Transportation Model for Burgas

Transcription

1 Inception Report April 2009 Transportation Model for Burgas Inception report

2 Executive Summary: Main findings Daily Modal split in major corridors is in favor of car (59% of all trips) Average number of daily trips per person in PT is only 0.41 trips/person. This is low in comparison with other European countries with similar car ownership levels. There is no clear peak hour in the demand for PT (or for cars) number of passengers in mid-day is higher than in morning or afternoon peaks! Current Bus network coverage is good 96% of passengers walk to and from the bus with no need to transfer. The good coverage also explains the high proportion of monthly ticket users (~50%), although monthly tickets are valid only for one or two routes and NOT for the whole network The average peak hour commercial speed of the buses is quite high 21 km/h. However, due to lack of major congestion, the private car is much more attractive with average peak hour speed of 35 km/h The Trolley bus line is very slow and unattractive - average morning peak hour speed is only 12.9 km/h Ridership estimated by the Municipality is not accurate: Our observed ridership is lower by 46% than the reported ridership of BurgasBus, and HIGHER by 31% from the reported ridership of Volan. The reported ridership for comfort is close to the observed one with only 2% difference. (See Slide 63 for possible reasons) In some bus lines the average occupancies is low. This might be a result of relatively strong in-the-market competition among several bus routes Two bus lines - 12/12A and 211 carry 63% of the overall passengers in the system.

3 Scope of the inception report This report has the following structure Chapter 1 presents the travel demand model that is being developed Chapter 2 presents the work plan for data collection and the various surveys conducted Chapter 3 presents the main finding of the surveys conducted so far Chapter 4 presents the work plan for additional surveys

4 March 2009 Chapter 1: Model structure and design Inception report

5 1. Model Structure ROM develops a standard four-step transportation demand model for the city of Burgas The model underlines the transit segment and allows decision makers to test various transit scenario in which different facilities / policies will be examined. The model has 4 main components: 1. Supply definition: map all existing facilities (roads + transit scheme) 2. Demand evaluation: define O-D demand matrix 3. Modal split model: identify elasticity to move to transit 4. Post-processor and interface with economic & environmental models The creation of the model was based on various data resources (Municipality, bus operators, etc.) and extensive set of surveys conducted by ROM and third parties.

6 1. Model structure Scheme Stage finished

7 1. Model structure Mode Choice Structure Mode Choice model will estimate propensity to transfer to transit mode, when better level of service is introduced The elasticity to move to transit will be captured in a travel habit survey that is carried on this week ( 8-16/4/2009)

8 March 2009 Chapter 2: Data collection Inception report

9 2. Data Collection: Summary of surveys 2.1 Land Use & Demographic surveys Population by zone based on election zone, up-to-date Employment by zone on the ground survey (Students) 2.2 Road Network Road attributes Type, lane, Direction: on the ground survey (Students) Intersection control (Students) 2.3 Transit Network Bus alignment & Bus stop location on the ground survey Bus line characteristic- Time table, terminals, bus type (Operators) 2.4 Bus Survey (Students) On Board survey- 3,700 surveys!!! Passenger counts per stop 14,000 boarding counts!!! 2.5 Traffic counts (Students) 2.6 GPS survey 3 Corridor count for 14 hours, All mode 9+20 Car and Truck counts, AM, MD and PM only Bus speeds in 3 periods - on the ground survey (Drivers) Car Speed in 3 periods - on the ground survey (Students) 4. Additional survey Travel habit survey Conducted between 6/4-13/4 (callpoint-group, Sofia )

10 2. Data Collection 2.1 Land Use & Demographic Inception report

11 2.1 Land use & Demographic data Land use and demographic surveys are the cornerstone of any transportation model. First, we had to collect various land use and demographic data in order to identify the population and employment spatial distribution The following resources were identified: 1. Statistic from the municipality shows that by 2008, there were 72,970 employees in Burgas 2. Election zones The municipality holds an up-to-date data base with 261 election zones. Each zone has the permanent and actual number of residents living in it. 3. List of major employment centers such as Refinery, large factories, shopping mall, hospital, university, etc. 4. Employment survey: Students from the free university conducted a physical survey were they estimated number of employees in each zone

