Impact of the Social Law on Truck Parking Sustainability in the EU

sustainability

Article Impact of the Social Law on Truck Parking Sustainability in the EU

Miloš Poliak 1,*, Adela Poliaková 2 and Kristián Culˇ ík 1

1 Department of Road and Urban Transport, University of Žilina, Univerzitná 1, 01026 Žilina, Slovakia; [email protected] 2 Department of Economics, University of Žilina, Univerzitná 1, 01026 Žilina, Slovakia; [email protected] * Correspondence: [email protected]; Tel.: +421-41-513-3050

Received: 5 October 2020; Accepted: 20 October 2020; Published: 12 November 2020

Abstract: Road freight transport in its current form has significant issues in terms of sustainability. These problems arise from an increase in density as well as from legislative decisions. Although not obvious, the parking of freight vehicles and legislation are connected. EU legislative decisions have reduced the sustainability of the parking system. The first and main goal of our study was to test the hypothesis that social law requirements negatively impact truck parking. The second important goal was to create a methodology that can determine the necessary number of parking spaces that comply with the requirements of social law. The method used for this research included the counting and numbering of parking spaces on specific routes in the EU compared with the intensity of freight vehicles on these routes. Our study shows that it is not possible to meet the requirements of social law and that the current state of freight vehicle parking is unsustainable. Planning sustainable parking areas in accordance with regulatory requirements is necessary, otherwise drivers will circumvent the rules, leading to a distortion of the freight transport market. In this paper, we also outline the proposed methodology for numbering parking spaces in a specific area.

Keywords: freight; transport; sustainable; parking; truck; road

1. Introduction In terms of inland freight transport, road freight transport is currently the most significant mode of transportation. According to The White Paper on Transport, transport is supposed to increase by 80% in 2050 compared to 2010. So far, this seems to be accurate, as the number of vehicles utilizing public infrastructure has increased as expected. With the increasing number of vehicles, especially freight vehicles, it is necessary to build infrastructure that meets increased demand for capacity and car parking. The number of cars parking influences the safety and sustainability of transport because it is connected to safety breaks and ensuring drivers’ rest. Increasing driver demands for rest also increases demands on parking places (e.g., judgment [1]). In this study, we aimed to determine whether the infrastructure of car parks is sustainable following the increase of road freight transport in the European Union. We specifically investigated the drivers of road freight transport. We analyzed the possibilities of vehicle parking in the selected area. Because goods transport is a significant aspect of the economic increase, we dealt with transport output sustainability in connection to parking policy; therefore, we processed the proposals of the European Union parking insurance sustainability. The contribution of our research is a draft of solutions, through which it will be possible to aim for vehicle parking sustainability that is related to the social regulation demands. Only a few studies have been interested in the relation between road transport output sustainability and truck parking place capacity. Chatterjee and Wegmann in 2000 [2] noted that in the United States,

Sustainability 2020, 12, 9430; doi:10.3390/su12229430 www.mdpi.com/journal/sustainability Sustainability 2020, 12, 9430 2 of 16 there are parking places for trucks in public car parks and resting areas along highways, but in the state of Tennessee, some car parks were fully occupied, causing big trucks to park on highway feeders to these areas. Based on interviews with drivers, they found that, although there are existing facilities for resting and sleeping in public places, many truck drivers cannot use these facilities due to a lack of available parking spaces, particularly during the night. Al-Kaisy et al. in 2012 [3] showed that the existing studies about rest areas were not accurate, or that they came from old data. Data were collected from surveillance video cameras with views of a whole parking place in 44 car parks in the USA over one week. We found that the average trucks’ parking time is longer than personal cars’ average parking time on less occupied highways [4]—that means an average of 30 min during a day and approximately 3 h and 22 min during a night. Kay (2014) introduced the results of binary logistics regression and negative binomial regression on demand characteristics of 47 road-resting places in Michigan [5]. He found out that as the distance between resting areas increased, the number of cars occupying the road resting areas increased. He used online data obtained from the monitoring information transport system from Michigan’s transport department. The problem of car park capacity was dealt with in Japan by Muramatsu and Oguchi in a 2017 study [6]. From the results of this study, it is possible to claim that parking places for freight transport are under-utilized in Japan. The authors suggest implementing a time toll to motivate the drivers to use a public area of the car park in as short a time as possible. This kind of approach is counterproductive to the requirements of road transport safety. The stated claim is possible to support using study results processed by author Jung in 2017 [7]. A study on the conditions in Korea showed that complementing resting areas, which are relatively small resting areas between common resting areas and which serve mainly for drowsy drivers’ rest, could decrease the number of accidents caused by sleepiness by approximately 14%, particularly on highways with two or more driving lanes. Matsushita et al. surveyed resting area distributions and developed a model of selection and model of attractivity evaluation [8]. Their results showed that transport time, area attractivity, and the number of passengers over 65 positively increases car park selection, while the available areas, cleanliness of sanitary facilities, and availability of restaurants or shops increases attractivity evaluation. Their results also emphasize the importance of the information provided concerning the resting areas and nearby relaxing places. A study of Hajime Seya examines truck drivers’ behavior in car parks [9]. The author uses six-month data about the vehicle’s trajectory from the digital tachograph and introduces a car park solution and, parallelly, a situation by multilevel continual model development. Given that digital tachographs note trucks’ time and area information in Japan, it is possible to analyze not only the behavior in car parks, but also a way to measure parking time. In this study, data was sourced from 1600 vehicles equipped with tachographs, similar to those used in the European Union. Based on data from digital tachographs, it was possible to identify an average driver’s resting time, but was not possible to identify a parking place occupancy. For truck drivers, it is important to know up-to-date information about free parking spaces. Nowadays, accurate GPS devices are used for navigation, but there is no guarantee of a free parking space. After finding out that the driver cannot park the vehicle in a given place, they begin to experience time-related stress; therefore, increasing the available information regarding parking spaces is important, which must be based on real-time parking data. According to [10], the parking information system can count the number of vehicles’ arrival and departure. This is called real-time indirect parking monitoring [11]. Indirect methodologies are based on detecting and classifying vehicles at all ingress and egress points of the parking facility and summing the difference over accumulated counts at specified time intervals, as opposed to directly monitoring each parking space status. Then, the data are sent to local parking information processing or management centers, or regional traffic management centers via communication networks. The information must be processed and converted to form, which navigation devices in vehicles can then display. This procedure has four steps: Data collection, data process, information and communication management, and the last is information display. Another source [12] talks not only about capacity information, but also Sustainability 2020, 12, 9430 3 of 16 about the possibility of preliminary parking place booking. The source [13] describes an online GIS (Geographic information system) survey instrument that is used for collecting the location information of areas with truck parking capacity shortages. According to [14], the parking pattern is defined by one main parameter—the global demand-to-supply ratio. In reality, the spatial distributions of the demand and supply are essentially heterogeneous, and this heterogeneity is critical for transportation management and planning. According to the analyses processed by Andras Nowak, more than 30,000 parking places in Germany are missing [15]. On average, 7000 trucks park in restricted places like highways feeders and exits and emergency parking areas on highways. They block approaches to gas stations or are in parking spaces defined for personal car parking. Another study [15] points out that, from 2016, the number of injuries and collisions with trucks has continually increased because of incorrect parking. In Germany, the listed state causes problems with finding drivers that are willing to drive a vehicle for longer distances like 500 km. More than 15% of all drivers spend the night next to the highway with no comfort, no toilets, or the possibility to wash [16]. According to studies [15], the increase of road freight transport in Germany introduces an extra 4% per year that requires 4000 freight transport parking places that are currently unavailable. Problems with the establishment of parking places next to highways also have an economic aspect. According to [17], the building of parking areas is very uneconomic because the investment cost for one parking place is 70,000–120,000€. Based on the analysis, it is possible to claim that road freight transport output increasing and demands in social areas cause problems with trucks parking. The capacity of resting areas is not built together with road freight transport output development. International road transport operation in member states of the European Union requires social regulation compliance, especially Regulation (EC) No. 561/2006 on the harmonization of certain social legislation relating to road transport. These requirements are shown in Table1.

