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RAM: A normative tool for transit route planning
216
BibliographicSection
characteristic of trallic systems and their control-the independence and in a sense the uncontrolability of the driver. It is important to note that this objective is not explicitly evaluated from the queuing approach. With the tic simulation this objective can be explicitly evaluated within the context of the.design process. A second requirement for an evaluation with a simulation model is the specification of a traffic scenario. This scenario is implemented by defining a set of three simulation runs: A base line run which establishes roadway operations under no incident and no control conditions; An incident run which establishes roadway operations under uncontrolled, incident conditions; and A control run which establishes for each algorithm to be tested roadway operations under controlled, incident conditions. Sets of these runs were made for various combinations of the following parameters: roadway demand volume, incident location, incident severity, volume of intercity trallic, and diversion fraction. The threshold algorithms examined in this paper have been specified for further testing and implementation on the 195/HlT/I695 roadway system as part of the Federal Highway Administration study program “The Diversion of Inter-City TralIic at a Single Point”. It is important to note that the algorithms satisfy the three operational objectives. They satisfy the first objective on freeway operation by quickly returning the roadways, after an incident has occurred, to their pre-incident non-congested condition. By satisfying the second objective (a 30% reduction in system delay experienced by the intercity motorists), the algorithms provide the positive benefit to the group of motorists who provide the control authority necessary for actual system operation. Finally, the third objective is satisfied by realizing a 20% reduction in total system delay over the uncontrolled operation of the system during the incident. Taken together these approaches address the need for generalized formal procedures which can be used in the development of control policies suitable for the real time operation of large scale freeway systems. These policies, to be accepted by the traffic community, must be shown to be implementable on actual roadway systems with quantifiable benefits for the motorist. Due to the complexity of these systems, in both space and time, analytical approaches alone cannot provide the required degree of acceptance. They can, however, provide the initial insight into system operation. At this point a simulation approach with appropriate validation can provide a more complete ‘real world’ evaluation. Combining the two approaches results in an optimum design and evaluation methodology.
.An Analysis of Elevator Operation in Modemte Height Buildings, Beryl Gamse, Foyers, Woodlands,
Southampton SO4 2GN, England (Dissertation in the Department of Civil Engineering, University of Caiifornia, Berkeley, CA 94720, available from the Institute of Transportation Studies, Dissertation Series UCB-ITSDS-78-2).
This study considers the operation of an elevator system serving a medium height (10-15 stories) building during periods of moderate to heavy traffic in one or both directions, with the bulk of the tra5c having one trip end at the lobby. When a system has multiple cars that serve all stops in the building and no attempt is made to control the spacing between cars, the only stable equilibrium for the vehicles is a fairly compact bunch or platoon. The level of service provided by an elevator system for various combinations of number of cars and demand is investigated when bunching occurs and when various strategies are used to control or eliminate it. The measure of the level of service is the mean passenger in-system time, i.e. the sum of the mean waiting and travel times. A model describing the motion of a single car system is developed and a formula is given for determining the approximate equilibrium characteristics of the system for arbitrary traffic distributions and demand levels. These results are used as the basis for simple analytical models used to describe the operation of multiple car systems. A computer simulation is used to verify the single elevator analytical model and to determine the multiple car system service levels yhen the simple models are inappropriate. Three basic strategies are considered: (a) regulating vehicle headways by imposing a minimum headway at a single control point, (b) partitioning the building into zones, each served by a single car, and (c) doing nothing, allowing bunching to occur. The system characteristics for which each strategy is best are discussed. It is shown that for a wide variety of conditions controlling headways to prevent pairing may slow the system sufficiently that the mean in-system time of passengers is less when cars are uncontrolled and allowed to bunch. Zoning strategies are shown generally to provide the best level of service except at low tra!Xc intensities, even in the 10-15 story buildings considered in this study.
