CN105096622B - A kind of dynamic route guidance method communicated based on bus or train route - Google Patents

Abstract

The invention relates to the fields of vehicle-road coordination technology and traffic guidance technology, in particular to a method for dynamically guiding a driver's travel path through information interaction between a vehicle-mounted device and a roadside device. The present invention proposes a dynamic route guidance method based on vehicle-road communication. The method uses the vehicle as the source of traffic information collection, and interacts with the vehicle-mounted equipment and roadside equipment to extract and update the traffic information of the road network under the jurisdiction of the roadside equipment. At the same time, the roadside equipment uploads the traffic flow operation status parameters of the road network under its jurisdiction to the central equipment at a certain time interval. Based on the traffic flow status information of the entire road network, the central device provides K initial optimal routes for the driver to choose. When the travel vehicle enters the road network under the jurisdiction of the roadside device, the roadside device The current traffic flow operation status provides the optimal travel route and information services in the road network under its jurisdiction for travel vehicles.

Description

A dynamic route guidance method based on vehicle-road communication

technical field

The invention relates to the field of vehicle-road coordination technology and traffic guidance technology, in particular to a method for dynamically guiding a driver's travel path through information interaction between vehicle-mounted equipment and roadside equipment.

technical background

At present, the dynamic traffic guidance system based on real-time road traffic information is mainly divided into distributed guidance and central guidance. Distributed guidance means that the traffic information center provides the global dynamic traffic information of the road network to the vehicle-mounted terminal equipment through the wireless communication network, and the vehicle-mounted terminal equipment calculates the best driving route by itself according to the driver's travel starting point and travel destination. However, the distributed guidance method has problems such as large amount of dynamic traffic information communication, large consumption of vehicle terminal computing resources, long time for updating road network traffic information, and serious communication network load. At the same time, research data show that: when more than 1/3 of the road network When vehicles adopt distributed guidance, it is easy to cause the induced vehicles to drive to uncongested routes, resulting in new traffic congestion, that is, traffic congestion transfer.

The central guidance is that the traffic information center calculates the best driving path between all point pairs of the road network from the perspective of the overall road network based on the real-time road traffic information of the road network, starting from balancing the road network load and preventing traffic congestion, through wireless The communication network provides the optimal travel route for each vehicle-mounted terminal device on the road network, and the vehicle-mounted terminal device guides the driver to take the optimal travel route according to the received route information. Although the central guidance method can effectively avoid the occurrence of traffic congestion and transfer, the traffic information center requires powerful, real-time, high-frequency computing power, the traffic information center is heavily loaded and difficult to maintain, and it does not consider the dynamic characteristics of the driver's travel route selection and The driver's induction obedience rate causes the induction obedience rate to be low, cannot really play the purpose of alleviating urban traffic congestion and congestion.

Whether it is distributed guidance or central guidance, it is necessary to install a large number of traffic information detection devices in the entire road network to detect and monitor road traffic operating parameters and operating conditions in all time and space. It requires a lot of capital and equipment to ensure traffic guidance. Full-time, high-reliability, and high-precision operation of the system.

Contents of the invention

Aiming at the problems that the current dynamic traffic guidance system installs a large number of traffic detection devices in the road network, the load of the traffic information communication network is heavy, and the calculation amount of the traffic information center is large, the present invention proposes a dynamic path guidance method based on vehicle-road communication. Taking the vehicle as the source of traffic information collection, the vehicle-mounted equipment and the roadside equipment interact with traffic information to extract and update the traffic flow operating status parameters of the road network under the jurisdiction of the roadside equipment, and the roadside equipment will update the traffic flow status parameters of the road network under the jurisdiction of the roadside equipment at a certain time interval. The traffic flow operation status parameters of the road network are uploaded to the central device. Based on the traffic flow status information of the entire road network, the central device provides K initial optimal routes for the driver to choose. When the travel vehicle enters the road network under the jurisdiction of the roadside device, the roadside device The current traffic flow operation status provides the optimal travel route and information services in the road network under its jurisdiction for travel vehicles, so as to ensure the dynamic characteristics and real-time performance of road network traffic information, and provide real-time adjustment capabilities for changes in travel routes.

The technical solution of the present invention is mainly composed of three parts: on-board device (On-Board Device, OBD), roadside device (Road-Side Device, RSD), and center device (Center Control Device, CCD). The distribution structure of the device is shown in the figure 1. A dynamic path induction method based on vehicle-road communication proposed by the present invention is characterized in that it mainly includes the following steps:

1) Vehicle equipment

The on-board equipment is installed on the multimedia dashboard of the vehicle cockpit, and is mainly used to obtain travel information such as the vehicle's travel starting point, travel terminal, GPS information (accuracy, latitude, instantaneous speed, direction angle, etc.), and at the same time transmit the travel information through the wireless communication network. Transmission to roadside equipment. And receive traffic information, optimal travel route information, etc. sent by roadside equipment and central equipment.