Table 1. Requirements for the work regime of drivers in the EU. Source: [18], processed by authors.

Regime of Work Requirement Maximum continuous vehicle driving time 4.5 h Maximum daily vehicle driving time 9 h, 10 h twice a week Maximum vehicle driving time per week 56 h Maximum vehicle driving time per two weeks 90 h Minimum length of break in work after 45 min (possible to divide into 2 time intervals with a 4.5 h of driving minimum of 15 min and subsequently 30 min at least in total) 11 h (possible to reduce into 9 h triple per week. The rest is Minimum length of daily rest (during 24 h) possible to divide into 2 intervals within a 24 h period; ﬁrst part has to be at least 3 h, and the second part at least 9 h) 45 h, which could be reduced into 24 h; however, the reduction shall be compensated before the end of the Minimum length of weekly rest third week following the week in question. A weekly rest period that falls in two weeks may be counted in either week, but not in both.

The following maximum marginal time intervals are defined in member states of the EU: Maximum continuous vehicle driving time, maximum daily vehicle driving time, maximum weekly vehicle driving time, maximum two-weekly vehicle driving time, and the maximum number of work shifts that follow each other. Minimum marginal times are defined as: Minimum length of work-rest after 4.5 h of driving, the minimum length of daily rest and limited time of its latest end, and the minimum length of weekly rest. Table2 shows a comparison of truck driver requirements in the USA, Canada, and New Zealand. In the United States, there are defined driving times and resting times outlined in the Federal Motor Carrier Safety Regulations. In Canada, the social problem concerning drivers working in road transport Sustainability 2020, 12, 9430 4 of 16 is defined in the National Safety Code Standards—Standard 9 [19]. In New Zealand, the working regime for drivers is outlined in the Land Transport Regulations and Land Transport Act: Part 4B, Work Time and Logbooks [20].

Table 2. Comparison of demands on driver’s work in chosen countries. Sources: [18–21], processed by authors.

Demand EU USA Canada New Zealand Uninterrupted vehicle driving 4.5 h 8 h 13 h 5.5 h Break 45 min 30 min - 30 min Daily driving time 9 h 11 h 13 h 13 h Daily rest 11 h 10 h 10 h 10 h Weekly driving time 56 h 60/70 h 70/80 h 70 h Weekly rest 45 h 34 h 36 h 24 h Two-weekly driving time 90 h 148 h 147 h 166 h

The analysis shows that, during vehicle operation in EU countries and contracting states of the AETR (Accord Européen sur les Transports Routiers, the European Agreement Concerning the Work of Crews of Vehicles Engaged in International Road Transport), it is possible to realize the lowest performance per week and also for the two following weeks. In the EU, the driver is allowed to utilize the maximum 90 h of vehicle driving once every two weeks; in other states, the minimum is 120 h; in the USA, 140 h can be driven before the week restart, for New Zealand, the minimum is 166 h. Table2 shows a comparison between these countries. A vehicle that is in the EU and driven by one driver has a shorter driving time per two weeks (Table3) when compared to other chosen countries. If vehicles in the EU spend a signiﬁcantly longer time in parking areas, it is necessary to build a higher number of parking places for the same number of vehicles than in other countries. This means that, in the current conditions of the EU, investigating the other countries compared will not yield any meaningful solution to the problem of parking for freight transport.

Table 3. Comparison of demands on driver’s work in chosen countries. Source: Processed by authors.

Time Capacity Ratio EU USA Canada New Zealand Driving (%) 26.7 44.0 43.75 49.4 Parking (%) 73.3 56.0 56.25 50.6

2. Materials and Methods The authors’ team realized from October 2018 to March 2019 an extensive research of drivers’ skills in road freight transport with vehicle parking. As part of the research at the University of Žilina, a Google questionnaire was compiled and published on internet discussion forums that are used by drivers of international road freight transport. Any driver who visits these discussion forums could answer. Drivers from Slovakia, Poland, Bohemia, and Germany were the main responders—all provide international road transport. The survey was taken by 825 drivers, from which 6% provide transportation by vehicles with a combined total weight of 40 tons. Considering the study in [22], our survey showed that drivers’ quality of sleep is better at night, and we attempted to determine whether the drivers have a problem with rest due to a lack of parking places in night hours. Out of the responses, 86.67% of drivers answered that they have a problem finding parking. Most often, they have a problem finding a parking place by highways, followed by main roads and border crossings; drivers said they can find a parking place in industrial areas the easiest. Drivers, according to social demands [23,24], can drive a vehicle no more than 9 h, then must have a daily rest of at least 11 h. Excluding a daily rest, the drivers have to have working breaks after a maximum of 4.5 h of driving. The length of the break is, at minimum, 45 min. This means that every truck has to stop in a car Sustainability 2020, 12, 9430 5 of 16 park after 4.5 h of driving at the latest. The authors also analyzed how the drivers plan their rest. Our research shows that drivers often cannot drive the whole 9 h per day or 4.5 h without break, because they are afraid that they will not be able to find a car park. Drivers’ answers were often: I park the vehicle earlier or start driving earlier only because of finding a free place.

