The Use of the Decision Support System to Control Bicycle

Transportation

Irina Makarova

, Aleksey Boyko

, Eduard Tsybunov

, Krzysztof Żabiński

and Kuanysh Abeshev

Kazan Federal University, Syuyumbike prosp., 10a, 423822 Naberezhnye Chelny, Russian Federation

Institute of Computer Science, University of Silesia, Katowice, Poland

School of Engineering Management, Almaty Management University, Rozybakiyeva st., 227, 050060, Almaty, Kazakhstan

Keywords: Bicycle Sharing System, Road Safety, Ecological Efficiency.

Abstract: City transport problems that today exist practically everywhere require from city authorities together with

scientists to develop new ways of ensuring transport system’s sustainability. One of such ways is promotion

of non-motorised transport among the population. However, such problems as the lack of necessary bicycle

infrastructure and the vulnerability of cyclists prevent population from shifting to non-motorised modes of

transport. Authors have considered existing positive experience of implementing bicycles into city transport

systems and came to the conclusion that the identified problems should be solved in a comprehensive manner.

For this, authors suggest the Decision Support System (DSS) that will help to plan the development of bicycle

infrastructure and to evaluate its efficiency and safety. Moreover, the proposed DSS allows building possible

cycling routes and choosing the best one on the base of their road and ecological safety calculation.

1 INTRODUCTION

The problems caused by the urbanization growth and

the need to ensure the population’s safe mobility and

the goods transportation have led to the strategies

emergence to improve the safety and sustainability of

the transport systems of cities and countries. These

strategies include measures both on the choice of

vehicles that meet safety requirements and on the

infrastructure development more friendly to traffic

participants. The measures indicated in these

strategies can be clustered according to various

criteria. According to the influence method, these are

technical measures, that is, those associated with

technical effects on systems, managerial, involving

effects on the management object, and socio-

psychological, associated with the human factor.

Digitalization and intellectualization of industries and

activity areas brings a decision-making new level in

the complex systems management. This provides

increased efficiency, safety and sustainability of such

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systems. For these purposes, a decision support

system is created that allows using intelligent tools to

verify possible solutions to a problem and select the

optimal one among them.

The city’s population mobility is provided by

different transport types, among which motor

transport, in particular using gasoline and diesel fuel,

causes the greatest harm to the environment.

Therefore, among the measures to improve the

environmental situation in cities is the transition from

individual to public and non-motorized transport. At

the same time, public transport should become more

environmentally friendly, using cleaner fuels such as

natural gas or electricity. Cycle transport, in addition

to reducing the burden on the environment,

contributes to improving health, since physical

activity reduces the risk of diabetes, obesity and

cardiovascular diseases. Despite the obviousness of

such changes in the transport systems of cities and

megalopolis, there are problems that need to be

addressed in order for these changes to be effective.

Makarova, I., Boyko, A., Tsybunov, E., Å

zabiÅ

Dski, K. and Abeshev, K.

The Use of the Decision Support System to Control Bicycle Transportation.

DOI: 10.5220/0007899806490656

In Proceedings of the 5th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2019), pages 649-656

ISBN: 978-989-758-374-2

649

The first problem is that 8% of all road fatalities

in the European Union are cyclists, although there are

significant differences between countries. Cyclists

(like pedestrians) tend to be vulnerable in traffic, so

ensuring the safety of walking and cycling is a top

priority. Real and subjectively perceived safety can

have an impact on the modal choice. This largely

relates to such the most sustainable transportation

methods as walking and cycling, as well as the of

access to public transport possibility. At the same

time, the safety of both the route itself and the

interchange node for combined routes is considered.

The needs of pedestrians, cyclists and motorcyclists,

among whom, in total, 49% of all deaths due to road

accidents in the world occur, are not given enough

attention. Improving road safety in the world will be

possible only if all approaches to road safety are taken

into care the needs of all these road users. In Paris in

2016 at a special seminar on road safety of the

International Transport Forum (Road Safety Seminar,

2016) a scientific report was presented entitled “Zero

Road Deaths and Serious Injuries: Leading a

Paradigm Shift to a Safe System”. This report

describes a paradigm shift in road safety policy, in

accordance with the system safety principles. The

safe system is based on the assumption that traffic

accidents are predictable, they can be prevented, and

you can go to zero road deaths and avoid serious

injuries. This, however, requires a fundamental

rethinking of management and the road safety policy

implementation.

