CN102332122A - Layout optimization method for urban public bicycle rental stations - Google Patents
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Abstract
The invention relates to a layout optimization method for urban public bicycle rental stations. The method comprises the following steps of: firstly, establishing basic databases for regional lands, residential structures, trip modes and the like; then dividing traffic zones, and performing trip generation prediction and trip distribution prediction; and finally establishing a two-layer model which consists of an adaptive genetic algorithm and a mode sharing and traffic distribution combined feedback model for different layout schemes, solving, evaluating scheme results, and obtaining an optimal layout scheme after the final convergence of evaluated values to make regional trip cost and the construction cost of public bicycle system facilities the lowest. Compared with the prior art, in the method provided by the invention, the trip needs of residents and the supply of traffic facilities are coordinated, and the method has a wide application range and a high quantification extent, and can provide a scientific technical support for related decision making.
Description
Technical field
The present invention relates to city public bicycles lease point layout method, especially, belong to the traffic programme field the optimization of existing public bicycles lease point layout.
Background technology
Trip mode as a kind of health, energy-saving and environmental protection; Public bicycles offers convenience for the short distance trip on the one hand; Also enlarged the passenger flow attraction scope of public traffic station on the other hand, improved middle and long distance trip mode structure, practiced thrift path resource through transfer (B+R).Practice shows; The successful development public bicycles; Be unable to do without correct planning operation and propaganda guiding, unreasonable the unbalance of each lease point resource distribution that often cause of programming and distribution wherein causes that service level reduces, traveller runs off and the loss of enterprise and finally can't runing.Existing research to public bicycles lease point layout is main with macroscopic view and qualitative analysis, mainly concentrates in layout principle, signature analysis and the scale forecast, and is less to the research of quantitative model.On going result lacks the feedback of considering between public bicycles trip requirements and facility supply, and model needs a large amount of enquiry data supports simultaneously, and exploitativeness is not strong.
Summary of the invention
In order to overcome the deficiency of existing method; The present invention is from resident trip demand and transport infrastructure provision angle; Foundation is based on the city public bicycles lease point layout optimization model of bilayer planning, and the research model solution is for the decision-making of public bicycles lease point layout provides scientific basis.
The concrete scheme that the present invention adopts is following:
A kind of city public bicycles lease point layout optimization method may further comprise the steps:
1) at first sets up the database that is used for lower floor's forecast model and upper strata evaluate alternatives model;
2) carry out the trip generation of demand forecast and the distribution of going on a journey;
3) program simulation and evaluation obtain optimal case after judging convergence.
Wherein:
Database creation process in the described step 1) is following:
11) at first, confirm planned range,, select public bicycles lease point alternate location according to present situation and planned land use type; Secondly, be the basis, analyze socio-economic indicator, demarcate the correlation parameter of different travelers, comprise owning rate speed, expense, the comfort level of age, structure of earnings and each trip mode with the resident trip survey data;
12) site location, the service range of conventional public transport and track traffic in the clear and definite zone, the departure frequency of each public transport line, and the public transport in entering zone is on average taken advantage of the rate of carrying first.
Described step 2) trip generation and forecast of distribution process in are following:
21) divide inside and outside traffic zone based on the land used type, add up population and post number in each sub-district;
22) trip generates according to using ground structure, adopts the cross division method, the traveler of all ages and classes, trip purpose is predicted respectively predicted time is a morning peak;
23) trip distributes and adopts two constraint Gravity Models, and considers the externally distribution situation of trip separately.
Program simulation in the described step 3), evaluation and final plan deterministic process are following:
31) the initial scheme collection is to produce definition n public bicycles lease point placement scheme of population size down by computer random, and making it is the first generation of population;
32) each scheme is divided and the traffic distribution according to lower floor's model solution method mode of carrying out, the total trip cost that draws thus is through feeding back to layer model evaluation after the penalty correction;
33) if evaluation result restrains or reaches the maximum algebraically of population, be transferred to next step, otherwise, scenarios is carried out selection, intersection and variation in the self-adapted genetic algorithm; The update scheme collection is transferred to the next generation, returns step 32);
34) select the optimum scheme of evaluation result, as final plan.
The present invention adopts double-deck plan model on public bicycles lease point layout optimization problem, to crowd's modeling respectively of government planning department and two kinds of different targets of traveler.