3. Results The survey showed that 92% of drivers adjust the driving time and their own working time to the situation in car parks. As a result, the listed drivers are not using their working time eﬀectively because they cannot rely on ﬁnding a safe parking place at the end of their working time. Our research was also aimed at the comfort of drivers during the rest in the car park. From the point of view of safety, only 12.73% of drivers feel safe in a vehicle during rest. Almost half of the drivers (49.45%) stated that they are afraid of fuel and personal theft from the vehicle, 14.3% sometimes feel endangered, and 23.5% of drivers have been robbed in a car park. Our research gathered a lot of data. The most important results relevant to this paper are displayed in Tables4 and5. The survey involved 65.3% of international freight drivers, 27% of national freight drivers, and 7.7% of drivers who perform both modes of transport.

Table 4. Selected results from our survey. Source: Processed by authors.

Question: Do you adjust your driving time to the current conditions in the truck parks? (a) Yes. 92.3% Answers: (b) No. 7.7% Question: Do you feel safe in a vehicle during rest in the truck parks? (a) Yes, I feel safe in the vehicle. 12.8% (b) I am concerned about the theft of fuel or personal belongings from the vehicle. 49.5% Answers: (c) Sometimes I feel threatened. 14.3% (d) I have personal experience with parking theft. 23.5% Do you have a problem in Slovakia with truck parking due to a lack of parking spaces in Question: the evening? (a) Yes. 86.7% Answers: (b) No. 13.3%

Table 5. Demands of drivers for the facilities of car parks. Source: Processed by authors.

Demand Weight of Importance Rating Weight of Importance Clean toilets and showers 20.27 1 20.27 Calm environment 16.52 3 16.52 Eating facility 14.72 4 14.72 Foods shop, supermarket 12.97 5 12.97 Social room for drivers 8.90 7 8.90 Active guarding 16.82 2 16.82 Laundry room 9.80 6 9.80

Despite the clear lack of parking space, our research also dealt with car park facilities. A significant amount of car parks does not provide suitable comfort for drivers. Based on the results, drivers require more facilities and safety measures to improve the quality of the rest period, whose length is more than 11 h. The results are listed in Table5. The most important demand is the cleanness of toilets and showers. Based on our research, it is possible to claim that sufficient capacity for freight transport parking does not currently exist. This situation gets worse with the increasing output of road freight transport. Despite significant efforts of logistic companies and public institutions, the output cannot be moved to other transport modes [25], and in the close future, it is not possible to consider autonomous trucks in road traffic. Based on our research, it is possible to claim that, from the point of view of Sustainability 2020, 12, 9430 6 of 16 sustainability, parking policy is important. Currently, 87% of drivers report that they do not feel safe in car parks, 87% of drivers have problems with vehicle parking, and 92% of drivers adjust their working time to deal with the limited parking spaces and poor facilities. Without a parking policy solution, and with freight transport output increasing, it is reasonable to assume that drivers will search for parking places near highway exits to urban areas to find comfort and to avoid congestion and undesirable conditions.

3.1. The Ban on Spending Weekly Rest in the Vehicle If the vehicle is equipped with a suitable sleeping device for each driver and the vehicle is stationary according to Art. 8 Regulation No. 561/2006 [22], the driver may take a daily rest period and a reduced weekly rest period in the vehicle. Until 2014, this condition did not generally apply in practice. Belgium and France adjusted the fines in 2014. The driver could not spend their regular weekly rest in the vehicle; however, if they do so in Belgium, they could get a fine of up to €1800. From 11 July 2014, the fine increased to a maximum of € 30,000, or imprisonment of one year in France [26,27]. The Court of Justice of the European Union also expressed a judgment on the issue of regular weekly rest on 20 December 2017. In the judgment, the court ruled that drivers of freight transport could not spend regular weekly rest in vehicles. This also means that no EU country can interpret legislation differently [28]. The dragging litigation began three years ago when the Belgian transport company Vaditrans BVBA initiated a dispute with the Kingdom of Belgium. The carrier considered that regular weekly rest could not be penalized because Regulation (EC) 561/2006 did not provide for such a prohibition in its provisions. Article 8 (8) of Regulation (EC) No 561/2006 states: “If the driver so decides, daily rest periods and reduced weekly rest periods may be taken outside the base, as long as he has suitable sleeping places for each driver and the vehicle is stationary.“ The Belgian authorities referred to the wording of Regulation (EC) No 561/2006. They asked for clarification on whether this provision of Regulation (EC) No 561/2006 is to be interpreted as meaning that it contains an implicit prohibition on the use of regular weekly rest in the vehicle. As EU law can only be enforced by an EU court, a Belgian court has asked an EU court to determine whether EU law contained an implicit ban on the use of weekly rest in a vehicle [29,30]. The Court of Justice of the EU has stated that EU law only concerns the possibility of reducing the weekly rest period by 24 h, which is allowed in the vehicle in certain circumstances; however, it follows that it should not apply to regular 45 h rest. If possible, the driver may spend the rest of the time in the vehicle, but this would not improve the driver’s working conditions, as required by EU law. Following the judgment, the Court of Justice of the European Union explicitly prohibits drivers from spending their regular weekly rest in the vehicle. The judgment is valid from the date of publication and is valid from 20 December 2017. It is important to note that the judgment is valid in all EU Member States. It follows that, if national law allows a driver to impose a fine for such an offense, the inspection body may also impose such a fine [31]; however, the judgment does not regulate the power to control the use of taking regular weekly rests on the territory of a particular Member State. The judgment only stipulates that drivers in a vehicle may not take regular weekly rests. This means that, for example, in Belgium, if the inspection authorities find that a Slovak driver driving for a Slovak hauler takes a regular weekly rest period in Germany, they may be given a restrictive fine in Germany when inspected in Belgium. It is important to note that the regular weekly rest area can be found from the digital tachograph (from the previous 28 days) or the driver card. For this reason, drivers entering the country of arrival and the country of exit should carefully set the country code on the digital tachograph [27]. The amount of the fines is currently set under the national law of each EU Member State. It will take some time for a fine to be added to national rules for spending regular weekly rest in the vehicle in all countries. From 1 January 2017, Regulation (EU) 2016/403 updated the classification of serious road traffic offenses in the EU; however, the regulation does not cover a breach of the rule of taking regular Sustainability 2020, 12, x FOR PEER REVIEW 7 of 16 rest area can be found from the digital tachograph (from the previous 28 days) or the driver card. For this reason, drivers entering the country of arrival and the country of exit should carefully set the country code on the digital tachograph [27]. The amount of the fines is currently set under the national law of each EU Member State. It will take some time for a fine to be added to national rules for spending regular weekly rest in the vehicle in all countries. From 1 January 2017, Regulation (EU) 2016/403 updated the classification of serious road traffic offenses in the EU; however, the regulation does not cover a breach of the rule of taking regular weekly rests in a vehicle. According to that classification, each Member State has adopted national legislation providing for penalties in the field of road transport.