2 METHODS AND MEANS OF

IMPROVING THE URBANIZED

TERRITORIES’ TRANSPORT

SYSTEMS EFFICIENCY

2.1 Non-motorized Transport and

Conditions Extending its Use

The population will prefer cycling in the event that

the clear advantage of using it is ensured. Today, in

many European cities, such as Amsterdam,

Copenhagen, Oulu, cyclists make up two thirds of all

road users. In other words, most residents of big cities

can change from car to bike. However, not everyone

can ride a bike every day, so the bike is not a

competitor, but rather complements public transport

in urban mobility. Especially great potential for

bicycles is represented by regular trips to and from

work: in London such trips by bike account for about

2.5% of all trips to work, in Berlin - 13%, in Munich

- 15%, and in Copenhagen and Amsterdam 36% and

37% respectively.

Such a high proportion of cycling trips is ensured

by the Copenhagen politicians’ priority strategy, who,

in order to create more favourable conditions for life

in the city, have chosen the bicycle infrastructure

development (Bredal, 2014). This has helped reduce

the so-called carbon footprint, which in Copenhagen

is one of the smallest in the world — less than two

tons per person. However, the Denmark capital set a

goal to become neutral in terms of emissions by 2025.

The city has approved a project to equip bicycles with

special sensors that report pollution levels and real-

time traffic congestion (Smart City, 2017).

The study of Otero et al. (2019) is dedicated to

assessing the health effects of basic BSS in Europe.

The authors estimate the annual mortality dynamics

as a result of physical activity, deaths from traffic

accidents and air pollution, by analysing four

scenarios. A quantitative model was built using data

from transport and health surveys, as well as

environmental and road safety records. The study

involved BSS users aged 18 to 64 years. As a result,

it was found that the twelve basic bicycle sharing

systems (BSS) in Europe are beneficial for health and

economy. Stimulating vehicles drivers to use the BSS

can be used as a tool for disease prevention and health

promotion.

One of the most common counterarguments

against cycling are unfavourable climatic conditions.

However, it all depends on the attitude to the bike

lanes and on their priority when cleaning snow. This

confirms the Oulu example, where the majority of

residents move on bicycles, even at temperatures

below zero during the deep winter. This is ensured by

800 km of bicycle paths (4.3 m per inhabitant), 98%

of which work in winter, since the main bike tracks

maintenance is more important than the roadway

maintenance. The tracks parallel to the roadway are

separated by a green stripe, which is also used for

snow removal. Passages were built under the busiest

intersections, and you can get anywhere in the city by

bicycle (Tahkola, 2014).

There are technical problems to integration of

bicycle transport with public transport. For example,

among the companies of carriers is not well

developed transportation of bicycles in public

transport. Consider two options for transporting

bicycles: inside and outside the bus or other transport.

Most often, such methods are not available or not

designed for use by a large number of cyclists. This is

due to the introduction of additional changes in the

design of public transport and reduce the area inside

it, which leads to additional costs for carriers. As the

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Copenhagen experience shows, the expansion of the

bicycles model range designed for different

population groups and different uses can increase the

attractiveness of bicycle transport. Here you can rent

not only bicycles of familiar designs, but also such

models as: velomobile, cargobike, recumbent,

electric-assist Long John, electric bicycle (Bicycle

innovation lab, 2018).

Ways to increase the attractiveness of non-

motorized transport are presented in Figure 1.

When planning a bicycle infrastructure, it is

necessary to provide for the creation of bicycle lanes,

the construction of parking areas and bicycle storage

places. It is important to take into account the area

features, as well as the population structure - the

potential cyclists’ part. Despite the large number of

reseaches in the bicycle lanes design (Parkin and

Rotheram, 2010; Larsen et al., 2013; Forsyth and

Krizek, 2011; Rybarczyk, 2014), determining the

terrain and modelling the topographic conditions for

the designed or upgraded network of bicycle paths

remains an urgent task. The most common method of

designing bicycle paths is the method of overhead

lines or shortest distances. Since, when designing a

cycle route, it is not always possible to avoid the hilly

terrain, the creation of bicycle lifts or electric drives

for a bicycle will help solve the problem of

overcoming steep ascents.