RAM: A Nonnative Tool for Transit Route Planning,
Leonard Goldstein (Dissertation in the Department of Transportation Planning and Engineering, Polytechnic Institute of New York, New York, NY 11201). This dissertation deals with the development of a Route Allocation Model (RAM), a practical methodology to assist the transit planner in the development of transit routes. The model is multi-purpose in that it may be utilized for standard transit route planning oi for transit route planning under a scenario of special interest. These scenarios may include such items as limited autoenvironment planning due to fuel and/or pollution restrictions, standard Transportation Systems Management Element applications, and the updating of currently outdated transit routes to reflect present day transportation needs. The model has been designed to facilitate transit routing in a forward planning manner. Contrary to conventional route planning where routes are evaluated after
BibliographicSection manual bus installation on a computerized network (i.e. a backward planning approach), the RAM outputs transit routes as a function of given criterion with an existing network and associated triptable. This methodology is designed with a high degree of flexibility, so that it could be used in various areas, both rural and metropolitan, utilizing a forward planning approach. In existing computerized route planning, a route is established in a computer-coded network, and a simulation performed. The impact upon the traveler’s walking time, transfer time, overall time, etc. is observed. If the route is considered unsatisfactory by the transit route planner, the route is redefined in the network, and the procedure repeated. If the route appears to be satisfactory to the transit route planner, the route may be physically implemented. It should be noted that the transit route.planner decides to implement the route or to repeat the procedure until an acceptable solution is found. Thus, the conventional route planning methodology is a backwards planning procedure, in that it is always necessary to “go back” and keep repeating the process of placing a route and then evaluating it, where the transit route planner is providing this “feedback” process. Unlike conventional route planning (i.e. the backward planning approach), the forward planning approach utilizes design characteristics which the transit route planner desires to have incorporated into the overall transit system. These characteristics are given as input to the process, and a system of transit links is output accordingly. It is interesting to note that in this process there is no human “feedback” element. The routes are generated, given criteria about the desired transit service. The result is intended to be a sound multimodal infrastructure which represents the needs of the transportation users. The RAM is designed to be used as a normative tool for the transit route planner, due to its inherent flexibility and computational efficiency. Unlike other techniques, the RAM is able to process rather large networks. A corridor analysis technique developed within the scope of the RAM allows for the manageability of these large complex networks. In addition, the RAM has the ability to complement existing high capital investment transit (i.e. subways and commuter railroad) with surface transit (bus) service. Also developed within the scope of this dissertation is a quality of service index, which is used to assess the disutility of a travel path as compared to another travel path. This disutility index, known as ZK, is constructed from items such as walking time, transfer time, number of transfers, total time and the volume on a particular O-D interchange. Once these ZK disutility indices have been calculated for all interchanges in the network, the RAM may start allocating routes, beginning with the O-D interchanges which have the worst ZK disutility indices. A case study is used for application of the RAM methodology. This case study is Queens, N.Y.C., under a hypothetical scenario of limited auto environment, which could occur in the event of an air pollution or energy crisis. A massive data base is used as a triptable for the
217
681 zone netuiork; the RAM applied; and results presented to de&mine an approximate cost of the transit route system generated. Because of the methodology’s dependence upon the Urban Transportation Planning System (UTPS) for its network analysis capability, it is assumed that there is familiarity with this suite of programs.
Dynamic Programming Algorithms for Specially Structured Sequencing and Routing Problems in Tmnsportation, Harilaos N. Psaraftis, Department of Ocean Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139. In this thesis, a number of dynamic programming algorithms are developed for several sequencing and routing problems in Transportation that exhibit special structures. First, three versions of the problem of sequencing aircraft landings at an airport are examined. In these, two alternative objectives are considered: How to land all of a prescribed set of airplanes as soon as possible, or, alternatively, how to minimize the total passenger waiting time. All these three versions are “static”, namely no intermediate aircraft arrivals are accepted until our initial set of airplanes land. The versions examined are (a) the single runway-unconstrained case, (b) the single runway-Constrained Position Shifting (CPS) case and (c) the two-runway-unconstrained case. In the unconstrained case no priority considerations exist for the airplanes of our system. By contrast, CPS prohibits the shifting of any particular airplane by more than a prespecified number of positions (MPS) from its initial position in the queue. Au three algorithms exploit the fact that the airplanes in our system can be classified into a relatively small number of distinct categories and thus, realize drastic savings in computational effort, which is shown to be a polynomially bounded function of the number of airplanes per category. The CPS problem is formulated in (b) in a recursive way, so that for any value of MPS, the computational effort remains polynomially bounded as described above. We then proceed to examine two versions of the dial-a-ride problem. These versions involve the dispatching of a vehicle to carry certain customers from distinct origins to distinct destinations usually in an urban environment. All customers request immediate service by telephone. Vehicle capacity constraints and priority rules similar to CPS are part of our problem. We study a generalized objective to minimize a weighted combination of the time to service the customers and their corresponding total disutility. In the “static” version, no intermediate customer requests are considered until the service of all initial customers is accomplished. In the “dynamic” version, an update is made each time a new customer requests service. The algorithms for both cases are exponential but perform asymptotically better than the classical dynamic programming algorithm applied to a Travelling Salesman Problem of the same size.