3.2. Transport Planning in the EU in Relation to Taking Weekly Rest outside the Vehicle

The Court’sSustainability judgment2020, 12, 9430 points to several problems with the ban on weekly rest periods.7 of 16 Trucks must park in designated truck parking lots. These car parks are usually out of town and do not have motels or hotelsweekly nearby rests in a [32]. vehicle. In Accordingconnection to that with classification, the problem each Member of weekly State has rest, adopted three national transport routes leading fromlegislation the Slovak providing Republic for penalties to selected in the field EU of roadcountries transport. were processed. The routes3.2. Transport we studied Planning head in the west EU in Relationfrom the to Taking Slovak Weekly Republic Rest Outside because the Vehicle more than 80% of transport from the SlovakThe Republic Court’s judgment goes west. points We to several have problems also ch withosen the one ban route on weekly to restthe periods. north, Trucksone direct must to France, and one to thepark south. in designated Subsequently, truck parking parking lots. These lots car parksfor trucks are usually were out ofsearched—specifically, town and do not have motels parking lots that provideor the hotels driver nearby with [32]. In the connection opportunity with the to problem stay ofin weekly case of rest, taking three transport a regular routes weekly leading rest. Truck from the Slovak Republic to selected EU countries were processed. parking spacesThe were routes searched we studied headusing west the from Truck the Slovak Parking Republic becauseEurope more application, than 80% of transport which provides informationfrom on the the Slovakpossibility Republic of goesparking west. on We a have given also route chosen with one routea maximum to the north, vehicle one direct detour to of 12 km. After searchingFrance, for and accommodation one to the south. Subsequently,facilities, the parking accommodation lots for trucks werecapacity searched—specifically, was also ascertained. In parking lots that provide the driver with the opportunity to stay in case of taking a regular weekly some cases,rest. this Truck information parking spaces was were not searched available. using theBased Truck on Parking individual Europe application, capacities, which accommodation provides can be divided accordinginformation onto thethe possibility number of of parking rooms on ainto given the route following with a maximum three categories vehicle detour [27]: of 12 km. After searching for accommodation facilities, the accommodation capacity was also ascertained. In some (a) Small (1cases, to 20 this rooms), information was not available. Based on individual capacities, accommodation can be (b) mediumdivided (21 to according 40 rooms), to the numberand of rooms into the following three categories [27]: (c) large (more(a) Small than (1 40 to 20rooms). rooms), (b) medium (21 to 40 rooms), and Figure 1 shows the first routes leading from Žilina in Slovakia to Lyon in France. The total length (c) large (more than 40 rooms). of the route is 1449 km. There are 201 car parks or rest areas on this route, but only 16 car parks offer accommodation.Figure Up1 to shows 50% the of first the routes sought-after leading from ca Žilinar parks, in Slovakia which to Lyonprovide in France. accommodation The total length for drivers of the route is 1449 km. There are 201 car parks or rest areas on this route, but only 16 car parks offer on the givenaccommodation. route, are Uplocated to 50% in of theSwitzerland. sought-after car Another parks, which example provide accommodationis the Slovak for Republic. drivers In this country, noon such the given car route,parks are were located found in Switzerland. on the Anotherselected example route is theafter Slovak evaluation Republic. Inusing this country, the application. Table 6 alsono contains such car parks information were found about on the selected accommodation route after evaluation capacity. using Most the application. of them Table can6 alsobe classified in contains information about accommodation capacity. Most of them can be classified in the middle the middle categorycategory (21–40 (21–40 rooms). rooms). Accommodation Accommodation with a capacity ofwith more a than capacity 40 rooms of is providedmore than by only 40 rooms is provided by4 accommodationonly 4 accommodation facilities out of facilities 13 found. out of 13 found.

Figure Figure1. Route 1. Route 1 from 1 from Slovakia Slovakia (Žilina)(Žilina) to Franceto France (Lyon). (Lyon).

Sustainability 2020, 12, x FOR PEER REVIEW 8 of 16

Table 6. Possibilities of regular weekly rest on the route from Žilina (Slovakia) to Lyon (France). Source: Processed by authors.