12 2.1 Land Use & Demographic data - Employment Sector Employees-2008 (source municipality/ Bureau of statistics) 4% 5% 4% Building gross trade 7% 35% Food and drink production Buisness services 7% Rtail trade Hotels & restuarants 8% Agriculture Road transport. Incl. pipeline 7% 10% 13% Health care & social services Plastic & rubber production According to official statistic, by 2008, there were 73,000 employees in Burgas. Due to the recession, the high share of the construction and building sector was likely to shrink and lead to lower employment rate. Our employment survey account for 20% less employees than official number suggests

13 2.1 Land Use & Demographic data- Super Zone Population by Super-Zone segmentation ID Name Population Share 1 Izgrev 24,000 11% 2 Industry + Pobeda 8,000 4% 3 Zornica 18,000 8% 4 Slaveykov 33,000 15% Industrialna- North- West - 0% 5 6 Rail & Port - 0% 7 Lazur 18,000 8% 8 Center 32,000 15% 9 Miladinovi 18,000 8% 10 North 18,000 8% 11 Meden Rudnik 45,000 21% 12 South 4,000 2% Total 218, % 12 super zones were identified with different land use type characteristics

14 2.1 Land Use & Demographic data- Land Type Land use type was identified for each zone based on the most common utilization of the zone

15 2.1 Land Use & Demographic data - Population High Medium LOW Population distribution Zonal aggregation of the election zone Election zone population inventory Based on up-to-date election zone statistics. (Source municipality of Burgas)

16 2.1 Land Use & Demographic data Employment Location of refinery is few KM north Employment centers are scattered in the east part of the city. The city center attracts only 12% of overall population

17 2. Data Collection 2.2 Road Network Transit Survey

18 2.2 Road Network Road network will enable us to code bus routes in the model, to perform auto and transit assignment and to conduct various analysis The basic network was obtained from the GIS department in the municipality. This network had to be revised to fit the model s requirements. For that matter, ROM engaged few students that surveyed all road of Burgas and collected the following attributes: 1. Number of lanes per road per direction 2. Road directionality one way/ two ways 3. Road type; Segmented into: Principal - 98 KM Arterial 91 KM Local 552KM Parking / Access roads 70 KM Intercity 190 KM Walk-way 192 KM Ramps 5 KM 4. Traffic-light survey to model delays in intersections The road network of the model spans over 1,198 km. 379 km out of them are main road

19 2.2 Road Network Road Hierarchy (road type) Total of 378 km of principal roads out of a network of 1,1198 km

20 2.2 Road Network Number of lanes Most of the network has one lane per direction. The main roads have 2-3 lanes

21 2.2 Road Network Directionality of roads Most of the road network is two-way roads. 58 KM is one way painted in red (out of total of 1,198 km)

22 2.2 Road Network Intersection control Overall 37 traffic lights were identified in Burgas

23 2. Data Collection 2.3 Transit Network Transit Survey

24 2.3 Transit Network Each existing and proposed bus / BRT route is identified and coded in our model. ROM applied a variety of methods to collect all the above. Each Route includes the following set of information: Specific alignment of the route Number of stops Operator name Location of all bus stops (Including Terminals) Typical bus type Peak AM Headway / Frequency of service Total number of daily trip Total of 31 one way bus lines were coded (total of 20 unique bus lines)

25 2.3 Transit Network Example for bus line # 211 Total Length = (South) (North) Operator = BurgasBus Bus type = 18 meter (3 doors) AM peak Frequency = 5 minutes Number of stops = Daily departures = 165 Locations of stops was carefully located, because data in the On-Board survey is stops based and the location of the stops derives the O-D matrix

26 2.3 Transit Network Entire network Total network length is km (two directions). Total number of stops = 694 (Average of 22.4 per line per direction)

27 2.3 Transit Network Bus line table Passenger ridership, boarding and alighting figures will be added to this data base

28 2. Data Collection 2.4 Bus Surveys Transit Survey

29 2.4 Bus survey Objective Generate Transit demand matrix for 3 periods Calibrate Transit demand matrix for 3 periods Identify propensity to use transit / Auto for Mode Choice model Identify other statistical characteristics for the project (ticket usage, transfer rate, etc)

30 2.4 Bus survey: Methodology ROM conducted 2 types of surveys during 2 weeks in February and March 2009: On-Board Survey and Passenger counts Prior to launching the surveys ROM conducted 2 pilots to examine the format of the surveys and other operational issues. Surveys were conducted on all bus lines for 3 time periods: 07:00-09:00, 12:00-14:00 and 16:30-18:30. ROM sampled 240 out of 632 of all buses departed between the defined periods. Total number of valid interviews conducted is 4700, that is, 33% of overall 14,200 passengers boarded the surveyed buses On each bus, a team of 2-4 students were deployed. Two surveyors counted passengers boarding or alighting from each stop along the course of the bus. The other two conducted the on-board surveys In each terminal ROM had an office that served for sheets deliveries and collections, coding data on the laptops right after each team s shift and so on.