2) Roadside equipment

The roadside equipment is installed at the intersection of the urban road network, and the grid distribution is carried out in the urban road network according to the communication coverage of the roadside equipment, as shown in Figure 2. Roadside equipment is mainly used to obtain GPS information and path information of vehicles operating within the scope of its jurisdictional road network, and to estimate the traffic flow operating status information of the road network under the jurisdiction of roadside equipment, including average road travel time and average road speed. Wait. At the same time, it provides the optimal travel route and traffic information services within the scope of the road network for vehicles entering the scope of the road network under its jurisdiction.

3) Central equipment

The central equipment is installed in the traffic information center or traffic command center. It mainly obtains the road network traffic flow operation status parameters of each roadside device through the optical fiber network or wireless communication network, so as to collect and store the traffic flow operation status information of the entire road network. At the same time, According to the running state of the road network traffic flow, K initial optimal paths are provided for the vehicles preparing to travel.

Description of drawings

Figure 1: A structural diagram of a dynamic path guidance system based on vehicle-road communication;

Figure 2: Road network layout of roadside equipment and road network coverage under its jurisdiction;

Figure 3: The weight tree assignment diagram of the central equipment road section;

Figure 4: Location division map of road sections;

Figure 5: The initial optimization path of central equipment and the optimization path of roadside equipment.

detailed description

A dynamic path guidance method based on vehicle-road communication described in the present invention is mainly composed of three parts: vehicle-mounted equipment, roadside equipment, and central equipment. The on-board equipment is mainly used to obtain travel information such as the starting point, destination, running track, and running speed of the vehicle. The roadside equipment is mainly used to extract the travel information of vehicles, estimate the traffic flow operation status information of the road network under its jurisdiction, and provide the optimal route information for vehicles entering the road network under the jurisdiction of the roadside equipment to travel within the scope of the road network and traffic information services. The central equipment is mainly used to obtain the traffic flow operation status information of the road network under the jurisdiction of different roadside devices in the road network, collect and store the traffic flow operation status information of the entire road network, and at the same time, prepare the vehicles for travel according to the traffic flow status information of the entire road network. Running status information, providing K (K is generally 3) initial optimal paths. The on-board equipment, roadside equipment, and central equipment jointly realize the acquisition of the operating status of road network traffic flow and the dynamic guidance of the driver's travel path. A dynamic route induction method based on vehicle-road communication proposed by the present invention can be described as including two core functions of road network traffic information acquisition and travel route dynamic optimization, and the specific workflow is as follows:

1) Acquisition of road network traffic information

(1) Vehicle equipment

During the operation of the vehicle, the on-board equipment obtains the vehicle GPS information VEH_GPS (specifically including GPS time, longitude, latitude, instantaneous speed and direction angle) through the built-in GPS module at a certain time interval VEH_T, and at the same time transmits VEH_GPS and vehicle information VEH_ID through the on-board equipment The built-in wireless communication module transmits to adjacent roadside equipment.

(2) Roadside equipment

The roadside equipment receives the VEH_GPS and VEH_ID information sent by the vehicle equipment, and uses the vehicle VEH_ID as the identification number in the built-in database of the roadside equipment, and uses the GPS time of VEH_GPS as the index number to track the vehicle's running track in the road network under the jurisdiction of the roadside equipment data storage.

The roadside equipment performs map matching processing on the VEH_GPS vehicle trajectories of all vehicles running in the road network under the jurisdiction of the roadside equipment at a certain time interval RSD_T, and extracts the travel time of each vehicle on the road section of the road network under the jurisdiction of the roadside equipment VEH_LT _i,j (VEH_LT _i,j is the segment travel time of the i-th vehicle passing through the j-th road segment of the road network under the jurisdiction of the road-side equipment within the road-side equipment information processing time interval RSD_T). Then the average travel time of the road section of the road network under the jurisdiction of the roadside equipment is:

Among them: RSD_LT _j is the average travel time of the jth road section of the road network under the jurisdiction of the roadside equipment; N is the roadside equipment information processing time interval RSD_T through the operation of the jth road section in the road network under the jurisdiction of the roadside equipment total number of vehicles.

