年期间内来自超过700个道路交通检测站(VDS)的数据分析结果,本文结合交通流理论,分析加利福尼亚洲的连续访问类型和限制访问类型HOV高承载车道的特征,确立对车道运行的评价指标。并运用大量的历史数据,实证对比评价不同车道设施的性能。针对事故下的非正常交通状态,提供了一个系统化处理的方法,并广泛探讨和分析实际高承载车道的交通事故及交通状况的数据,量化事故对不同配置的高乘载车道的影响。
通过对HOV专用车道和相邻的通用(GP)的行车线的评价,结果显示这些通道操作系统包括以下几个特点：1)有限的访问HOV设施领域的入口/出口区域可能会影响高乘载车道瓶颈的形成；2)统计表明,和有限访问类型的HOV路线比较,连续访问类型的HOV专线的车速以及HOV车道和通用车道之间的车速差更大,以及3)两种不同类型的高乘载车道的速度—车流分布有显著的不同,但对于相邻不同类型通用车道则没有明显的区别。此外,统计分析表明,在某些线路层面上的性能指标,包括空间和车辆平均速度(车辆行驶里程)和高乘载车道的占有率,对于不同的访问类型与不同的HOV设施有明显的不同。
事故引起的影响区域使用以下的方法来进行估计拟议的,其中包括三个主要步骤：1)从加州高速公路性能测量系统(PeMS)和交通事故监测与分析系统(TASAS)同步发生在HOV车道上事故的信息,2)确定事故影响的区域,以及3)计算事故引起的延迟。以Wilcoxon秩和检验和对数线性回归模型来探讨一些有影响的因素对潜水器巷事故影响,如车道配置,事故持续时间和事故受伤程度。分析结果表明,当我们比较事故影响的均值和方差的地区和延误时,高承载路线上的事故对高乘载道和相邻的通用车道的在不同的车道配置下影响不同,同时也表明,在本研究中的所有检查的因素中,事故发生的时间和伤害与否在统计学意义(在5%的水平)上不是很重要。
High-occupancy vehicle (HOV) facilities, which are reserved for vehicles with more than a pre-determined number of occupants, have been developed for decades as a part of the roadway network system to relieve pressures from ever-increasing travel demands and an effective and environmentally friendly approach to improve the mobility and productivity of freeway systems in metropolitan areas. Based on the traffic data from over 700 vehicle detector stations (VDS) during 2008 and 2009 period, a comparative study of operational performance at the route level was conducted between continuous-access and limited-access HOV facilities in California.
The evaluation results of both HOV lanes and adjacent general purpose (GP) lanes revealed several operating characteristics of these lanes, including:1) the ingress/egress areas in limited-access HOV facilities may affect the formation of bottlenecks along HOV lanes; 2) the speed on HOV lanes and the speed differential between the HOV and adjacent GP lanes are statistically shown to be greater in continuous-access facilities than those in the limited-access facilities; and 3) the characteristics of speed-flow distribution of HOV lanes exhibit observable differences between the two types of HOV facilities, but those of adjacent GP lanes are similar regardless of the access type. Furthermore, statistical analyses show that some performance measures at the route level, including the space mean speed and vehicle-mile-traveled (VMT) share of the HOV lanes, are significantly different for HOV facilities with different access types.
The accident-induced impacts were estimated by the proposed methodology, in which three major steps are included:1) synchronization of HOV lane accident information from two databases, the California Freeway Performance Measurement System (PeMS), and the Traffic Accident Surveillance and Analysis System (TASAS); 2) identification of accident impact regions; and 3) calculation of 10 accident-induced delays. The Wilcoxon rank sum test and log-linear regression models were used to investigate several influential factors on HOV lane accident impacts, such as lane configuration, accident duration, and injury or not. The analysis results imply that the impacts of HOV lane accidents on both HOV lanes and adjacent general purpose (AGP) lanes may be different for different HOV lane configuration, when compared the sample mean and variance of accident impact regions and delays, and also indicate that the accident duration and injury or not appear to be statistically significant (at 5% level) among all the factors examined in this study.