31 2.4 Bus survey Format of on-board survey Stop list A unique format was prepared for each bus line for each direction due to the stop coding

32 2.4 Bus survey Format of passenger count survey Stop list

33 2.4 Bus survey Expanding the survey (1) The individual passenger trips surveyed on board should be expanded to represent all trips in the bus network. Sample volumes and methods of calculation of the expansion factors are shown below: AM MD PM Expansion factor calculation A. Number of sampled bus trips B. Total number of bus trips in service Factor1 = B/A: by route, direction, period C. Number of valid interviews D. Total number of passengers in sampled buses (counted) 1,737 5,088 1,571 5,123 1,382 4,014 Factor2 = D/C: by route, direction, period, stop of boarding E. Total number of passenger trips during survey periods 14,225 F. Estimation of total number of daily passenger trips (daily ridership) Factors: F/E; G/F; H/G, by route; see explanation below G. Estimation of monthly ridership H. Estimation of annual ridership

34 2.4 Bus survey Expanding the survey (2) There are three different expansion factors used with the results of the survey: Expansion factor to transform sampled bus trips to bus trips in service in periods of survey. It is calculated as a ratio of total number of bus in service for given period of day, route and direction, to the number of sampled buses A factor to expand the data of interviews with passengers. This is the ratio of number of passengers boarded in certain stop to the bus of given route and direction during given period of day, to the number of valid interviews conducted with these passengers A factor to expand the surveyed passenger trips to estimate daily, monthly or annual ridership.

35 2.4 Bus survey Ridership estimation (1) Daily (monthly, annual) ridership cannot be estimated from the survey results; data from other source is required. Following assumptions are used here: The daily sale volume of regular tickets by route is an accurate estimate of daily ridership of passengers traveled with regular tickets. The share of passengers traveled with discounted pass cards is better estimated from on board survey, as compared to the Municipality figures obtained from the sale volumes of discounted pass cards with rough assumption on monthly amount of trips per pass. The ratio of ridership during survey periods of day to the total daily ridership is assumed the same for passengers with regular and with discounted tickets. The monthly and annual ticket sales figures can be used for expansion of daily ridership to monthly and annual values.

36 2.4 Bus survey Ridership estimation (2) To summarize, the daily ridership for each route is obtained as estimated ridership from the survey multiplied by the daily-to survey period expansion factor. The factor is calculated as a ratio of number of regular tickets sold during a day, to the estimated number of passengers traveled with regular ticket during survey periods according to the survey. For most routes this factor is close to 2. Exceptions are routes 121, 13 and 101 which do not operate fully during whole day. The monthly ridership is obtained from the weekly ridership: according to the data for December 2008, average weekly ridership is 5.8 times bigger than the weekday one. Therefore, average monthly-to-daily expansion factor equals to 5.8*4.34 weeks/month = Annual-to-daily factor is 25.2 * 12 = It should be noted, that according to available data the natural variations in the daily ridership may reach 15%, and therefore, the usage of above average factors is quite acceptable

37 2. Data Collection 2.5 Corridor and car count surveys Opposite direction Car count Truck count Transit Survey

38 2.5 Corridor Survey: Objective & Methodology Traffic counts have several purposes: Validate bus surveys Calibrate O-D Car and Transit matrices Expansion of survey results into daily figures Mode choice analysis (To be integrated with the travel-habit survey) ROM surveyed 3 major locations in the city for 14 hours (06:30-20:30). In those locations we counted vehicle and passengers in all vehicle types. In addition ROM counted auto and truck traffic in 9 additional points, and plans to count traffic in additional 20 points this week (6-10/4/2009)

39 2.5 Corridor Survey: Location of counts 9+20 (new) locations for Auto counts (Car+ Truck only) 3 locations for corridor counts (Car+Truck+Bus) ROM identified additional 20 locations and performed traffic counts during 6-10/4