For vehicles whose roadside equipment information processing time interval RSD_T leaves the road network area under the jurisdiction of the roadside equipment, when the vehicle leaves the road network area under the jurisdiction of the roadside equipment, the roadside equipment reads from the built-in database. Carry out map matching on the running trajectory data of the road network under the jurisdiction, and extract the travel time VEH_OLT _i,j of the vehicle in each section of the road network under the jurisdiction of the roadside equipment (VEH_OLT _i,j is the information processing time interval RSD_T of the roadside equipment and leave the roadside equipment place The travel time of the i-th vehicle on the j-th road segment of the road network under the jurisdiction of the road-side equipment by the vehicle under the jurisdiction of the road network). Then the average travel time of the road section of the road network under the jurisdiction of the roadside equipment is:

Among them: RSD_OLT _j is the average travel time of the jth road section of the road network under the jurisdiction of the roadside equipment; N is the roadside equipment information processing time interval RSD_T that leaves the road network under the jurisdiction of the roadside equipment through the jth road section total number of vehicles.

Since the roadside equipment extracts the travel time of the road section of the vehicles operating on the road network under the jurisdiction of the roadside equipment at the time interval RSD_T, it belongs to the fixed-period information processing, and the information has a relative lag, which is mainly for the route guidance service in the next time interval; and For vehicles leaving the road network under the jurisdiction of the roadside equipment at the time interval RSD_T, the extraction of road section travel time belongs to irregular and real-time dynamic information processing, and the information is relatively real-time. Dynamic update, as the average travel time of the road segment at the current moment, namely:

RSD_LT _j (t) = α·RSD_LT _j (RSD_T-1)+β·RSD_OLT _j (t)

Among them: RSD_LT _j (t) is the average travel time of the jth road segment of the road network under the jurisdiction of the roadside equipment at the current time t within the current time interval RSD_T; RSD_LT _j (RSD_T-1) is the previous time interval RSD_T roadside equipment The average travel time of the jth road section of the road network under its jurisdiction; RSD_OLT _j (t) is the vehicle leaving the road network under the jurisdiction of the roadside equipment at the current time t within the current time interval RSD_T passing through the jth road network under the jurisdiction of the roadside equipment The average travel time of the road segment; α and β are the adjustment coefficients of the travel time of the road segment.

(3) Central equipment

The central device extracts the average travel time of each road section of the road network stored by each roadside device in the road network through the optical fiber communication network or wireless communication network at a certain time interval CCD_T. The information extraction interval CCD_T of the central equipment is an integer multiple of the information processing interval RSD_T of the roadside equipment, namely:

CCD_T=n·RSD_T

Where: n is a natural number greater than 2.

Therefore, the central device can extract the average travel time data of n time series from the built-in database of each roadside device, and at the same time perform unified calibration on the average travel time data of n time series within the CCD_T time interval:

Among them: CCD_LT _j is the average travel time of the jth road segment in the road network within the central device CCD_T time interval; RSD_T _i is the i-th information processing time interval of the roadside device; RSD_LT _j (RSD_T _i ) is the roadside device The calibrated i-th information processing time interval RSD_T is the average travel time of the j-th road segment in the _i road network.

2) Dynamic optimization of travel routes

(1) Vehicle equipment

When the driver starts the vehicle and prepares to travel, the vehicle-mounted device automatically obtains the starting point VEH_O of the vehicle through the built-in GPS module, and the driver inputs the travel destination VEH_D through the human-computer interaction interface of the vehicle-mounted device. After the on-board device obtains the driver's travel starting point VEH_O and travel end point VEH_D, the vehicle's travel starting point VEH_O and travel end point VEH_D are sent to the central device through the built-in wireless communication module of the vehicle device.

(2) Central equipment

After the central device receives the start point VEH_O and the end point VEH_D of the on-board device, it provides K (generally K is 3) initial optimal paths for the vehicle.

The first initial optimal path: According to the average travel time of each road segment of the entire road network obtained by the central device at the current moment as the weight of the road segment for the shortest path calculation, the Dijkstra algorithm is used to solve the problem between the travel starting point VEH_O and the travel end point VEH_D The shortest path of , denoted as Path_TL1;

The second initial optimal path: According to the average travel time of the road section in the same period of history stored in the central equipment database as the road section weight value for the shortest path calculation, such as the road section where the starting point VEH_O of the vehicle travels is LINK1 (assuming that the starting point of LINK1 is VEH_O, the end point is LK1_D), the departure time is the current moment T_NOW, and the average travel time LT1 of the LINK1 section recorded by the central equipment at the current moment, then the section weight of LINK1 is LT1; when the vehicle arrives at LK1_D from the starting point VEH_O, the road section starting from LK1_D is For LINK2 and LINK3, the central device extracts the average travel time D_LT2 and D_LT3 of the road sections of LINK2 and LINK3 from the T_NOW+LT1 moment of the previous day; extracts the average travel time W_LT2 and W_LT3 of the road sections of LINK2 and LINK3 from the T_NOW+LT1 moment of the same date in the previous week, Then the link weights of LINK2 and LINK3 are:

LT2＝δ1·D_LT2+δ2·W_LT2

LT3＝δ1·D_LT3+δ2·W_LT3

Among them: LT2 and LT3 are respectively LINK2 and LINK3 are link weights; δ1 and δ2 are link weight adjustment coefficients, and δ1+δ2=1.