City with Parking for Trucks Accommodation Capacity Distance to the Nr. Country Accommodation with Accommodation (Rooms/Beds) Previous (km) 1. Austria Pöchlarn Gasthaus Gramel 21/44 - Motor-Hotel Sankt 2. Austria St. Valentin 30/60 62 Valentin 3. Austria Asten Gasthaus Heimbau Not indicated 11 4. Germany Bernau Am Chiemsee Camping Mariengrund 6/18 195 Autobahnmotel 5. Germany Irschenberg 50/114 40 Irschenberg Süd 6. Germany Türkheim Landhaus Rosenbräu Not indicated 123 7. Germany Aichstetten AI Hotel 21/44 53 Hotel Gasthaus 8. Switzerland Sustainability 2020 Gossau, 12, 9430 Not indicated /40 8 of 16 111 Moosburg 9. Switzerland Geroldswil Hotel Geroldswil 71/134 82 10. Switzerland Table Othmarsingen 6. Possibilities of regular weekly rest Landgasthof on the route Pflug from Žilina (Slovakia) Not to indicated Lyon (France). 23 11. Switzerland Source: Hunzenschwil Processed by authors. Gasthof Kastanienbaum 15/26/ 8 City with Parking for Raststätte Grauholz Accommodation Distance to the 12. Switzerland Nr. Country Ittigen Trucks with Accommodation Not indicated /62 78 Capacity (Rooms/Beds) Previous (km) Accommodation Nord 1. Austria PöchlarnPark GasthausInn by Gramel Radisson 21/44 - 13. Switzerland Lully Not indicated /80 58 2. Austria St. Valentin Motor-HotelLully Sankt Valentin 30/60 62 3. Austria Asten Gasthaus Heimbau Not indicated 11 14. Switzerland 4. Germany Rolle Bernau Am Chiemsee Camping Loft de Mariengrund charme 6/18 1/3 195 68 5. Germany Irschenberg AutobahnmotelHotel-Restaurant Irschenberg Le Süd 50/114 40 15. Switzerland 6. Germany Grens Türkheim Landhaus Rosenbräu Not indicatedNot indicated /22 123 41 7. Germany AichstettenPetit AI Moulin Hotel 21/44 53 8. Switzerland Gossau Hotel Gasthaus Moosburg Not indicated /40 111 Hotel Restaurnat Le 16. France 9. Switzerland Maillat Geroldswil Hotel Geroldswil 71/Not134 indicated /35 82 81 10. Switzerland Othmarsingen LandgasthofRelax Pﬂug Not indicated 23 11. Switzerland Hunzenschwil Gasthof Kastanienbaum 15/26/ 8 12. Switzerland Ittigen Raststätte Grauholz Nord Not indicated /62 78 13. Switzerland Lully Park Inn by Radisson Lully Not indicated /80 58 14. Switzerland Rolle Loft de charme 1/3 68 Figure 2 shows15. the Switzerland second route Grens leading Hotel-Restaurant from Slovakia Le Petit Moulin (Žilina) Not indicated to/22 Hamburg 41 (Hamburg). There are 145 car parks on16. this Franceroute, but Maillat the driver Hotel can Restaurnat take Le Relaxtheir regular Not indicated weekly/35 rest 81 in only 15 of them

(Table 7). Most of theFigure parking2 shows the secondlots routefor leadingtrucks from on Slovakia this (Žilina) route to Hamburgprovide (Hamburg). accommodation There are in Poland, specifically 9 out 145of car15 parks and on at this least route, in but the driver Slovak can take Republic. their regular It weekly should rest in onlybe noted 15 of them that (Table the7). transport route Most of the parking lots for trucks on this route provide accommodation in Poland, speciﬁcally 9 out within the Slovakof 15 andRepublic at least in theis Slovakonly Republic. 39 km It should long be notedout that of the a transport total route of within1048 the km. Slovak Information on accommodation capacityRepublic is only was 39 kmavailable long out of only a total ofin 1048 eight km. Informationcases. Of on accommodationthese, four capacityhave a was capacity of fewer available only in eight cases. Of these, four have a capacity of fewer than 20 rooms, and only one than 20 rooms, andaccommodation only one has accommo more than 40dation rooms. has more than 40 rooms.

Figure 2. RouteFigure 2.2 Routefrom 2 fromSlovakia Slovakia (Žilin (Žilina)a) to Germanyto Germany (Hamburg). (Hamburg).

Table 7. Possibilities of regular weekly rest on the route from Žilina in Slovakia to Hamburg in Germany. Source: Processed by authors.

City with Parking for Trucks Accommodation Distance to the Nr. Country Accommodation with Accommodation Capacity (Rooms/Beds) Previous (km) 1. Slovakia Svrčinovec-Purašovci Hotel Paris Not indicated - 2. Poland Hażlach Restauracja Babilon 7/17 51 3. Poland Góra Św. Anny x Not indicated 111

Sustainability 2020, 12, x FOR PEER REVIEW 9 of 16

Hotel 4. Poland Niemodlin Not indicated/12 53 ComfortExpress Hotel MOP Oleśnica 5. Poland Oleśnica Mała Not indicated/10 44 Mała 6. Poland Lubień Hotel Dworek 30/60 79 7. Poland Sustainability 2020 Milenium, 12, 9430 x Not indicated 9 of 16 93 8. Poland Czerna x Not indicated 149 9. Poland Table Ję 7.drzychowiczkiPossibilities of regular weekly rest Motel on the route INTERTANK from Žilina in Slovakia to Not Hamburg indicated/43 in Germany. 89 Source: Processed by authors. 10. Poland Olszyna x Not indicated 88 City with Parking for Accommodation Distance to the 11. Germany Nr. Country Luckau Trucks with Accommodation x Not indicated 182 Capacity (Rooms/Beds) Previous (km) Accommodation Avus Raststätte 12. Germany 1. Slovakia Berlin Svrˇcinovec-Purašovci Hotel Paris Not indicated48/81 - 97 2. Poland Ha˙zlach RestauracjaMotel Babilon 7/17 51 3. Poland Góra Sw.´ Anny Pension-Truck-x Not indicated 111 13. Germany 4. Poland Fehrbellin Niemodlin Hotel ComfortExpress Not indicated/126/10 53 72 5. Poland Ole´snicaMała Hotel MOPCenter Ole´snicaMała Not indicated/10 44 6. Poland Lubie´n Hotel Dworek 30/60 79 Shell7. Autohof Poland Herzsprung, Milenium x Not indicated 93 8. Poland CzernaAutohof x Not indicated 149 14. Germany 9.Steinstraße Poland 9, 16909 J˛edrzychowiczki Motel INTERTANK Not indicatedNot/43 indicated 89 38 10. Poland OlszynaHerzsprung x Not indicated 88 11.Wittstock/Dosse Germany Luckau x Not indicated 182 Raststätte12. Germany Gudow Nord, Berlin A24 AvusAutobahnhotel Raststätte Motel 48/81 97 15. Germany 13. Germany Fehrbellin Pension-Truck-Center 6/1028/46 72 134 23899 GudowShell Autohof Gudow Nord Herzsprung, 14. Germany Autohof Herzsprung Not indicated 38 Steinstraße 9, 16909 Wittstock/Dosse Raststätte Gudow The last analyzed15. route, Germany whichNord, A24 is 23899 shownAutobahnhotel in Fi Gudowgure Nord 3, was the 28/46 route leading 134 from the Slovak Gudow Republic (Žilina) to Italy (Livorno). There is a total of 113 car parks on this route, and only 15 of them also provide accommodation.The last analyzed The route, route which includes is shown in three Figure3 ,countries—Slovakia, was the route leading from the Austria, Slovak and Italy. This route includes sevenRepublic truck (Žilina) car to parks Italy (Livorno). in Austria There is (Table a total of 8) 113 and car parks eight on in this Italy route, and(three only car 15 of parks are nearby them also provide accommodation. The route includes three countries—Slovakia, Austria, and Italy. and also provideThis the route same includes type seven of truck accommodation). car parks in Austria (Table The8) andcapacity eight in Italyof facilities (three car parks was are only found in 13 cases. The best optionsnearby and for also providedrivers the sameare typeprovided of accommodation). by car Theparks capacity in of Italy, facilities which was only foundin most in cases provide 13 cases. The best options for drivers are provided by car parks in Italy, which in most cases provide accommodation withaccommodation a capacity with a capacityof more of more than than 40 40 rooms. rooms.