(1) layer model under
Following layer model is in order to describe the selection of traveler in existing network upper type and path, and promptly mode is shared with traffic and being distributed.Be used for associated form and share the supernet that the network of traffic distribution is made up of public transport links, road net, bicycle net and sneakernet.In this network, trip mode and path that each traveler all will select the broad sense expense to economize most.Should upgrade impedance and the mode of feeding back to is shared in the model based on link flow after distributing each time.
Mode is shared the aspect; Because trip mode is more and relate to multimode transfer; Be IIA (the relevant independence of selecting) characteristic and hobby randomness limits of avoiding simple Logit (decilog) model to have, the present invention adopts mixed Logit (mixing decilog) model.
Minimum mode and the path of trip cost between terminus will be selected in traffic distribution aspect, each traveler.When network reached balance, traveler can't reduce the trip cost through change trip mode and path.The user equilibrium model has been realized theoretic optimum, yet in fact the user often makes a strategic decision based on idea trip cost at random, so adopt random user balance model (SUE).
(2) go up layer model
The optimal location scheme need be selected based on location trip requirements characteristic by government department when planning public bicycles lease point layout, make that total trip cost and Facilities Construction cost are minimum.Simultaneously, according to public bicycles lease point principle for layout, set up three constraint conditions: lease dot spacing, density and use amount.
For each placement scheme, following layer model obtains dispense flow rate according to scheme, and this result is fed back to layer model giving evaluation, and whether check satisfies constraint condition, and scheme set is screened and optimized, and concrete grammar is:
For following layer model, consider the multimode transfer, set up the supernet mode of carrying out and divide with traffic and distribute.Method for solving is:
Step 1: create network.According to public bicycles lease point scheme layout, set up supernet;
Step 2: computing impedance is also sought the shortest path of OD (origin and destination) to each folk prescription formula.The result seeks feasible multimode shortest path based on folk prescription formula shortest path, adopts floyd (Freud) algorithm.
Step 3: mode is divided.
Step 4: traffic distributes.Adopt straight average method to distribute, branch timing iteration each time all adopts STOCH (the multipath traffic distributes at random) algorithm to calculate.
For finding the solution of last layer model, make up the rational and effective scheme according to constraint condition, and the result is fed back to layer model down.The present invention selects self-adapted genetic algorithm to find the solution layer model, and placement scheme is represented by discrete scale-of-two gene data, and through selection, intersection and the variation of gene scheme carried out further exploration; For the scheme that does not meet constraint condition, reduce its selected probability through adaptive value punishment.
Compared with prior art; The present invention can with regional present situation resident trip survey or target year Travel Demand Forecasting the result be data bases; Carry out the planning and the evaluation of public bicycles layout; Plan as a whole trip requirements and facility and supplied with, planned as a whole traveler, government and planning department, tripartite interests and the demand of operating unit; Simultaneously, ripe traffic forecast Four-stage Method model supports is arranged, possess higher science and applicability.
Description of drawings
Fig. 1 is a city public bicycles lease point layout optimization method flow diagram;
Fig. 2 is regional abstract road network figure;
Fig. 3 is evolutionary process figure;
Fig. 4 is the optimal location conceptual scheme.
Embodiment
Be illustrated in figure 1 as city public bicycles lease point layout optimization method flow diagram in this embodiment, this method comprises the steps:
The first step: data are prepared
At first, confirm planned range,, select public bicycles lease point alternate location according to present situation and planned land use type; Secondly, be basis with the resident trip survey data, the analysis socio-economic indicator is demarcated the parameters such as owning rate speed, expense, comfort level of age, structure of earnings and each trip mode of different travelers.
The site location of conventional public transport and track traffic, service range in the clear and definite zone, the departure frequency of each public transport line, and the public transport in entering zone is on average taken advantage of the rate of carrying first.
Set up supernet, comprise road net, conventional bus-route network, rail transit network, bicycle net and sneakernet.
According to land used internal zone is divided, foundation goes out line direction and trip distance is divided outside traffic zone.The population of clear and definite each sub-district and post distribution situation.
Suppose certain inhabitation section planning construction public bicycles lease point in the about 3 square kilometres city of floor area, main passenger flow Distribution Center such as residential district, school, shopping square, park is alternate location.1 in distribution rail circuit in the zone, 2 of websites (square), 6 on routine bus line road, 26 of websites, abstract road network is made up of trunk roads, secondary distributor road (the non-separation of machine), branch road (the non-mixing of machine), track traffic and routine bus line road (dotted line), like Fig. 2.
Public transport is seen table 1 with external sub-district connected relation.Each trip mode technical indicator is seen table 2.