By analogy, the links starting from the end of link LINK2 are LINK4 and LINK5, and the links starting from the end of link LINK3 are LINK6 and LINK7, as shown in FIG. 3 . Then the central equipment extracts the average travel times D_LT4 and D_LT5 of LINK4 and LINK5 from the T_NOW+LT1+LT2 moment of the previous day; extracts the average travel times W_LT4 and W_LT5 of LINK4 and LINK5 from the T_NOW+LT1+LT2 moment of the same date in the previous week; Extract the average travel times D_LT6 and D_LT7 of LINK6 and LINK7 from T_NOW+LT1+LT3 of the previous day; extract the average travel times W_LT6 and W_LT7 of LINK6 and LINK7 from T_NOW+LT1+LT3 on the same date of the previous week. Then the link weights of LINK4, LINK5, LINK6, LINK7 are:

LT4＝δ1·D_LT4+δ2·W_LT4

LT5＝δ1·D_LT5+δ2·W_LT5

LT6＝δ1·D_LT6+δ2·W_LT6

LT7＝δ1·D_LT7+δ2·W_LT7

Among them: LT4, LT5, LT6, and LT7 are the link weights of LINK4, LINK5, LINK6, and LINK7 respectively.

By analogy, until the road segments required in the shortest path calculation between the travel start point VEH_O and the travel end point VEH_D are re-weighted with the average travel time of the road segments.

While assigning the weight of the road section, the central device uses the Dijkstra algorithm to solve the shortest path between the travel starting point VEH_O and the travel destination VEH_D, which is recorded as Path_TL2;

The third initial optimal path: Assume that the starting point of LINK1 is VEH_O, the end point is LK1_D, the road segments starting from LK1_D are LINK2 and LINK3, the road segments starting from the end point of LINK2 are LINK4 and LINK5, and the end point of road segment LINK3 The starting points are LINK6 and LINK7, as shown in FIG. 3 , and the departure time is the current time T_NOW. Firstly, the central equipment extracts the average travel time of the road segment LINK1 at the current moment and the previous information processing time interval as N_LT1 and P_LT1 respectively, and the average travel time of the road segment at the T_NOW moment of the previous day and the same date of the previous week are respectively D_LT1 and W_LT1; secondly The central equipment extracts the average travel time of the links LINK2 and LINK3 at the current moment and the previous information processing time interval as N_LT2, N_LT3 and P_LT2, P_LT3 respectively; at the same time extracts the T_NOW+N_LT1 moments of the previous day and the same date of the previous week for the links LINK2 and LINK3 The average travel time of the road sections in is D_LT2, D_LT3 and W_LT2, W_LT3 respectively. By analogy, the average travel time of the road sections extracted by the central device at the current moment and the previous information processing time interval of LINK4, LINK5, LINK6, and LINK7 are N_LT4, N_LT5, N_LT6, N_LT7 and P_LT4, P_LT5, P_LT6, P_LT7 respectively; T_NOW from the previous day Extract the average travel time D_LT4 and D_LT5 of LINK4 and LINK5 at +N_LT1+N_LT2; extract the average travel time W_LT4 and W_LT5 of LINK4 and LINK5 from T_NOW+N_LT1+N_LT2 on the same day in the previous week; Extract the average travel time D_LT6 and D_LT7 of LINK6 and LINK7 at time N_LT3; extract the average travel time W_LT6 and W_LT7 of LINK6 and LINK7 from T_NOW+N_LT1+N_LT3 on the same day in the previous week. but

LT1＝λ1·N_LT1+λ2·P_LT1+λ3·D_LT1+λ4·W_LT1

LT2＝λ1·N_LT2+λ2·P_LT2+λ3·D_LT2+λ4·W_LT2

LT3＝λ1·N_LT3+λ2·P_LT3+λ3·D_LT3+λ4·W_LT3

LT4＝λ1·N_LT4+λ2·P_LT4+λ3·D_LT4+λ4·W_LT4

LT5＝λ1·N_LT5+λ2·P_LT5+λ3·D_LT5+λ4·W_LT5

LT6＝λ1·N_LT6+λ2·P_LT6+λ3·D_LT6+λ4·W_LT6

LT7＝λ1·N_LT7+λ2·P_LT7+λ3·D_LT7+λ4·W_LT7

Among them: LT1, LT2, LT3, LT4, LT5, LT6, LT7 are the link weights of LINK1, LINK2, LINK3, LINK4, LINK5, LINK6, LINK7 respectively. λ1 , λ2 , λ3 , λ4 , λ5 , λ6 , and λ7 are respectively road section weight adjustment coefficients, and λ1+λ2+λ3+λ4=1.