40 2.5 Corridor Survey: Time distribution in S. Stambalov Peak traffic in Stambalov is between 08:30-09:30 and 17:00-18:00. No classic off-peak in the middle of the day in this point

41 2.5 Corridor Survey: Corridor 1 S. Stambalov Located on a bottleneck where almost all traffic from the northern parts of the city should path through

42 2.5 Corridor Survey: Corridor 1 - Industrialna Higher Bus share (42% of passenger) in this point relative to Stambalov (Low income residents from M. Rudnik)

43 2.5 Corridor Survey: Corridor 3 Christo Botev (Tzar Peter) High Bus share (52% of passenger) in this point - serves as a transit corridor with 15 bus lines passing here (out of 23)

44 2.5 Corridor Survey: Car & Truck Count

45 2. Data Collection 2.6 GPS survey Transit Survey

46 2.6 GPS Survey: Objective & Methodology GPS Speed survey has several purposes: Validate bus route in some cases we identified different alignment of bus line than officially reported to us Extract bus scheme speeds in 3 period and embedded it in the Model Extract Auto speed for modeling purpose Useful when identifying stop location Compare speed of different bus route and bus type ROM installed GPS devices in all bus routes and measured traveling speed in 3 time periods. GPS device are very accurate with 2 second sampling rate. In addition ROM lunched a floating car equipped GPS roamed the city in 3time period All data was incorporated in modeling tools.

47 2.6 GPS Survey Bus Speed analysis Bus average speed in the city stands on 22 km/ hr in the AM peak, 27 km/hr in the midday and 23 km/ hr in the PM peak (Including stops) Bottle necks Transit traveling speeds are reasonable when comparing it to other city in the EU. However, there is a great potential to increase speed drastically.

48 2.6 GPS Survey Car speed analysis A Floating car equipped GPS roamed the city in three time period. Average Auto speed is 28.4 for AM, 33.2 for MD and 29.1 for PM. The Auto speeds are 40% faster then bus speeds for AM/MD and 20% faster in the MD.

49 March 2009 Chapter 3: Main Findings Inception report

50 3 Main findings The following items are being presented in this chapter: 3.1 Transit network analysis 3.2 Traffic analysis in Burgas 3.3 Bus Scheme analysis 3.4 Level of Service for the Transit passengers 3.5 Main findings: Potential BRT corridor

51 3.1 Main Findings: Transit network Overlapping routes 24 one-way bus lines (80%) 16 one-way bus lines (53%) 20 one-way bus lines (66%) 16 one-way bus lines (53%) Bus network is redundant with an average of 3.1 different bus lines (~5 one-way route) per street link. On some locations, then number of bus lines (one way) exceed 15!!!

52 3.1 Main Findings: Transit network Competing routes 2A Northbound Examples of competing routes 121 northbound 1 Northbound 211 Northbound 2 Northbound In many cases bus routes runs parallel one to each other, and create an in-the-marketcompetition, that causes low bus occupancy

53 3.1 Main Findings: Transit Network Versioning 25A Northbound 25 Northbound Several bus lines have different versions for different time of day. It leads to some confusion by passenger and cause some inaccuracies in statistic collection

54 3.2 Main findings: Traffic analysis - City center A Cordon line around the city center is bounded by only 4 entrance as depicted on the map. Total estimated of traffic crossing the cordon line of the city center in one direction is 75,000 car passengers and 35,000 public transport passengers Modal split trends: In the south 42% of the passengers uses transit (Low income origin of M. Rudnik) while in the north the share drops to only 28% of overall passengers (Inter-city traffic, suburban car traffic. Etc ) The Household survey will reveal a better estimation about the market share for public transportation It is important to note that the city center isn t the major employment center and therefore attracts less than a third of the overall traffic

55 3.2 Main findings: Traffic analysis - North Cordon line A Cordon line north of the city was defined to measure the in and out traffic to the city. CAR AM peak inbound traffic is 1,589 CAR AM peak outbound traffic is 1,647 Truck traffic is 318 inbound and 367 outbound. Traffic in Burgas has no clear directionality in the peak hour, like other cities. Major employment centers in the north (Refinery, Airport, sunny beach, etc) and the absence of major suburbs cause significant outbound traffic, while commuters from the suburbs and traffic from other cities that enter the city generate the majority of inbound traffic