根据2008年和2009年期间内来自超过700个道路交通检测站(VDS)的数据分析结果,本文结合交通流理论,分析加利福尼亚洲的连续访问类型和限制访问类型HOV高承载车道的特征,确立对车道运行的评价指标。并运用大量的历史数据,实证对比评价不同车道设施的性能。针对事故下的非正常交通状态,提供了一个系统化处理的方法,并广泛探讨和分析实际高承载车道的交通事故及交通状况的数据,量化事故对不同配置的高乘载车道的影响。
通过对HOV专用车道和相邻的通用(GP)的行车线的评价,结果显示这些通道操作系统包括以下几个特点：1)有限的访问HOV设施领域的入口/出口区域可能会影响高乘载车道瓶颈的形成；2)统计表明,和有限访问类型的HOV路线比较,连续访问类型的HOV专线的车速以及HOV车道和通用车道之间的车速差更大,以及3)两种不同类型的高乘载车道的速度—车流分布有显著的不同,但对于相邻不同类型通用车道则没有明显的区别。此外,统计分析表明,在某些线路层面上的性能指标,包括空间和车辆平均速度(车辆行驶里程)和高乘载车道的占有率,对于不同的访问类型与不同的HOV设施有明显的不同。
事故引起的影响区域使用以下的方法来进行估计拟议的,其中包括三个主要步骤：1)从加州高速公路性能测量系统(PeMS)和交通事故监测与分析系统(TASAS)同步发生在HOV车道上事故的信息,2)确定事故影响的区域,以及3)计算事故引起的延迟。以Wilcoxon秩和检验和对数线性回归模型来探讨一些有影响的因素对潜水器巷事故影响,如车道配置,事故持续时间和事故受伤程度。分析结果表明,当我们比较事故影响的均值和方差的地区和延误时,高承载路线上的事故对高乘载道和相邻的通用车道的在不同的车道配置下影响不同,同时也表明,在本研究中的所有检查的因素中,事故发生的时间和伤害与否在统计学意义(在5%的水平)上不是很重要。
High-occupancy vehicle (HOV) facilities, which are reserved for vehicles with more than a pre-determined number of occupants, have been developed for decades as a part of the roadway network system to relieve pressures from ever-increasing travel demands and an effective and environmentally friendly approach to improve the mobility and productivity of freeway systems in metropolitan areas. Based on the traffic data from over 700 vehicle detector stations (VDS) during 2008 and 2009 period, a comparative study of operational performance at the route level was conducted between continuous-access and limited-access HOV facilities in California.
The evaluation results of both HOV lanes and adjacent general purpose (GP) lanes revealed several operating characteristics of these lanes, including:1) the ingress/egress areas in limited-access HOV facilities may affect the formation of bottlenecks along HOV lanes; 2) the speed on HOV lanes and the speed differential between the HOV and adjacent GP lanes are statistically shown to be greater in continuous-access facilities than those in the limited-access facilities; and 3) the characteristics of speed-flow distribution of HOV lanes exhibit observable differences between the two types of HOV facilities, but those of adjacent GP lanes are similar regardless of the access type. Furthermore, statistical analyses show that some performance measures at the route level, including the space mean speed and vehicle-mile-traveled (VMT) share of the HOV lanes, are significantly different for HOV facilities with different access types.
The accident-induced impacts were estimated by the proposed methodology, in which three major steps are included:1) synchronization of HOV lane accident information from two databases, the California Freeway Performance Measurement System (PeMS), and the Traffic Accident Surveillance and Analysis System (TASAS); 2) identification of accident impact regions; and 3) calculation of 10 accident-induced delays. The Wilcoxon rank sum test and log-linear regression models were used to investigate several influential factors on HOV lane accident impacts, such as lane configuration, accident duration, and injury or not. The analysis results imply that the impacts of HOV lane accidents on both HOV lanes and adjacent general purpose (AGP) lanes may be different for different HOV lane configuration, when compared the sample mean and variance of accident impact regions and delays, and also indicate that the accident duration and injury or not appear to be statistically significant (at 5% level) among all the factors examined in this study.