By analogy, until the road segments required in the shortest path calculation between the travel start point VEH_O and the travel end point VEH_D are re-weighted with the average travel time of the road segments.

While assigning the weight of the link, the central device uses the Dijkstra algorithm to solve the shortest path between the travel starting point VEH_O and the travel destination VEH_D, which is recorded as Path_TL3.

(3) Roadside equipment

After the central device provides the vehicle with three initial optimal paths, the driver chooses one of the induced paths to travel according to his own preference, and the selected travel path is recorded as Path_INI. Assume that the entry node of Path_INI passing through the road network range under the jurisdiction of the roadside equipment is VEH_IN, and the exit node is VEH_OUT. When a vehicle enters the range of the road network under the jurisdiction of the roadside equipment, the roadside equipment obtains the instantaneous speed of each vehicle on each section of the road network under its jurisdiction, and at the same time divides the section into three parts: the upstream section, the middle section, and the downstream section, as shown in Figure 4 shown. According to the latitude and longitude information of the vehicle VEH_GPS, the instantaneous vehicle speed is divided into three types of position speeds: the instantaneous vehicle velocity VEH_UV _i in the upstream section of the road section, the instantaneous vehicle velocity VEH_MV _i in the middle section, and the instantaneous vehicle velocity VEH_DV _i in the downstream section.

VEH_V _i =δ1·VEH_UV _i +δ2·VEH_MV _i +δ3·VEH_DV _i

Among them: VEH_UV _i , VEH_MV _i , and VEH_DV _i are distributed as the instantaneous speed of vehicles in the upstream section, the instantaneous speed of vehicles in the middle section, and the instantaneous speed of vehicles in the downstream section of the i-th road section of the road network under the jurisdiction of the roadside equipment; VEH_UV _i,j , VEH_MV _{i, j} , VEH_DV _{i, j} are respectively the instantaneous speed of the vehicle in the upstream section, the instantaneous speed of the vehicle in the middle section, and the instantaneous speed of the vehicle in the downstream section of the jth vehicle in the i-th road section of the road network under the jurisdiction of the roadside equipment; M1, M2, and M3 are respectively The total number of vehicles in the upstream section, middle section, and downstream section of the road section; VEH_V _i is the average driving speed of the i-th road section of the road network under the jurisdiction of the roadside equipment; δ1, δ2, and δ3 are the average speed adjustment coefficients of the road section; LINK_T _i is the average travel time of the i-th road section of the road network under the jurisdiction of the roadside equipment; LINK_L _i is the length of the i-th road section of the road network under the jurisdiction of the roadside equipment.

At the same time, according to the time when the vehicle enters the entry node VEH_IN of the road network under the jurisdiction of the roadside device, the roadside device obtains the signal status information SIG_INFO of the traffic signal controller of each node of the road network under its jurisdiction, and estimates the signal waiting of each node on the vehicle's driving path time. Assume that the road section of the road network under the jurisdiction of the roadside equipment starts from VEH_IN as LINK1, the end node of LINK1 is LK1_D, and the road sections starting from LK1_D are LINK2 and LINK3. The time when the vehicle enters VEH_IN is TIN_NOW, and the average travel time of LINK1, LINK2, and LINK3 is LINK_T ₁ , LINK_T ₂ , LINK_T ₃ , then the roadside equipment estimates the waiting time for the vehicle to pass the intersection when it arrives at the node LK1_D at TIN_NOW+LINK_T ₁ Signal time LINK_SIG(STime,LTime) ₁ . Afterwards, the roadside equipment estimates TIN_NOW+LINK_T ₁ +LINK_SIG(STime,LTime) ₁ +LINK_T ₂ when the vehicle arrives at the LINK2 termination node and passes through the intersection signal time LINK_SIG(STime,LTime) ₂ ; the roadside equipment estimates TIN_NOW +LINK_T ₁ +LINK_SIG(STime,LTime) ₁ +LINK_T ₃ The signal time LINK_SIG(STime,LTime) ₃ that the vehicle needs to wait to pass through the intersection when the vehicle arrives at the end node of LINK3. By analogy, the roadside equipment estimates the signal time LINK_SIG(STime,LTime) _i that the vehicle needs to wait for when passing through the end nodes of each road section of the road network under its jurisdiction.

Then the road section weight of each section of the road network under the jurisdiction of the roadside equipment is:

LT _i =LINK_T _i +LINK_SIG(STime,LTime) _i

Among them: LT _i is the section weight of the i-th road section of the road network under the jurisdiction of the roadside equipment; LINK_SIG(STime,LTime) _i is the signal time function that the vehicle needs to wait for passing through the i-th road section of the road network under the jurisdiction of the roadside equipment, STime is the time to wait for the straight green light, and LTime is the function to wait for the left turn green light.