Table 1 public transport and external cell connected relation table
Table 2 trip mode technical indicator
Consider the influence of through trip, suppose trunk roads basis saturation degree 0.6, secondary distributor road 0.5, branch road 0.2.The peak hour travel amount accounts for full-time 12.5%.Build and the operation related data with reference to ground public bicycles systems such as Paris, Shanghai, Hangzhou, Wuhan; If be limited to 150m under the residential district public bicycles lease dot spacing; Density range is 2～4/km2, is limited to 10 under single lease point morning peak rent, the sum of returning the car, and construction cost is 200,000 yuan; 400 yuan/of vehicle acquisition costs, 5 years serviceable life.
Second step: demand forecast
With the traffic Four-stage Method is theoretical foundation, carries out resident's trip generation forecast and trip forecast of distribution.Here need trip be divided into intra-zone trip and externally trip of zone to the planning zone, consider the influence of through trip simultaneously road section traffic volume saturation degree in the zone.Predict the outcome like table 3.
Table 3 morning peak passenger flow OD
The 3rd step: program simulation and evaluation
Scheme set is to produce definition n public bicycles lease point placement scheme of population size down by computer random; Lower floor's model solution method mode of carrying out to each scheme proposes according to the present invention is divided and the traffic distribution, estimates feeding back to layer model after the total trip cost process penalty correction that draws thus, according to evaluation result; Adopt self-adapted genetic algorithm to find the solution to scenarios; Carry out selection, intersection and the variation of gene, the update scheme collection is transferred to the next generation.
Roulette strategy (roulette wheel selection) is adopted in the selection of gene, and promptly individual selection probability is relevant with fitness, extracts individuality with random chance and remains in the follow-on colony.Penalty increases progressively coefficient and gets 7.5, and the initial crossover probability of gene gets 0.9, and the variation probability gets 0.04.
Use the Matlab programming to realize the levels algorithm of double-deck plan model, and apply to this example.Obtain the final optimization pass scheme through the evolution of 100 generations.Evolutionary process sees Table 4, evolutionary process such as Fig. 3.
Table 4 evolutionary process table
| Evolutionary generation | Optimum individual | The optimal-adaptive degree | Average fitness |
| 1 | 00111100100001001110 | 33978 | 70632 |
| 2 | 11110101000000011111 | 32075 | 57104 |
| 3 | 01100001110010011110 | 31084 | 50365 |
| 4 | 11110101001100011110 | 29061 | 49386 |
| ... | ... | ... | ... |
| 98 | 00111100011011110000 | 23967 | 24114 |
| 99 | 00111100011011110000 | 23967 | 23995 |
| 100 | 00111100011011110000 | 23967 | 23981 |
The 4th step: confirm final plan
Carry out the simulation and the evaluation of scheme set repeatedly, up to evaluation of estimate convergence or reach maximum population algebraically, the scheme of selecting optimum evaluation of estimate is as final plan.
Population optimal-adaptive kilsyth basalt shows the fitness that each obtains for optimal case among Fig. 3, and the population fitness is on average represented the degree of evolving.Be evolved to the 30th generation kept stable, optimal case is as shown in Figure 4.
Claims (5)
1. city public bicycles lease point layout optimization method is characterized in that, this method may further comprise the steps:
1) at first sets up the database that is used for lower floor's forecast model and upper strata evaluate alternatives model;
2) carry out the trip generation of demand forecast and the distribution of going on a journey;
3) program simulation and evaluation obtain optimal case after judging convergence.
2. city according to claim 1 public bicycles lease point layout optimization method is characterized in that the database creation process in the described step 1) is following:
11) at first, confirm planned range,, select public bicycles lease point alternate location according to present situation and planned land use type; Secondly, be the basis, analyze socio-economic indicator, demarcate the correlation parameter of different travelers, comprise owning rate speed, expense, the comfort level of age, structure of earnings and each trip mode with the resident trip survey data;
12) site location, the service range of conventional public transport and track traffic in the clear and definite zone, the frequency of dispatching a car of each public transport line
Rate, and the public transport in entering zone is on average taken advantage of the rate of carrying first.
3. city according to claim 1 public bicycles lease point layout optimization method is characterized in that described step 2) in trip generation and forecast of distribution process following:
21) divide inside and outside traffic zone based on the land used type, add up population and post number in each sub-district;
22) trip generates according to using ground structure, adopts the cross division method, the traveler of all ages and classes, trip purpose is predicted respectively predicted time is a morning peak;
23) trip distributes and adopts two constraint Gravity Models, and considers the externally distribution situation of trip separately.