Figure 3. RouteFigure 3. 3Route from 3 from Slovakia Slovakia (Žilina) (Žilina) to Italy to (Livorno). Italy (Livorno).

Table 8. Possibilities of regular weekly rest on the route from Žilina in Slovakia to Livorno in Italy. Source: Processed by authors.

City with Parking for Distance to Accommodation Nr. Country Trucks with Accommodation the Previous Capacity (Rooms/Beds) Accommodation (km) 1. Austria Grimmenstein Gasthof Pichler Not indicated/24 - 2. Austria Zöbern Oldtimer Raststätte 20/40 13 3. Austria Ilz Welog Rast Ilz 4/Not indicated 62 4. Austria Hofstätten Rasthaus Dokl 20/40 22 5. Austria Preitenegg Motorhotel Oldtimer 16/32 101 6. Austria Griffen x Not indicated 39 Hotel Rosenberger 7. Austria Völkermarkt Autobahn-Restaurant & 42/84 13 Motorhotel

Sustainability 2020, 12, 9430 10 of 16

Table 8. Possibilities of regular weekly rest on the route from Žilina in Slovakia to Livorno in Italy. Source: Processed by authors.

City with Parking for Accommodation Distance to the Nr. Country Trucks with Accommodation Capacity (Rooms/Beds) Previous (km) Accommodation 1. Austria Grimmenstein Gasthof Pichler Not indicated/24 - 2. Austria Zöbern Oldtimer Raststätte 20/40 13 3. Austria Ilz Welog Rast Ilz 4/Not indicated 62 4. Austria Hofstätten Rasthaus Dokl 20/40 22 5. Austria Preitenegg Motorhotel Oldtimer 16/32 101 6. Austria Griﬀen x Not indicated 39 Hotel Rosenberger 7. Austria Völkermarkt Autobahn-Restaurant & 42/84 13 Motorhotel 8. Italy Arnoldstein Raststätte Dreiländerecke Süd Not indicated/90 81 9. Italy Santo Stino di Livenza Albergo Ristorante da Gigi 29/56 178 10. Italy San Pietro in Casale x Not indicated 179 11. Italy Barberino di Mugello Hotel Barberino 78/Not indicated 102 12. Italy Firenze Nord Hotel the Gate 157/Not indicated 21 13. Italy Altopascio Hotel Le Cerbaie 64/Not indicated 4

Table9 represents a comparison of the individual routes concerning the number of truck parking lots. On the Žilina–Lyon line, there are 8% of truck parking lots with accommodation from the total number of truck parking lots on this route. There are 10% of car parks on the Žilina–Hamburg route and 13% of the total on the Žilina–Livorno route.

Table 9. Comparison of individual routes with respect to the number of truck parks. Source: Processed by authors.

Parking Parking for Trucks with Parking for Trucks Route Distance (km) Parking for Trucks for Trucks with Accommodation per per 100 km Accommodation 100 km Žilina–Lyon 1449 201 13.87 16 1.10 Žilina–Hamburg 1048 145 13.84 15 1.43 Žilina–Livorno 1163 113 9.72 15 1.28

From the analysis of the processing of information on truck car parks that provide accommodation for the driver, we conﬁrmed that truck car parks generally do not have motels or hotels in their vicinity. Many accommodations are located in the city [27]; however, parking trucks are not allowed in the cities, and drivers would somehow have to get to the nearest accommodation facility. If the vehicle is parked in an unsecured truck parking lot, there is a risk to the goods being transported. If the truck parking lots are not guarded, there is a risk of possible damage to the transported goods or theft not only of the goods, but also of the entire vehicle. When planning the transport, it is necessary to take into account, in addition to the provision of suitable parking lots for trucks, the current capacity of the accommodation. This is because some accommodations provide a relatively low number of rooms. A ban on regular weekly rests in the vehicle can interfere with some important transport routes. This may also aﬀect the transport companies themselves operating in the Western European market, which carry out sabotage operations and for longer periods, drivers operate outside the company’s premises.

3.3. Proposal to Increase the Capacity of Freight Transport Car Parks Most research teams, e.g., teams in Germany, deal with increasing car park capacity by its enlargement or by building a new car park based on road freight transport vehicles intensity in the road network. A need for parking places in a speciﬁed section depends not only on transport intensity, but also on the length of stay of vehicles in the car park [28]. Ordinary daily rest in EU and contracting states of AETR (e.g., Russia) is at least 11 h, as well as at least one break of a duration of 45 min after 4.5 h of driving [23]. This means that a vehicle, during 24 h, can drive no more than 12 h and Sustainability 2020, 12, 9430 11 of 16

15 min. A certain number of parking spaces also depends on the freight transport vehicle speed, which, based on research, is 60–80 km per hour [33]. The number of required parking places in a speciﬁed section of highway or road is possible to be deﬁned by relation (1). This equation is used to calculate parking spaces regardless of the type of park area.