According to the weight value of the road section of the road network under its jurisdiction LT _i = LINK_T _i +LINK_SIG(STime,LTime) _i , the roadside equipment uses the Dijkstra algorithm to solve the shortest path between the travel starting point VEH_IN and the travel end point VEH_OUT, which is recorded as RSD_Path, and calculates Required travel time T(RSD_Path).

Assuming that the initial optimal path of Path_INI is CCD_Path in the path part of the road network under the jurisdiction of the roadside equipment, use LT _i = LINK_T _i +LINK_SIG(STime,LTime) _i to reassign the road sections included in CCD_Path, and calculate the time required for vehicles to pass through CCD_Path The travel time of is T(CCD_Path), and compared with RSD_Path, as shown in Figure 5.

If T(RSD_Path)<T(CCD_Path), within the jurisdiction of the roadside equipment, change the induced path to RSD_Path, and send it through traffic information services such as information guidance (path change description, change advantage analysis, etc.), information prompts, etc. For the on-board equipment, the on-board equipment guides the driver through the human-computer interaction interface.

Claims (1)

1. it is a kind of based on bus or train route communicate dynamic route guidance method, it is characterised in that trip route dynamic optimization：

(1) mobile unit：When trip is prepared, mobile unit obtains car by built-in GPS module to driver actuation automatically Go out beginning-of-line VEH_O, driver is input into travel destination VEH_D by the human-computer interaction interface of mobile unit；Set when vehicle-mounted It is standby obtain driver go out beginning-of-line VEH_O and travel destination VEH_D after, will by the built-in wireless communication module of mobile unit Vehicle go out beginning-of-line VEH_O and travel destination VEH_D is sent to central apparatus；

(2) central apparatus：Central apparatus receive mobile unit go out beginning-of-line VEH_O and travel destination VEH_D after, be vehicle There is provided K bars initial optimal path：

First initial optimal path, the section at the system-wide net each section current time obtained according to current time central apparatus are put down Journey time as the section weights for carrying out shortest path calculating, using dijkstra's algorithm solve beginning-of-line VEH_O and Shortest path between travel destination VEH_D, is designated as Path_TL1；

The initial optimal path of Article 2, makees according to the average travel time for road sections of the history same period stored in central apparatus data base To carry out the section weights of shortest path calculating, the section that vehicle driving starting point VEH_O is located is LINK1, and LINK1 terminals are LK1_D, sets out constantly as current time T_NOW, the average travel time for road sections of the LINK1 of current time central apparatus record LT1, then the section weights of LINK1 are LT1；When vehicle reaches LK1_D, the road section with LK1_D as starting point from starting point VEH_O For LINK2 and LINK3, then central apparatus extract the road-section average row of LINK2 and LINK3 from the T_NOW+LT1 moment of the previous day Journey time D_LT2 and D_LT3；The road-section average of LINK2 and LINK3 was extracted from upper one week of even date T_NOW+LT1 moment Journey time W_LT2 and W_LT3, then the section weights of LINK2 and LINK3 be：

LT2=δ 1D_LT2+ δ 2W_LT2

LT3=δ 1D_LT3+ δ 2W_LT3

Wherein：It is section weights that LT2 and LT3 is respectively LINK2 and LINK3；δ 1 and δ 2 is section weighed value adjusting coefficient, and δ 1+ δ 2=1；

By that analogy, as LINK4 and LINK5, the terminal with section LINK3 is in the section with the terminal of section LINK2 as starting point The section of starting point is LINK6 and LINK7；Then central apparatus from the T_NOW+LT1+LT2 moment of the previous day extract LINK4 and The average travel time for road sections D_LT4 and D_LT5 of LINK5；Extracted from upper one week of even date T_NOW+LT1+LT2 moment The average travel time for road sections W_LT4 and W_LT5 of LINK4 and LINK5；Extract from the T_NOW+LT1+LT3 moment of the previous day The average travel time for road sections D_LT6 and D_LT7 of LINK6 and LINK7；From upper one week of even date T_NOW+LT1+LT3 when Carve the average travel time for road sections W_LT6 and W_LT7 for extracting LINK6 and LINK7；Then LINK4, LINK5, LINK6, LINK7 Section weights are：

LT4=δ 1D_LT4+ δ 2W_LT4

LT5=δ 1D_LT5+ δ 2W_LT5

LT6=δ 1D_LT6+ δ 2W_LT6

LT7=δ 1D_LT7+ δ 2W_LT7

Wherein：LT4, LT5, LT6, LT7 are respectively the section weights of LINK4, LINK5, LINK6, LINK7；