56 3.2 Main findings: Traffic analysis - Directionality Traffic in Burgas has no clear directionality like many other cities worldwide. This can be attributed to the fact that residential and employment centers are located both in the south and the north. Average car occupancy is 1.59 passenger per private car. This is much higher than European average (1.2 in peak hour) and reflects low car ownership. The following graph illustrates the 1,7 1,65 1,6 1,55 1,5 1,45 1,4 1,35 occupancy average by time of day 1,3 Peak- Off peak- AM Peak- Off peak- MD Peak- Off peak- PM different locations % 250% 200% 150% 100% 50% 0% In most locations, there is no clear directionality inbound towards the city in the AM peak

57 3.3 Main findings: Bus scheme analysis There are 20 bus routes with 31 unique one way trips in Burgas Daily VKMT is estimated at around 25,788 KM. AM peak average speed is 21 km/ hr, 40% lower than the average car speed in the same period. 1,768 daily bus trips carry around 83,000 passengers a day The following graph illustrates some operational statistic by operator: Note: Bus size and capacity differs between the different operators : Comfort: Operates only mini-midi bus Burgasbus: operates also articulated buses Burgasvolan : mainly standard buses BurgasBus is still the most dominant player in the transit system in Burgas. BurgasVolan suffers from less attractive routes and more complex scheme

58 3.3 Main findings: Bus scheme analysis Average transfer rate is 6% Walk access share is about 96%. Distribution of walk time is: 51% of passengers are walking less than 5 minutes, 29% of passengers are walking between 5 and 10 minutes, and the rest (20%) walk more than 10 minutes Distribution of trips by purpose: All the above figures shows that the bus network has very good coverage. This can be attribute to the convenient layout of the city which is bounded by the sea and the lakes. Trip by purpose is illustrated in the following table: Period Other Study Work Total AM 10% 26% 65% 100% MD 25% 44% 32% 100% PM 24% 20% 56% 100% Total 19% 30% 51% 100%

59 3.3 Main findings: Bus scheme analysis Distribution of passengers by reason of using bus, and not car: Period No car Other Parking problems Too expensive Traffic problems Total AM 66% 0% 9% 10% 14% 100% MD 76% 0% 7% 5% 11% 100% PM 67% 0% 10% 8% 15% 100% Total 70% 0% 9% 8% 14% 100% Distribution of passengers by ticket type: Period Monthly Other Regular Total AM 48% 2% 49% 100% MD 58% 2% 40% 100% PM 44% 2% 53% 100% Total 50% 2% 47% 100%

60 3.3 Main findings: Bus scheme analysis Bus Occupancy Maximal and average bus occupancy AM MD PM Approximate values Route Max. occupan cy Avg. occupanc y Max. occupancy Avg. occupan cy Max. occupancy Avg. occupanc y Max. bus Capacity *0.7 Max. occupancy rate Avg. occupanc y rate A T A Big variance in occupancy rate in different bus routes. Some routes are under-utilized.

61 3.3 Main findings: Bus scheme analysis - Bus Occupancy (2) The above Table shows maximal and average bus occupancy and occupancy rate along the route. It should be noted that in some routes buses of different capacity are used, and that the survey was far from comprehensive or statistically reliable due to budget and schedule constraints. For these reasons, absolute maximum of occupancy for each route and period of day was shown, and not average maximum. The Table shows that the small buses of Comfort company (lines 1, 2, 2A) operate at high load levels during entire day. The Burgas Bus lines 12, 15, T and 211, and Burgas Volan lines 7 and 25 may reach occupancy rate of with average values of All other lines are clearly underloaded. Maximal-to-average occupancy ratio varies from 2 to 4, indicating a need in deeper analysis of the route system and possibly its re-arrangement.

62 3.3 Main findings: Bus scheme analysis - Ridership Our survey reveals that BurgasBus over-estimates the number of passenger by 85% while BurgasVolan under-estimates it by 24% - See explanation next slide

63 3.3 Main findings: Explanation of the ridership differences The annual ridership estimates made on the basis of sales of regular tickets, together with use of the on board survey for estimation of share of trips with discount pass cards differs from the estimations of Municipality of Burgas. The main reasons for the differences are: Misinterpretation of monthly ticket usage, especially by students: The amount of trips made by discount pass card holders was not evaluated correctly by Municipality. An accurate evaluation would require detailed analysis of the demand structure for different types of pass cards. The field survey reflects this structure. This conclusion is confirmed by the fact that the differences in estimation for Comfort company where pass card are not used, are minimal. seasonality: The base sales figures used in calculation of expansion factors were taken from October 2008 while our observations are from February Conclusions The estimations obtained from combination of data sources (sales figures and field observations) seems quite reasonable and willbe used as a base for further work in the project.