R D PP = I (1) ·24·S T · d where PP—needed number of parking places, I—traffic intensity in solved section, R/24—driver’s rest in hours/24 h, D—length of the solved section, S—the average speed of truck in solved section, and Td—the average driving time of vehicle per 24 h. The proposed equation mathematically defines the number of parking spaces. Its reliability depends on the accuracy of input data. It takes into account traffic intensity in the solved section, its length, the average speed of trucks, and also basic data about the rest period of truck drivers. Although it is not calibrated, it still provides a theoretical basis for designing new parking areas. After the application of the introduced relationship into selected sections of roads of European importance in Slovakia, it is not possible to claim that car parks achieve the demanded capacity in any section (Table 10). The intensity data in Table 10 are sourced from Road Databank, which is available online. Road Databank is managed by the department of Slovak Road Administration, which is responsible for the operation of the Central technical Register of Roads, determination of Abnormal Transport Routes, and operation of the Traffic Information Centre.

Table 10. The needed number of parking places in selected sections of the road network. Source: Processed by authors.

Existing Needed Intensity Speed Length Road Section Number Number (Trucks/24 h) (km/h) (km) of Places of Places D1 Bratislava–Trnava 8956 80 50 65 214 D1 Trnava–Trenˇcín 6675 80 75 190 235 D1 Trenˇcín–Žilina 6272 80 87 63 261 D1,18 Žilina–Ružomberok 4441 60 64 14 181 D1 Ružomberok–Poprad 3586 80 80 91 137 D1 Poprad–Prešov 2794 80 102 85 136 D1 Prešov–Košice 4555 80 40 12 87 D2 Rajka–Brodské 10,168 80 80 310 388 R1 Trnava–Nitra 5825 80 42 9 117 R1 Nitra–Žiar n. Hron. 3486 80 82 79 136 R1 Žiar n. Hron.–B. Bystrica 4044 80 40 21 77 R2,16 Zvolen–Luˇcenec 2521 70 60 4 83

Despite that analyzed car parks in individual sections do not achieve the demanded capacity, the results of the survey conﬁrm that it is possible to increase the capacity of existing car places by eﬀective management.

3.3.1. Return Allowing Car Park Two solutions improve the management and comfort in car parks, and, when implemented together, partly decrease the demands on built-up areas by parking places. These solutions are shown in Figure4. Sustainability 2020, 12, x FOR PEER REVIEW 11 of 16

The proposed equation mathematically defines the number of parking spaces. Its reliability depends on the accuracy of input data. It takes into account traffic intensity in the solved section, its length, the average speed of trucks, and also basic data about the rest period of truck drivers. Although it is not calibrated, it still provides a theoretical basis for designing new parking areas. After the application of the introduced relationship into selected sections of roads of European importance in Slovakia, it is not possible to claim that car parks achieve the demanded capacity in any section (Table 10). The intensity data in Table 10 are sourced from Road Databank, which is available online. Road Databank is managed by the department of Slovak Road Administration, which is responsible for the operation of the Central technical Register of Roads, determination of Abnormal Transport Routes, and operation of the Traffic Information Centre. Despite that analyzed car parks in individual sections do not achieve the demanded capacity, the results of the survey confirm that it is possible to increase the capacity of existing car places by effective management.

Table 10. The needed number of parking places in selected sections of the road network. Source: Processed by authors.

Intensity Speed Length Existing Number Needed Number Road Section (Trucks/24 h) (km/h) (km) of Places of Places D1 Bratislava–Trnava 8956 80 50 65 214 D1 Trnava–Trenčín 6675 80 75 190 235 D1 Trenčín–Žilina 6272 80 87 63 261 D1,18 Žilina–Ružomberok 4441 60 64 14 181 Ružomberok– D1 3586 80 80 91 137 Poprad D1 Poprad–Prešov 2794 80 102 85 136 D1 Prešov–Košice 4555 80 40 12 87 D2 Rajka–Brodské 10,168 80 80 310 388 R1 Trnava–Nitra 5825 80 42 9 117 R1 Nitra–Žiar n. Hron. 3486 80 82 79 136 Žiar n. Hron.–B. R1 4044 80 40 21 77 Bystrica R2,16 Zvolen–Lučenec 2521 70 60 4 83

3.3.1. Return Allowing Car Park Two solutions improve the management and comfort in car parks, and, when implemented Sustainabilitytogether, partly2020, 12 decrease, 9430 the demands on built-up areas by parking places. These solutions are shown12 of 16 in Figure 4.

Figure 4. A return allowing car park.

The firstfirst solution is to allowallow thethe returnreturn ofof thethe vehicle.vehicle. Currently, the vastvast majoritymajority of car parksparks do not allowallow vehicles to return.return. If a vehicle searches for a free parkingparking place, it onlyonly drivesdrives throughthrough one line, and if it cannot findfind a free place there, due to the layout and direction of tratraffic,ffic, it has to abandon the car park even when there are freefree lotslots inin anotheranother line.line. There is a possibility to reverse at the beginning,beginning, but it isis veryvery didifficult,fficult, tedious,tedious, andand dangerousdangerous inin aa crowdedcrowded carcar park.park. The driver has Sustainability 2020, 12, x FOR PEER REVIEW 12 of 16 no certainty of success becausebecause after coming to the next vehicle, the driver is forced to leave the car park. The proposal contains a car park where the bi-directional traffic is possible, that means after the park. The proposal contains a car park where the bi-directional traffic is possible, that means after the unsuccessful searching of a free parking place, a vehicle can return to the beginning and try to find a unsuccessful searching of a free parking place, a vehicle can return to the beginning and try to find a free place in another parking line. free place in another parking line. The second solution is a parking organization method where vehicles reverse into a parking place. The second solution is a parking organization method where vehicles reverse into a parking When a parking place is occupied, other vehicles park longitudinally behind parking places. Of course, place. When a parking place is occupied, other vehicles park longitudinally behind parking places. earlier parked vehicles abandon the parking place earlier and longitudinally parked vehicles block an Of course, earlier parked vehicles abandon the parking place earlier and longitudinally parked approach to the parking place (Figure4—vehicles 4 and 5). In this case, the vehicles have to reverse vehicles block an approach to the parking place (Figure 4—vehicles 4 and 5). In this case, the vehicles into parking places too many times with right-hand cornering, when the driver has a severely limited have to reverse into parking places too many times with right-hand cornering, when the driver has a view in a rearview mirror, because if the articulated semi-trailer corners to the right-side with a bigger severely limited view in a rearview mirror, because if the articulated semi-trailer corners to the right- angle, the driver cannot see the end of a semi-trailer in the right mirror, as he sees only right side of the side with a bigger angle, the driver cannot see the end of a semi-trailer in the right mirror, as he sees semi-trailer, and in a left mirror, he sees only the front of the trailer (Figure5). only right side of the semi-trailer, and in a left mirror, he sees only the front of the trailer (Figure 5).