By that analogy, until going out the section quilt between beginning-of-line VEH_O and travel destination VEH_D needed for shortest path calculating Again the weights of average travel time for road sections are given；

While section weights assignment is carried out, central apparatus solve beginning-of-line VEH_O and trip using dijkstra's algorithm Shortest path between terminal VEH_D, is designated as Path_TL2；

The initial optimal path of Article 3, it is assumed that the starting point of LINK1 is VEH_O, and terminal is LK1_D, the road with LK1_D as starting point Section is LINK2 and LINK3, the section with the terminal of section LINK2 as starting point as LINK4 and LINK5, with section LINK3's Terminal is LINK6 and LINK7 for the section of starting point, and it be constantly current time T_NOW to set out；Central apparatus extract section first The average travel time for road sections at LINK1 current times and upper message processing time interval is respectively N_LT1 and P_LT1, with And the average travel time for road sections at section the previous day and upper one week of even date T_NOW moment is respectively D_LT1 and W_LT1； Secondly, central apparatus extract the road-section average row at section LINK2, LINK3 current time and upper message processing time interval The journey time is respectively N_LT2, N_LT3 and P_LT2, P_LT3；It is same that section LINK2, LINK3 the previous day and upper one week are extracted simultaneously The average travel time for road sections at the T_NOW+N_LT1 moment on one date is respectively D_LT2, D_LT3 and W_LT2, W_LT3；With this Analogize, central apparatus extract the road at LINK4, LINK5, LINK6, LINK7 current time and upper message processing time interval Section average travel time is respectively N_LT4, N_LT5, N_LT6, N_LT7 and P_LT4, P_LT5, P_LT6, P_LT7；From the previous day The T_NOW+N_LT1+N_LT2 moment extract the average travel time for road sections D_LT4 and D_LT5 of LINK4 and LINK5；From upper one The of even date T_NOW+N_LT1+N_LT2 moment in week extracts the average travel time for road sections W_LT4 and W_ of LINK4 and LINK5 LT5；From the T_NOW+N_LT1+N_LT3 moment of the previous day extract LINK6 and LINK7 average travel time for road sections D_LT6 and D_LT7；When from upper one week, the of even date T_NOW+N_LT1+N_LT3 moment extracted the road-section average stroke of LINK6 and LINK7 Between W_LT6 and W_LT7；Then：

LT1=λ 1N_LT1+ λ 2P_LT1+ λ 3D_LT1+ λ 4W_LT1

LT2=λ 1N_LT2+ λ 2P_LT2+ λ 3D_LT2+ λ 4W_LT2

LT3=λ 1N_LT3+ λ 2P_LT3+ λ 3D_LT3+ λ 4W_LT3

LT4=λ 1N_LT4+ λ 2P_LT4+ λ 3D_LT4+ λ 4W_LT4

LT5=λ 1N_LT5+ λ 2P_LT5+ λ 3D_LT5+ λ 4W_LT5

LT6=λ 1N_LT6+ λ 2P_LT6+ λ 3D_LT6+ λ 4W_LT6

LT7=λ 1N_LT7+ λ 2P_LT7+ λ 3D_LT7+ λ 4W_LT7

Wherein：LT1, LT2, LT3, LT4, LT5, LT6, LT7 be respectively LINK1, LINK2, LINK3, LINK4, LINK5, The section weights of LINK6, LINK7；λ 1, λ 2, λ 3, λ 4, λ 5, λ 6, λ 7, respectively section weighed value adjusting coefficient, and λ 1+ λ 2+ λ 3+ λ 4=1；

By that analogy, until going out the section quilt between beginning-of-line VEH_O and travel destination VEH_D needed for shortest path calculating Again the weights of average travel time for road sections are given；

While section weights assignment is carried out, central apparatus solve beginning-of-line VEH_O and trip using dijkstra's algorithm Shortest path between terminal VEH_D, is designated as Path_TL3；

(3) roadside device：Central apparatus are provided after three initial optimal paths for vehicle, and driver is selected according to the preference of oneself Induction path trip therein, then Selecting Travel Paths are designated as Path_INI；Assume Path_INI through roadside device institute The Ingress node of linchpin road network scope is VEH_IN, and Egress node is VEH_OUT；When vehicle enters the administrative road network scope of roadside device When, roadside device obtains the instantaneous velocity of each vehicle on each section of administrative road network, meanwhile, by pavement section be upstream section, in Portion section, three part of downstream road section；According to the vehicle latitude and longitude information of vehicle VEH_GPS, vehicle instantaneous velocity is divided into The upstream section vehicle instantaneous velocity VEH_UV in road section_i, middle part section vehicle instantaneous velocity VEH_MV_i, downstream road section vehicle wink Shi Sudu VEH_DV_iThree class position and speeds：