BibliographicSection
characteristic of trallic systems and their control-the independence and in a sense the uncontrolability of the driver. It is important to note that this objective is not explicitly evaluated from the queuing approach. With the tic simulation this objective can be explicitly evaluated within the context of the.design process. A second requirement for an evaluation with a simulation model is the specification of a traffic scenario. This scenario is implemented by defining a set of three simulation runs: A base line run which establishes roadway operations under no incident and no control conditions; An incident run which establishes roadway operations under uncontrolled, incident conditions; and A control run which establishes for each algorithm to be tested roadway operations under controlled, incident conditions. Sets of these runs were made for various combinations of the following parameters: roadway demand volume, incident location, incident severity, volume of intercity trallic, and diversion fraction. The threshold algorithms examined in this paper have been specified for further testing and implementation on the 195/HlT/I695 roadway system as part of the Federal Highway Administration study program “The Diversion of Inter-City TralIic at a Single Point”. It is important to note that the algorithms satisfy the three operational objectives. They satisfy the first objective on freeway operation by quickly returning the roadways, after an incident has occurred, to their pre-incident non-congested condition. By satisfying the second objective (a 30% reduction in system delay experienced by the intercity motorists), the algorithms provide the positive benefit to the group of motorists who provide the control authority necessary for actual system operation. Finally, the third objective is satisfied by realizing a 20% reduction in total system delay over the uncontrolled operation of the system during the incident. Taken together these approaches address the need for generalized formal procedures which can be used in the development of control policies suitable for the real time operation of large scale freeway systems. These policies, to be accepted by the traffic community, must be shown to be implementable on actual roadway systems with quantifiable benefits for the motorist. Due to the complexity of these systems, in both space and time, analytical approaches alone cannot provide the required degree of acceptance. They can, however, provide the initial insight into system operation. At this point a simulation approach with appropriate validation can provide a more complete ‘real world’ evaluation. Combining the two approaches results in an optimum design and evaluation methodology.
.An Analysis of Elevator Operation in Modemte Height Buildings, Beryl Gamse, Foyers, Woodlands,
Southampton SO4 2GN, England (Dissertation in the Department of Civil Engineering, University of Caiifornia, Berkeley, CA 94720, available from the Institute of Transportation Studies, Dissertation Series UCB-ITSDS-78-2).
This study considers the operation of an elevator system serving a medium height (10-15 stories) building during periods of moderate to heavy traffic in one or both directions, with the bulk of the tra5c having one trip end at the lobby. When a system has multiple cars that serve all stops in the building and no attempt is made to control the spacing between cars, the only stable equilibrium for the vehicles is a fairly compact bunch or platoon. The level of service provided by an elevator system for various combinations of number of cars and demand is investigated when bunching occurs and when various strategies are used to control or eliminate it. The measure of the level of service is the mean passenger in-system time, i.e. the sum of the mean waiting and travel times. A model describing the motion of a single car system is developed and a formula is given for determining the approximate equilibrium characteristics of the system for arbitrary traffic distributions and demand levels. These results are used as the basis for simple analytical models used to describe the operation of multiple car systems. A computer simulation is used to verify the single elevator analytical model and to determine the multiple car system service levels yhen the simple models are inappropriate. Three basic strategies are considered: (a) regulating vehicle headways by imposing a minimum headway at a single control point, (b) partitioning the building into zones, each served by a single car, and (c) doing nothing, allowing bunching to occur. The system characteristics for which each strategy is best are discussed. It is shown that for a wide variety of conditions controlling headways to prevent pairing may slow the system sufficiently that the mean in-system time of passengers is less when cars are uncontrolled and allowed to bunch. Zoning strategies are shown generally to provide the best level of service except at low tra!Xc intensities, even in the 10-15 story buildings considered in this study.