4. city according to claim 1 public bicycles lease point layout optimization method is characterized in that the program simulation in the described step 3), evaluation and final plan deterministic process are following:
31) the initial scheme collection is to produce definition n public bicycles lease point placement scheme of population size down by computer random, and making it is the first generation of population;
32) each scheme is divided and the traffic distribution according to lower floor's model solution method mode of carrying out, the total trip cost that draws thus is through feeding back to layer model evaluation after the penalty correction;
33) if evaluation result restrains or reaches the maximum algebraically of population, be transferred to next step, otherwise, scenarios is carried out selection, intersection and variation in the self-adapted genetic algorithm; The update scheme collection is transferred to the next generation, returns step 32);
34) select the optimum scheme of evaluation result, as final plan.
5. city according to claim 4 public bicycles lease point layout optimization method is characterized in that said lower floor model solution method comprises the steps:
Step 1: create network,, set up supernet according to public bicycles lease point scheme layout;
Step 2: computing impedance is also sought the shortest path of OD to each folk prescription formula, and the result seeks feasible multimode shortest path based on folk prescription formula shortest path, adopts the floyd algorithm;
Step 3: mode is divided;
Step 4: traffic distributes, and adopts straight average method to distribute, and branch timing iteration each time all adopts the STOCH algorithm to calculate.
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Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103198365A (en) * | 2013-04-08 | 2013-07-10 | 天津大学 | University campus public bike management optimization and evaluation method |
| CN103646132A (en) * | 2013-11-26 | 2014-03-19 | 华南理工大学 | Layout method of urban public bicycle leasing network |
| CN103956042A (en) * | 2014-04-21 | 2014-07-30 | 南京师范大学 | Public bike scheduling area intelligent partition method based on graph theory |
| CN104361398A (en) * | 2014-08-04 | 2015-02-18 | 浙江工业大学 | Method for predicting natural demands on public bicycle rental spots |
| CN104850900A (en) * | 2015-04-27 | 2015-08-19 | 北京工业大学 | Public bicycle system branch layout optimization complete set method |
| CN106980942A (en) * | 2017-04-18 | 2017-07-25 | 东南大学 | Calculate method of the bicycle free way to the coverage of public bicycles lease point |
| CN107067710A (en) * | 2017-04-21 | 2017-08-18 | 同济大学 | A kind of city bus running orbit optimization method for considering energy-conservation |
| CN107103701A (en) * | 2017-04-24 | 2017-08-29 | 北京航空航天大学 | Based on the mixed shared bicycle lease point site selecting method multiplied under urban public tranlport system |
| CN107800771A (en) * | 2017-09-19 | 2018-03-13 | 中铁第四勘察设计院集团有限公司 | Tramcar and shared bicycle integrated transfer system |
| CN108985511A (en) * | 2018-07-11 | 2018-12-11 | 华南理工大学 | A kind of public transportation lane layout optimization method based on SUE |
| CN109146264A (en) * | 2018-08-02 | 2019-01-04 | 吉林财经大学 | A kind of configuration method and system of vaccine resource |
| CN109615850A (en) * | 2018-12-27 | 2019-04-12 | 连尚（新昌）网络科技有限公司 | It is a kind of for determining the method and apparatus of the transit riding information of user |
| CN109993349A (en) * | 2019-03-11 | 2019-07-09 | 同济大学 | A kind of optimization method and device of city refuge addressing |
| CN110288198A (en) * | 2019-05-29 | 2019-09-27 | 东南大学 | Lease bicycle traffic facility bearing capacity Measurement Method based on traffic zone |
| CN110309953A (en) * | 2019-05-28 | 2019-10-08 | 特斯联（北京）科技有限公司 | Using the city safety monitoring layout system and method for object mobility forecast of distribution |
| CN110599074A (en) * | 2019-07-18 | 2019-12-20 | 广州市交通规划研究院 | Site selection method for electric vehicle charging facility construction |
| EP3644242A1 (en) | 2018-10-23 | 2020-04-29 | Honda Research Institute Europe GmbH | System and method for optimizing a service station layout |