$VEH\_{\mathrm{UV}}_i=\underset{j=1}{\overset{M1}{\&Sigma;}}VEH\_{\mathrm{UV}}_{i,j}$

$VEH\_{\mathrm{MV}}_i=\underset{j=1}{\overset{M2}{\&Sigma;}}VEH\_{\mathrm{MV}}_{i,j}$

$VEH\_{\mathrm{DV}}_i=\underset{j=1}{\overset{M3}{\&Sigma;}}VEH\_{\mathrm{DV}}_{i,j}$

VEH_V_i=δ 1VEH_UV_i+δ2·VEH_MV_i+δ3·VEH_DV_i

$LINK\_T_i=\frac{LINK\_L_i}{VEH\_V_i}$

Wherein：VEH_UV_i、VEH_MV_i、VEH_DV_iIt is distributed as the upstream section car of administrative the i-th road section of road network of roadside device Instantaneous velocity, middle part section vehicle instantaneous velocity, downstream road section vehicle instantaneous velocity；VEH_UV_i,j、VEH_MV_i,j、VEH_ DV_i,jRespectively the upstream section vehicle instantaneous velocity of the jth car of administrative the i-th road section of road network of roadside device, middle part section Vehicle instantaneous velocity, downstream road section vehicle instantaneous velocity；The upstream section of M1, M2, M3 respectively in road section, middle part road Section, the vehicle fleet of downstream road section；VEH_V_iFor the average overall travel speed of administrative the i-th road section of road network of roadside device；δ1、δ 2nd, δ 3 is respectively road section average speed regulation coefficient；LINK_T_iFor the average of administrative the i-th road section of road network of roadside device Running time；LINK_L_iFor the road section length of administrative the i-th road section of road network of roadside device；

Meanwhile, the time of the Ingress node VEH_IN of the administrative road network scope of roadside device is entered according to vehicle, roadside device is obtained Signal condition information SIG_INFO of each junction traffic signal controller of administrative road network, estimates each node on vehicle running path The signal waiting time；Road section of the administrative road network of roadside device with VEH_IN as starting point is assumed as LINK1, the termination of LINK1 Node is LK1_D, and the road section with LK1_D as starting point is as LINK2, LINK3；Vehicle is TIN_ into the time of VEH_IN NOW, the road-section average running time of LINK1, LINK2, LINK3 is LINK_T₁、LINK_T₂、LINK_T₃, then roadside device estimate Calculate TIN_NOW+LINK_T₁Moment vehicle reaches the signal time LINK_SIG needed to wait for by crossing during node LK1_D (STime,LTime)₁；Afterwards, roadside device estimation TIN_NOW+LINK_T₁+LINK_SIG(STime,LTime)₁+LINK_T₂ Moment vehicle reaches signal time LINK_SIG (STime, the LTime needed to wait for by crossing during LINK2 terminal nodes )₂；Roadside device estimates TIN_NOW+LINK_T₁+LINK_SIG(STime,LTime)₁+LINK_T₃Moment vehicle reaches LINK3 The signal time LINK_SIG (STime, LTime) needed to wait for by crossing during terminal node₃；By that analogy, trackside sets Needed to wait for during each by the administrative road network section terminal node of standby estimation vehicle signal time LINK_SIG (STime, LTime)_i；

Then the section weights in each section of the administrative road network of roadside device are：

LT_i=LINK_T_i+LINK_SIG(STime,LTime)_i

Wherein：LT_iFor the section weights of administrative the i-th road section of road network of roadside device；LINK_SIG(STime,LTime)_iFor car The signal time function needed to wait for by administrative the i-th road section of road network of roadside device, STime is to wait during straight trip green light Between, LTime is wait left-hand rotation green light function；

Road section weights LT of the roadside device according to administrative road network_i=LINK_T_i+LINK_SIG(STime,LTime)_i, adopt Dijkstra's algorithm solves the shortest path between beginning-of-line VEH_IN and travel destination VEH_OUT, is designated as RSD_Path, and Journey time T (RSD_Path) needed for calculating；

Assume that the initial optimal paths of Path_INI are CCD_Path in the path sections of the administrative road network of roadside device, using LT_i= LINK_T_i+LINK_SIG(STime,LTime)_iThe road section included by CCD_Path assignment again, calculates vehicle and passes through Journey time needed for CCD_Path is T (CCD_Path), and is compared with RSD_Path；

If T (RSD_Path)<T (CCD_Path), then, in roadside device administrative area, be RSD_ by induction route diversion Path, and mobile unit is sent to by traffic-information services such as information guidance, information alerts, by mobile unit by man-machine friendship Mutually interface is guided to driver.