RAM: A Nonnative Tool for Transit Route Planning,
Leonard Goldstein (Dissertation in the Department of Transportation Planning and Engineering, Polytechnic Institute of New York, New York, NY 11201). This dissertation deals with the development of a Route Allocation Model (RAM), a practical methodology to assist the transit planner in the development of transit routes. The model is multi-purpose in that it may be utilized for standard transit route planning oi for transit route planning under a scenario of special interest. These scenarios may include such items as limited autoenvironment planning due to fuel and/or pollution restrictions, standard Transportation Systems Management Element applications, and the updating of currently outdated transit routes to reflect present day transportation needs. The model has been designed to facilitate transit routing in a forward planning manner. Contrary to conventional route planning where routes are evaluated after
BibliographicSection manual bus installation on a computerized network (i.e. a backward planning approach), the RAM outputs transit routes as a function of given criterion with an existing network and associated triptable. This methodology is designed with a high degree of flexibility, so that it could be used in various areas, both rural and metropolitan, utilizing a forward planning approach. In existing computerized route planning, a route is established in a computer-coded network, and a simulation performed. The impact upon the traveler’s walking time, transfer time, overall time, etc. is observed. If the route is considered unsatisfactory by the transit route planner, the route is redefined in the network, and the procedure repeated. If the route appears to be satisfactory to the transit route planner, the route may be physically implemented. It should be noted that the transit route.planner decides to implement the route or to repeat the procedure until an acceptable solution is found. Thus, the conventional route planning methodology is a backwards planning procedure, in that it is always necessary to “go back” and keep repeating the process of placing a route and then evaluating it, where the transit route planner is providing this “feedback” process. Unlike conventional route planning (i.e. the backward planning approach), the forward planning approach utilizes design characteristics which the transit route planner desires to have incorporated into the overall transit system. These characteristics are given as input to the process, and a system of transit links is output accordingly. It is interesting to note that in this process there is no human “feedback” element. The routes are generated, given criteria about the desired transit service. The result is intended to be a sound multimodal infrastructure which represents the needs of the transportation users. The RAM is designed to be used as a normative tool for the transit route planner, due to its inherent flexibility and computational efficiency. Unlike other techniques, the RAM is able to process rather large networks. A corridor analysis technique developed within the scope of the RAM allows for the manageability of these large complex networks. In addition, the RAM has the ability to complement existing high capital investment transit (i.e. subways and commuter railroad) with surface transit (bus) service. Also developed within the scope of this dissertation is a quality of service index, which is used to assess the disutility of a travel path as compared to another travel path. This disutility index, known as ZK, is constructed from items such as walking time, transfer time, number of transfers, total time and the volume on a particular O-D interchange. Once these ZK disutility indices have been calculated for all interchanges in the network, the RAM may start allocating routes, beginning with the O-D interchanges which have the worst ZK disutility indices. A case study is used for application of the RAM methodology. This case study is Queens, N.Y.C., under a hypothetical scenario of limited auto environment, which could occur in the event of an air pollution or energy crisis. A massive data base is used as a triptable for the
217
681 zone netuiork; the RAM applied; and results presented to de&mine an approximate cost of the transit route system generated. Because of the methodology’s dependence upon the Urban Transportation Planning System (UTPS) for its network analysis capability, it is assumed that there is familiarity with this suite of programs.
Dynamic Programming Algorithms for Specially Structured Sequencing and Routing Problems in Tmnsportation, Harilaos N. Psaraftis, Department of Ocean Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139. In this thesis, a number of dynamic programming algorithms are developed for several sequencing and routing problems in Transportation that exhibit special structures. First, three versions of the problem of sequencing aircraft landings at an airport are examined. In these, two alternative objectives are considered: How to land all of a prescribed set of airplanes as soon as possible, or, alternatively, how to minimize the total passenger waiting time. All these three versions are “static”, namely no intermediate aircraft arrivals are accepted until our initial set of airplanes land. The versions examined are (a) the single runway-unconstrained case, (b) the single runway-Constrained Position Shifting (CPS) case and (c) the two-runway-unconstrained case. In the unconstrained case no priority considerations exist for the airplanes of our system. By contrast, CPS prohibits the shifting of any particular airplane by more than a prespecified number of positions (MPS) from its initial position in the queue. Au three algorithms exploit the fact that the airplanes in our system can be classified into a relatively small number of distinct categories and thus, realize drastic savings in computational effort, which is shown to be a polynomially bounded function of the number of airplanes per category. The CPS problem is formulated in (b) in a recursive way, so that for any value of MPS, the computational effort remains polynomially bounded as described above. We then proceed to examine two versions of the dial-a-ride problem. These versions involve the dispatching of a vehicle to carry certain customers from distinct origins to distinct destinations usually in an urban environment. All customers request immediate service by telephone. Vehicle capacity constraints and priority rules similar to CPS are part of our problem. We study a generalized objective to minimize a weighted combination of the time to service the customers and their corresponding total disutility. In the “static” version, no intermediate customer requests are considered until the service of all initial customers is accomplished. In the “dynamic” version, an update is made each time a new customer requests service. The algorithms for both cases are exponential but perform asymptotically better than the classical dynamic programming algorithm applied to a Travelling Salesman Problem of the same size.