| CN111984924A (en) * | 2020-07-07 | 2020-11-24 | 东南大学 | Method for evaluating influence of public bicycle leasing policy on regional bicycle safety |
| CN114418466A (en) * | 2022-03-30 | 2022-04-29 | 北京市智慧交通发展中心(北京市机动车调控管理事务中心) | Method and device for evaluating influence degree of bus stop setting on bicycle traffic |
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- 2011-10-18 CN CN201110316200A patent/CN102332122A/en active Pending
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| CN103198365A (en) * | 2013-04-08 | 2013-07-10 | 天津大学 | University campus public bike management optimization and evaluation method |
| CN103646132A (en) * | 2013-11-26 | 2014-03-19 | 华南理工大学 | Layout method of urban public bicycle leasing network |
| CN103646132B (en) * | 2013-11-26 | 2016-10-05 | 华南理工大学 | A kind of city public bicycle lease site layout method |
| CN103956042B (en) * | 2014-04-21 | 2016-02-24 | 南京师范大学 | A kind of intelligence of the public bicycles dispatcher-controlled territory based on graph theory division methods |
| CN103956042A (en) * | 2014-04-21 | 2014-07-30 | 南京师范大学 | Public bike scheduling area intelligent partition method based on graph theory |
| CN104361398A (en) * | 2014-08-04 | 2015-02-18 | 浙江工业大学 | Method for predicting natural demands on public bicycle rental spots |
| CN104850900A (en) * | 2015-04-27 | 2015-08-19 | 北京工业大学 | Public bicycle system branch layout optimization complete set method |
| CN104850900B (en) * | 2015-04-27 | 2018-08-28 | 北京工业大学 | A kind of complete method of city-bike system net point layout optimization |
| CN106980942A (en) * | 2017-04-18 | 2017-07-25 | 东南大学 | Calculate method of the bicycle free way to the coverage of public bicycles lease point |
| CN106980942B (en) * | 2017-04-18 | 2021-03-23 | 东南大学 | Method for measuring and calculating influence range of bicycle express way on public bicycle rental spots |
| CN107067710A (en) * | 2017-04-21 | 2017-08-18 | 同济大学 | A kind of city bus running orbit optimization method for considering energy-conservation |
| CN107103701A (en) * | 2017-04-24 | 2017-08-29 | 北京航空航天大学 | Based on the mixed shared bicycle lease point site selecting method multiplied under urban public tranlport system |
| CN107800771A (en) * | 2017-09-19 | 2018-03-13 | 中铁第四勘察设计院集团有限公司 | Tramcar and shared bicycle integrated transfer system |
| CN107800771B (en) * | 2017-09-19 | 2020-09-11 | 中铁第四勘察设计院集团有限公司 | Tramcar and shared bicycle integrated transfer system |
| CN108985511A (en) * | 2018-07-11 | 2018-12-11 | 华南理工大学 | A kind of public transportation lane layout optimization method based on SUE |
| CN109146264A (en) * | 2018-08-02 | 2019-01-04 | 吉林财经大学 | A kind of configuration method and system of vaccine resource |
| CN109146264B (en) * | 2018-08-02 | 2022-04-08 | 吉林财经大学 | Vaccine resource configuration method and system |
| EP3644242A1 (en) | 2018-10-23 | 2020-04-29 | Honda Research Institute Europe GmbH | System and method for optimizing a service station layout |
| CN109615850A (en) * | 2018-12-27 | 2019-04-12 | 连尚（新昌）网络科技有限公司 | It is a kind of for determining the method and apparatus of the transit riding information of user |
| CN109993349A (en) * | 2019-03-11 | 2019-07-09 | 同济大学 | A kind of optimization method and device of city refuge addressing |
| CN110309953A (en) * | 2019-05-28 | 2019-10-08 | 特斯联（北京）科技有限公司 | Using the city safety monitoring layout system and method for object mobility forecast of distribution |
| CN110288198A (en) * | 2019-05-29 | 2019-09-27 | 东南大学 | Lease bicycle traffic facility bearing capacity Measurement Method based on traffic zone |
| CN110599074A (en) * | 2019-07-18 | 2019-12-20 | 广州市交通规划研究院 | Site selection method for electric vehicle charging facility construction |
| CN111984924A (en) * | 2020-07-07 | 2020-11-24 | 东南大学 | Method for evaluating influence of public bicycle leasing policy on regional bicycle safety |
| CN114418466A (en) * | 2022-03-30 | 2022-04-29 | 北京市智慧交通发展中心(北京市机动车调控管理事务中心) | Method and device for evaluating influence degree of bus stop setting on bicycle traffic |
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Application publication date: 20120125 |