引文
[1]FHWA. Federal-Aid Highway Program Guidance on High Occupancy Vehicle (HOV) Lanes-August 2008. http://www.ops.fhwa.dot.gov/. Accessed June 15th,2010
[2]Daganzo, C. F. and M. J. Cassidy. Effects of High Occupancy Vehicle Lanes on Freeway Congestion. Transportation Research Part B, No.42,2008, pp.861-872
[3]Lahon, D., P. T. Martin, and A. Stevanovic. Traffic Impact, Safety Assessment and Public Acceptance of the High Occupancy Vehicle (HOV) Lanes in Utah's Salt Lake Valley. In Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington, DC,2005
[4]Bertini, R. L. and A. M. Mayton. Using PeMS Data to Empirically Diagnose Freeway Bottleneck Locations in Orange County, California. In Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington, DC,2005
[5]Mayora, J. M. P., et al. Recent European Experience with HOV Facilities in Congested Metropolitan Arterials, Analysis of the Operational Performance of the N-VI Bus/HOV Lanes in Madrid, Spain. In Proceedings of the 83th Annual Meeting of the Transportation Research Board, Washington, DC,2004
[6]Texas Transportation Institute (TTI) and Parsons Brinckerhoff Inc.. New Jersey I-80 and I-287 HOV Lane Case Study. Final Report for FHWA, Jul 2000
[7]Xu, G, X. P. Huang and P. Pant. Method for Estimating Capacity Reduction in 7 High-Occupanyc-Vehicle Lane Ingress and Egress Sections. Transportation Research Record, No.1678, Transportation Research Board, Washington, D.C.1999, pp.107-115
[8]Poppe, M. J., D. J. P. Hook, and K. M. Howell. Evaluation of High-Occupancy-Vehicle Lanes in Pheonex, Arizona. Transportation Research Record, No.1446, Transportation Research Board, Washington, D.C.1994, pp.1-7
[9]Newman, L., C. Nuworsoo, and A. D. May. Operational and Safety Experience with Freeway HOV Facilities in California. Transportation Research Record, No.1173, Transportation Research Board, Washington, D.C.1988, pp.18-24
[10]Brown, B. and L. Bolotin. HOV User Survey Washington State Freeway HOV System. In Proceedings of the 87th Annual Meeting of the Transportation Research Board, Washington, DC,2008
[11]Southern California Association of Govements (SCAG). Regional High-Occupancy Vehicle Lane System:Performance Study. Final Report. Nov.2004
[12]Parsons Brinckerhoff Inc.. HOV Performance Program Evaluation Report, for Los Angeles County. Final Report. Nov.2002
[13]C. Wellander and K. Leotta. Are High-Occupancy Vehicle Lanes Effective? Overview of High-Occupancy Vehicle Facilities Across North America. Transportation Research Record, No.1711, Transportation Research Board, Washington, D.C.2000, pp.23-30
[14]Dahlgren, J. High Occupancy Vehicle Lanes:Not Always More Effective than General Purpose Lanes. Transportation Research Part A, No.32,1998, pp.99-114
[15]Guin, A., M. Hunter and R. Guensler. Analysis of Reduction in Effective Capacities of High-Occupancy Vehicle Lanes Related to Traffic Behavior. Transportation Research Record, No.2065, Transportation Research Board, Washington, D.C.2008, pp.47-53
[16]Kwon, J. and P. Varaiya. Effectiveness of California's High Occupancy Vehicle (HOV) System. Transportation Research Part C, No.16,2008, pp.98-115
[17]Jang, K., et al. Safety Performance of High-Occupancy Vehicle (HOV) Facilities: Evaluation of HOV Lane Configurations in California. Transportation Research Record, No. 2099, Transportation Research Board, Washington, D.C.2009, pp.132-140
[18]Freeway Performance Measurement System, http://pems.eecs.berkeley.edu/. Accessed July 10th,2010
[19]Brownstone, D., et al. Evaluation of Incorporating Hybrid Vehicle Use of HOV Lanes. California PATH Research Report. UCB-ITS-PRR-2008-26,2008
[20]Transportation Research Board. Highway Capacity Manual 2000 (HCM 2000).2000
[21]Zar, J. H.. Biostatistical Analysis.4th edition. Prentice Hall, Upper Saddle River, NJ.1999
[22]Kwon, J. and P. Varaiya. Effectiveness of California's High Occupancy Vehicle (HOV) System. Transportation Research Part C, No.16,2008, pp.98-115
[23]Perrin, J., P. Wu, and P. T. Martin. Evaluating HOV Lanes in Salt Lake City, Utah. In Proceedings of the 83th Annual Meeting of the Transportation Research Board, Washington, DC,2004