Currently, in many cities and countries where the

authorities and the population are interested in the

cycling development, strategies and development

plans for mobility are being created. Along with

technical solutions, such as the development and

expansion of the bicycle infrastructure, considerable

efforts are being made to improve the bicycle

transport management and its integration into the

general transport system of cities.

Ottomanelli et al. in their study (2019) propose an

optimization framework for planning and designing a

bicycle paths network in urban environments based

on the equity principles and taking into account the

set budget available. The novelty of the proposal lies

in the fact that the goal function is aimed at

minimizing the existing inequality between different

population groups in terms of bicycle lanes

accessibility. The proposed methodology is a reliable

DSS (Decision Support System) tool that can help

transport authorities / managers to select priority

areas for their future investments related to bicycle

infrastructure. This can help them identify cycle paths

sections with a higher priority for implementation,

especially with regard to preventing further inequality

among population groups.

For large cities, the use of bicycles is a good

solution to the last mile problem. This is one of the

options for integration into the city’s road network.

The opportunity to get to / from the public transport

stop should be provided on short sections of the path

through the development of bicycle infrastructure,

without which the integration of bicycle transport

with public transport is impossible. This will increase

the attractiveness of the bicycle as a means of

transportation for most of the population. Sharing a

bike reduces driving and increases cycling speed.

Martin and Shaheen (2014) evaluate survey data in

two US cities to find out who is moving to and from

public transport as a result of sharing bikes. The

authors analyse the socio-demographic situation

associated with the modal shift through cross tables

and four ordinal regression models. Common signs

associated with switching to public transport include

an increase in age, males, residence in areas of lower

density and longer trips to work.

The identified problems should be solved in a

comprehensive manner. In order to calculate the

effectiveness proposed options at the design stage, as

Figure 1: Measures to increase the attractiveness of non-motorized transport.

The Use of the Decision Support System to Control Bicycle Transportation

651

well as to verify the proposed solutions adequacy, it

is necessary to create a DSS, the intelligent heart of

which will be a modules’ set to solve the

abovementioned problems. Such DSS will create a

unified information space and integrate positive

experience and scientific research to optimally solve

managerial problems of the city transport system.

2.2 Bicycle Sharing Systems: Problems

and Solutions

More than 400 cities around the world have deployed

or are planning to implement BSS. However, the

factors that determine their use, and the degree of

their rebalancing, are not precisely known.

Knowledge of these factors would allow cities to

design or modify their systems for increased use

while reducing the cost of restoring balance.

Ahmadreza et al. (2017) deal with usage data

collected with the help of scenarios that record the

bicycles availability at the station level every few

minutes in urban areas of Barcelona and Seville.

These data were aggregated to the county level, and

the time dimension was aggregated to the hourly

value. This allows us to calculate indicators of arrival

and departure on a bicycle, as well as regional

rebalancing factors.

The calculations results using real BSS data in

Palma de Mallorca (Spain) are given in article of

Alvarez-Valdes et al. (2016). Authors believe that

despite the differences in systems, each has two main

components: forecasting stochastic demand and

routing, which must realize the forecast requirements

in order to ensure user satisfaction. The authors,

based on a joint analysis of these components, have

developed a procedure that automatically reads the

information in the system, predicts the requirements

for withdrawal and return at each station for a specific

time period. The proposed procedure was tested on a

real BSS in Spain, and the results show its usefulness

for solving everyday problems, as well as a planning

tool that allows the user to evaluate alternative

configurations.

Mingshu and Xiaolu (2017) have studied the BSS

effect on reducing congestion in the city. The results

showed that the BSSs characteristics depended on the

city type. Compared to smaller cities, larger cities

tend to have more sustainable public transportation.

Since many of the docking stations are located close

to public transport, the BSS encourages multimodal

transport by connecting to public transport systems.

Therefore, in larger cities, BSS can help replace

short-distance road trips with cycling. During peak

hours, this can reduce traffic congestion. Conversely,

in smaller cities where there are fewer routes, the BSS

can serve as an addition to public transport, providing

links between various transit stops. The purpose of

Kayleigh’s study (2017) is to quantify the impact that

the BSS has on passenger traffic. Understanding how

the BSS and public transport are interconnected is

vital for planning a mutually supportive sustainable

transport network.