64 3.4 Main findings: Level of Service (LoS) analysis Buses within the city of Burgas runs in an average speed of 19.5 km/hr for the AM peak, 24 km/hr for MD and 20.3 km/hr for the PM peak Bus speeds are 40% slower then auto speeds for AM/MD and 20% slower in the MD. Comfort operate at load levels close to capacity during entire day, with significant overload at peak segments (up to 40 passengers in mini-bus!!!) BurgasBus lines 12, 30, 121 and 211 reach load-to-capacity ratio of about with average load levels of All other lines including BurgasVolan lines operate at load-to-capacity levels of about 0.5 at peak segments, and below 0.2 on average Bus stop are poorly signed and most of them are nothing but a sign On the other hand, Buses run on time in most cases. Moreover, only 1.2% of bus trips canceled. Upgrade LOS can be achieved by improving the speed of travel, increase capacity in several routes, and introduce more friendly bus stop and information system.

65 3.4 Main findings: LoS analysis - Bus speed analysis The following table demonstrates the average speed of each bus line in the AM peak: BurgasBus BurgasVolan Comfort The following conclusion can be drawn: Trolley bus is the slowest of all bus routes with an average speed of 13 km/hr Urban lines runs at 19.4 km/hr while lines that goes outside of Burgas runs at an average of 25.7 km/hr. Comfort bus fleet runs at 23 km/hr, 20% faster than average urban line

66 3.4 Main findings: LoS analysis The Trolley bus The Trolley runs between M. Rudnik to the city center. The line runs for 19.4 km and has 34 stops along the route. Frequency stands on 9-11 buses per hour. The average speed of the Trolley line is 12.9 km/hr, almost two time slower than parallel service. Daily Ridership on the trolley is estimated at 7,600 passenger (ranked third after 211, and 12) ~ 9% of all transit trips. Most of the time, the trolley runs half empty. Only in the AM peak inbound this service runs full.

67 3.5 Main findings: Potential BRT corridor (1) One of the scenario that is likely to be analyzed is a BRT corridor, that will replace several competing bus routes and will offer better Level of service The following map compares the catchment area of the BRT relative to 5 competing route 211,Troley,2A,2, and 1 BRT corridor - proposal 5 competing lines

68 3.5 Main findings: Potential BRT corridor (2) The following table shows the difference between the two alternatives shown in the previous slide: Criterion BRT Existing 5 lines Number of bus routes 1 5 Total bus route length Land Coverage (500 m range), KM^ Population within 500 meter 67% 78% Employment within 500 meter 43% 53% The BRT scheme will be explored in details when the model will be completed

69 March 2009 Chapter 4: Work plan for additional survey and model completion Inception report

70 4. Work plan: Finalizing the model The following tasks remains in order to complete the model developments: Complete Traffic counts /4 Launch Travel Habit Survey /4 Perform spatial analysis of surveys (on-board and THS) together with corridor counts to reveal additional features of the transport pattern 7-17/4 Create CAR and TRANSIT O-D matrix /4 } On-going Finalize network attributes (Transit speed, link Capacity, ff time) /4 Calibration of CAR+TRANSIT matrices /4 Develop Mode Choice component 23-30/4 Interface with other model economic, Environmental April Scenario analysis - April

71 4. Work plan : Travel Habit Survey The objective of the survey is to collect the data revealing the transportation preferences of travelers depending on the trip purpose and attributes of origin and destination (parking, travel time, travel cost, etc.) As a result, the mode split elasticity will be estimated for further use in the transportation model in analyzing proposed scenarios of the transit system development. The telephone survey among Burgas citizens will be conducted by CallPoint New Europe Co. with headquarters in Sofia. Due to schedule and budget constraints, the survey was designed with minimal number of questions focused at the transportation mode usage. Total number of full interviews that will be obtained is 500; the interviews will be allocated over the Burgas districts proportionally to their population.