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[26]Benz, R. J. and D. W. Fenno. Quantification of Travel Time Savings for Barrier Separated High-Occupancy Vehicle (HOV) Lanes During General Purpose Lane Incident
[27]Conditions. In Proceedings of the 85th Annual Meeting of the Transportation Research Board, Washington, DC,2006
[28]Newman, L., C. Nuworsoo, and A. D. May. Operational and Safety Experience with Freeway HOV Facilities in California. Transportation Research Record, No.1173, Transportation Research Board, Washington, D.C.1988, pp.18-24
[29]Skabardonis, A., et al.I-880 Field Experiment:Data-Base Development and Incident Delay Estimation Procedures. Transportation Research Record, No.1554, Transportation Research Board, Washington, D.C.1996, pp.204-212
[30]Skabardonis, A., P. Varaiya, and K. F. Petty and. Measuring Recurrent and Nonrecurrent Traffic Congestion. Transportation Research Record, No.1856, Transportation Research Board, Washington, D.C.2004, pp.118-124
[31]Kwon, J. and P. Varaiya, The Congestion Pie:Delay from Collisions, Potential Ramp Metering Gain and Access Demand. In Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington, DC,2005
[32]Lighthill, M. J. and G B. Whitham. On Kinematic Waves. I. Flood Movement in Long Rivers. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, Vol.229, No.1178,1955, pp.281-316
[33]Al-Deek, H., A. Garib, and A. E. Radwan. New Method for Estimating Freeway Incident Congestion. Transportation Research Record, No.1494, Transportation Research Board, Washington, D.C.1995
[34]Lindley, J.. A Methodology for Quantifying Urban Freeway Congestion. Transportation Research Record, No.1132, Transportation Research Board, Washington, D.C.1987, pp.25 1-7
[35]Jason, B. N., and A. Rathi. Economic Feasibility of Exclusive Vehicle Facilities. Transportation Research Record, No.1305, Transportation Research Board, Washington, D.C.1991, pp.201-214
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[2]Daganzo, C. F. and M. J. Cassidy. Effects of High Occupancy Vehicle Lanes on Freeway Congestion. Transportation Research Part B, No.42,2008, pp.861-872
[3]Lahon, D., P. T. Martin, and A. Stevanovic. Traffic Impact, Safety Assessment and Public Acceptance of the High Occupancy Vehicle (HOV) Lanes in Utah's Salt Lake Valley. In Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington, DC,2005
[4]Bertini, R. L. and A. M. Mayton. Using PeMS Data to Empirically Diagnose Freeway Bottleneck Locations in Orange County, California. In Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington, DC,2005
[5]Mayora, J. M. P., et al. Recent European Experience with HOV Facilities in Congested Metropolitan Arterials, Analysis of the Operational Performance of the N-VI Bus/HOV Lanes in Madrid, Spain. In Proceedings of the 83th Annual Meeting of the Transportation Research Board, Washington, DC,2004
[6]Texas Transportation Institute (TTI) and Parsons Brinckerhoff Inc.. New Jersey I-80 and I-287 HOV Lane Case Study. Final Report for FHWA, Jul 2000
[7]Xu, G, X. P. Huang and P. Pant. Method for Estimating Capacity Reduction in 7 High-Occupanyc-Vehicle Lane Ingress and Egress Sections. Transportation Research Record, No.1678, Transportation Research Board, Washington, D.C.1999, pp.107-115
[8]Poppe, M. J., D. J. P. Hook, and K. M. Howell. Evaluation of High-Occupancy-Vehicle Lanes in Pheonex, Arizona. Transportation Research Record, No.1446, Transportation Research Board, Washington, D.C.1994, pp.1-7
[9]Newman, L., C. Nuworsoo, and A. D. May. Operational and Safety Experience with Freeway HOV Facilities in California. Transportation Research Record, No.1173, Transportation Research Board, Washington, D.C.1988, pp.18-24
[10]Brown, B. and L. Bolotin. HOV User Survey Washington State Freeway HOV System. In Proceedings of the 87th Annual Meeting of the Transportation Research Board, Washington, DC,2008
[11]Southern California Association of Govements (SCAG). Regional High-Occupancy Vehicle Lane System:Performance Study. Final Report. Nov.2004
[12]Parsons Brinckerhoff Inc.. HOV Performance Program Evaluation Report, for Los Angeles County. Final Report. Nov.2002