Ahmadreza et al. (2014) have examined factors

affecting BSS use in Canada. Established in 2009,

BIXI is the first major public BSS in Montreal. Using

data collected in the form of per-minute readings of

the bicycles availability at all stations of the BIXI

system from April to August 2012, this study

complements the literature on the bicycles sharing.

The authors examined the meteorological data

effects, time characteristics, bicycle infrastructure,

land use, and attributes of the built environment on

the station-level arrival and departure flows using a

multi-level approach to statistical modelling that can

be applied to other regions. The data obtained allow

to identify the factors contributing to the increase in

the use of the BSS in Montreal, and to provide

recommendations regarding the station size and

location decisions. The developed methodology and

study's results can be useful for urban planners and

engineers who design or modify BSSs for maximum

utilization and accessibility.

Brian et al. (2017) argue that BSS changes

attitudes towards cycling and sharing transport

infrastructure. The article presents the using details

one of the newest BSS in Ireland. The results show

that, although Cork is a city without a strong cycling

culture, BSS is often used. The results show that most

trips were short and in most cases frequent. Frequent

BSS users had the shortest travel time, including daily

(or weekly) trips. The strong influence of weather

conditions on the use of the BSS was also found.

Under good weather conditions, the number of trips

and their duration increase. The results of this article

provide valuable insight into how a BSS works in a

small city. According to the authors, more research is

needed to understand the differences in smaller and

larger cities, such as New York and London.

3 RESULTS AND DISCUSSION

Since the bicycle infrastructure development is a

promising direction, which will require a roads

situation periodic analysis, a DSS conceptual scheme

was developed, containing data collection and

analysis modules, simulation models (SM) and

advice development module. AnyLogic 7.3.3 was

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652

used for the development of SM. Modules for data

analysis and recommendation justification are

implemented in Delphi 7.

3.1 Designing DSS for Managing the

Bicycle Traffic Development

The qualitative integration of the bicycle

infrastructure with the city’s public transport system

can be achieved through system solutions. One of

such modules is designed to justify the effectiveness

and economy of such integration and should provide

the possibility of both strategic and operational

management. Strategic objectives are defined for the

long term. Criteria for the quality of integration will

be increased safety, capacity and passenger traffic, as

well as reducing the time to overcome the cycling

route. Correctness of such information system is

largely determined by the source information quality

and the adequacy of the its processing method. This

is ensured by following modules:

 collecting, storing and administering monitoring

data for cycling and pedestrian flow parameters,

quantitative and qualitative properties of bicycle

infrastructure, transport system parameters;

 analysis of statistical and dynamic data;

 simulation models development and carrying out

computational experiments in before / after

situations (before - with parameters of the existing

infrastructure, after - with changes in accordance

with the recommendations received).

 making decisions for analysing and evaluating

data and then developing recommendations

(calculating the track width based on passenger

traffic and the existing bicycle infrastructure

capacity; calculation of the need to create

recreation and repair areas, their number and

parameters, etc.).

The conceptual DSS scheme is shown in Figure 2.

The database is formed from:

 reference information, which is conditionally

constant, as it is updated quite rarely, at specified

intervals, or as needed.

 operational information - monitoring data of

objects that change dynamically and characterize

the transport system state over time;

 positive decisions that characterize the system's

optimal state with certain parameters. These

decisions are formed after the analysis performed

in the intellectual module after computer

experiments and after the verification appropriate

results adequacy by the decision maker.

For data input, a user interface has been

developed, including information input and

adjustment windows (Figure 3).

3.2 Development of Intelligent Modules

for Evaluating the Efficiency and

Safety of Bicycle Infrastructure

The designed DSS is built according to a modular

principle, which allows it to expand its capabilities

using a single information base. Now, modules have

been developed for assessing environmental

performance and route safety. As an example, to test

the methodology adequacy, the Naberezhnye Chelny

city street-road network was used. The city specificity

is in the separation of industrial and residential areas.

Regular public transport routes between these zones

do not exist due to inefficiency. Therefore, most

industrial staffs prefer to use personal transport. In

this regard, there are significant difficulties in

delivering the population to the main city’s employer

– PC KAMAZ: despite the alternative routes

availability, congestion and traffic jams occur at rush

hours. Cycling routes integrated with public transport

routes to solve the “last mile” problem could improve

the situation.