[13]C. Wellander and K. Leotta. Are High-Occupancy Vehicle Lanes Effective? Overview of High-Occupancy Vehicle Facilities Across North America. Transportation Research Record, No.1711, Transportation Research Board, Washington, D.C.2000, pp.23-30
[14]Dahlgren, J. High Occupancy Vehicle Lanes:Not Always More Effective than General Purpose Lanes. Transportation Research Part A, No.32,1998, pp.99-114
[15]Guin, A., M. Hunter and R. Guensler. Analysis of Reduction in Effective Capacities of High-Occupancy Vehicle Lanes Related to Traffic Behavior. Transportation Research Record, No.2065, Transportation Research Board, Washington, D.C.2008, pp.47-53
[16]Kwon, J. and P. Varaiya. Effectiveness of California's High Occupancy Vehicle (HOV) System. Transportation Research Part C, No.16,2008, pp.98-115
[17]Jang, K., et al. Safety Performance of High-Occupancy Vehicle (HOV) Facilities: Evaluation of HOV Lane Configurations in California. Transportation Research Record, No. 2099, Transportation Research Board, Washington, D.C.2009, pp.132-140
[18]Freeway Performance Measurement System, http://pems.eecs.berkeley.edu/. Accessed July 10th,2010
[19]Brownstone, D., et al. Evaluation of Incorporating Hybrid Vehicle Use of HOV Lanes. California PATH Research Report. UCB-ITS-PRR-2008-26,2008
[20]Transportation Research Board. Highway Capacity Manual 2000 (HCM 2000).2000
[21]Zar, J. H.. Biostatistical Analysis.4th edition. Prentice Hall, Upper Saddle River, NJ.1999
[22]Kwon, J. and P. Varaiya. Effectiveness of California's High Occupancy Vehicle (HOV) System. Transportation Research Part C, No.16,2008, pp.98-115
[23]Perrin, J., P. Wu, and P. T. Martin. Evaluating HOV Lanes in Salt Lake City, Utah. In Proceedings of the 83th Annual Meeting of the Transportation Research Board, Washington, DC,2004
[24]J. Nee, J. Ishimaru, and M. E. Hallenbeck. HOV Lane Performance Monitoring 2002 Report Vol I. TRAC, Wahsington, June 2004
[25]Poppe, M. J., D. J. P. Hook, and K. M. Howell. Evaluation of High-Occupancy-Vehicle Lanes in Pheonex, Arizona. Transportation Research Record, No.1446, Transportation Research Board, Washington, D.C.1994, pp.1-7
[26]Benz, R. J. and D. W. Fenno. Quantification of Travel Time Savings for Barrier Separated High-Occupancy Vehicle (HOV) Lanes During General Purpose Lane Incident
[27]Conditions. In Proceedings of the 85th Annual Meeting of the Transportation Research Board, Washington, DC,2006
[28]Newman, L., C. Nuworsoo, and A. D. May. Operational and Safety Experience with Freeway HOV Facilities in California. Transportation Research Record, No.1173, Transportation Research Board, Washington, D.C.1988, pp.18-24
[29]Skabardonis, A., et al.I-880 Field Experiment:Data-Base Development and Incident Delay Estimation Procedures. Transportation Research Record, No.1554, Transportation Research Board, Washington, D.C.1996, pp.204-212
[30]Skabardonis, A., P. Varaiya, and K. F. Petty and. Measuring Recurrent and Nonrecurrent Traffic Congestion. Transportation Research Record, No.1856, Transportation Research Board, Washington, D.C.2004, pp.118-124
[31]Kwon, J. and P. Varaiya, The Congestion Pie:Delay from Collisions, Potential Ramp Metering Gain and Access Demand. In Proceedings of the 84th Annual Meeting of the Transportation Research Board, Washington, DC,2005
[32]Lighthill, M. J. and G B. Whitham. On Kinematic Waves. I. Flood Movement in Long Rivers. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, Vol.229, No.1178,1955, pp.281-316
[33]Al-Deek, H., A. Garib, and A. E. Radwan. New Method for Estimating Freeway Incident Congestion. Transportation Research Record, No.1494, Transportation Research Board, Washington, D.C.1995
[34]Lindley, J.. A Methodology for Quantifying Urban Freeway Congestion. Transportation Research Record, No.1132, Transportation Research Board, Washington, D.C.1987, pp.25 1-7
[35]Jason, B. N., and A. Rathi. Economic Feasibility of Exclusive Vehicle Facilities. Transportation Research Record, No.1305, Transportation Research Board, Washington, D.C.1991, pp.201-214
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