3.2.1 Calculation of Route’s Ecological

Efficiency

According to numerous studies, emissions and noise

are the most dangerous pernicious effects of the

vehicles operation. To study the potential for

reducing the vehicles negative impact due to the

cycling growing share, we examined the emissions

and noise level at one of the Naberezhnye Chelny

road network's critical sections. At the first stage, this

areas simulation model was built with available

transport routes and cycle paths in AnyLogic

simulation modelling environment based on a

discrete-event approach using a traffic library (Figure

4). Here red areas are marked with high traffic

intensity. Then a survey of PC KAMAZ employees

was conducted, which constitute the main flow of

traffic participants in this sector. The results showed

that only about 2% of respondents use bicycle

transport. 24% of respondents are ready to use a

bicycle instead of individual cars and as an addition

to public transport while improving bicycle

infrastructure (bicycle lanes, safe crossings at the

intersection with roads, recreation and repair areas,

self-service stations, secure indoor parking, rental

centres at affordable prices).

Simulation with predictive parameters, reflecting

The Use of the Decision Support System to Control Bicycle Transportation

653

Figure 2: The conceptual DSS scheme.

Figure 3: Information input and adjustment windows.

a decrease in the motorist’s number in favor of an

increase in the cyclist’s number, showed a decrease in

the vehicular traffic intensity, which will lead to a

reduction in the negative traffic impact on the

environment.

As a result, this will lead to a reduction in CO

emissions by 20.0%, NOX by 20.7%, hydrocarbons

by 8.9%, SO2 by 14.1%, the equivalent sound level

by 9.1%.

3.2.2 Cycling Route Safety Calculation

When drawing up routes for urban movements, it is

necessary to choose the safest of the possible routes,

taking into account the traffic participant

characteristics. Categorizing the route can be

performed depending on various factors complicating

traffic conditions. Depending on the movement type,

routes in the city can be road, pedestrian, cycling and

combined. The combined route, as a rule, includes the

areas where the movement takes place on public

transport, and the movement between the starting

(end) point and the stop of public transport - on foot

or by bicycle. These plots are estimated using

criteria’s different groups, since they may differ as

traffic conditions on the plots, and priorities for

different population categories.

Therefore, we propose a methodology for multi-

criteria route safety assessment. Route assessment

can be performed using a complex indicator, which is

calculated by the formula:



∑





∙







∑









→ (1)

Factors that determine the safety of the route can be

both objective (e.g., terrain, presence of unregulated

intersections, etc.), and subjective due to the features

and physical condition of the road user (age, health

condition, etc.). Adequacy of the assessment will

depend on the correctness of the selected factors and

their combined inclusion. For example, the same

route can be safer in the daylight than in the dark, in

the summer than in the winter, etc.

Possible routes are evaluated on the base of this

information. To do this a matrix of the given route

options is constructed and then the overall routes’

performance indicators are calculated (Figure 6). The

value of the route safety indicator is calculated with

provision for correction factors that depend on the

physical condition and characteristics of the user.

Using the simulation models described above, a

route safety assessment can be performed at the

design or reconstruction stage. In addition, when

changing the transport system parameters, such

models can be used to assess the effectiveness of the

route in terms of the infrastructure facilities use.

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Figure 4: Simulation model of routes with current traffic flow parameters.

Figure 5: Simulation model of routes using cycling.

Figure 6: View of the developed module.

4 CONCLUSION

The qualitative integration of the bicycle

infrastructure with the urban public transport system

can be achieved through the implementation of

complex projects, so one of the DSS subsystems will

become a module to justify such integration. DSS

must provide both strategic and operational

management capabilities. At the same time, the

criteria for the integration quality will be increased

environmental efficiency, safety, throughput and

passenger traffic, as well as reducing the time to

overcome the last mile. To ensure dynamic data

collection for the information system, we need to use

counters for cyclists and pedestrians. Such systems

are widely used in different countries, as well as in

different cities of Russia: for example, in Moscow,

Kazan and Almetyevsk.

The Use of the Decision Support System to Control Bicycle Transportation

655

ACKNOWLEDGEMENTS

Research is partially funded by national grant No.

BR05236644.

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