Figure 5. Right-hand cornering of a semi-trailer.

This proposalproposal suggests that vehicles reverse into parking places with left-handedleft-handed cornering as, although the driver, afterafter cornering,cornering, has a limitedlimited viewview in thethe rightright rearviewrearview mirrormirror wherewhere theythey seesee only the front of the trailer, theythey also see the left si sidede of the road train in the the mirror mirror and and after after cornering, cornering, theythey seesee thethe whole whole of of semi-trailer semi-trailer from from a sidea side driver’s driver’s window window with with a bigger a bigger angle. angle. Reversing Reversing to the to leftthe sideleft side is more is more comfortable comfortable and and safer safer for the fordriver. the driv Thiser. This solution solution is more is more economical economical for a for built-up a built-up area wherearea where there there is no is demand no demand on the on road the behindroad behind the ﬁrst the parking first parking line,or line, between or between the second the second and third and parkingthird parking line. A line. fourth A parkfourth line park is visible line is only visible for theonly reason for the of showingreason of the showing blocking the by longitudinalblocking by longitudinal parking (Figure 4). The first parking line is proposed according to the response of drivers from the transport survey, who suggested that vehicles should be arranged to keep the driver’s cab away from the highway, to lower noise and increase the rest comfort of the driver; however, turning the driver’s cab does not sufficiently eliminate noise, especially in an empty car park, so it is necessary to build a noise barrier behind the first line. Additionally, it is necessary to build a visual barrier between lines 2 and 3 so that vehicles do not bump into each other. An example of this parking management is as follows: Vehicle 1, after entering the car park, parks by reversing into a free place in the first line. Vehicle 2 drives through parking line 3 where it could not find a suitable place, but does not have to abandon the car park. It comes back onto the road between the first and second lines and parks in the second line by reversing. Vehicle number 3 fails to park in the third line, but even in the second line could not find a possible place. It is up to the driver whether they choose to turn to the petrol station and park by left-handed reversing, or park in the first line by driving forward under more demanding conditions, driving by reversing to the right side.

3.3.2. Car Parking Using Intelligent Transportation Systems The second proposal concerning the organization of the car park is aimed at using intelligent transport systems in combination with the previous proposal of reverse parking. Compact parking with variable signal (tested in Germany) shows the exit times of the parking space and thus the driver

Sustainability 2020, 12, 9430 13 of 16 parking (Figure4). The first parking line is proposed according to the response of drivers from the transport survey, who suggested that vehicles should be arranged to keep the driver’s cab away from the highway, to lower noise and increase the rest comfort of the driver; however, turning the driver’s cab does not sufficiently eliminate noise, especially in an empty car park, so it is necessary to build a noise barrier behind the first line. Additionally, it is necessary to build a visual barrier between lines 2 and 3 so that vehicles do not bump into each other. An example of this parking management is as follows: Vehicle 1, after entering the car park, parks by reversing into a free place in the first line. Vehicle 2 drives through parking line 3 where it could not find a suitable place, but does not have to abandon the car park. It comes back onto the road between the first and second lines and parks in the second line by reversing. Vehicle number 3 fails to park in the third line, but even in the second line could not find a possible place. It is up to the driver whether they choose to turn to the petrol station and park by left-handed reversing, or park in the first line by driving forward under more demanding conditions, driving by reversing to the right side.

3.3.2. Car Parking Using Intelligent Transportation Systems The second proposal concerning the organization of the car park is aimed at using intelligent Sustainability 2020, 12, x FOR PEER REVIEW 13 of 16 transport systems in combination with the previous proposal of reverse parking. Compact parking withchooses variable the parking signal (tested space inaccording Germany) to shows the planned the exit timesdeparture of the on parking the signal space [34,35]. and thus This the system driver choosesallows multiple the parking vehicles space to according be parked to in the a row planned without departure blocking on each the signal other [ 34because,35]. This the systemvehicles allows leave multiplethe parking vehicles places to gradually. be parked The in a system row without is upda blockingted every each 15 min other to because provide the quality vehicles and leave accurate the parkingparking placesmanagement. gradually. The The compact system parking is updated system every in 15 combination min to provide with quality the reverse and accurate parking parking system management.makes it possible The compactto park the parking vehicle system for an in undefined combination time. with In the case reverse of a parkingdefect appearing system makes on the it possiblevehicle, or to parkthe driver the vehicle parks foran anunloaded undeﬁned vehicle time. and In casethey of do a defectnot know appearing the exit on time, the vehicle,they can or park the driverthe vehicle parks in an the unloaded first line, vehicle where and they they park do by not reversing know the or exit longitudinally time, they can along park the the edge vehicle of the in thecar ﬁrstpark line, at reserved where they places. park Since by reversing it is not orpossible longitudinally to return along in this the type edge of of parking, the car parka parking at reserved space places.occupancy Since detection it is not system possible would to return need in to this be typeinstalled of parking, in the reverse a parking parking space line, occupancy and the detection driver is systeminformed would on the need signal to be before installed entering in the the reverse line parkingwhether line,is there and a the free driver parking is informed place in onthe the line signal and beforeso how entering many free the places line whether there are. is there Based a free on parkingthis information, place in the the line driver and can so how decide many whether free places they therechoose are. the Based ITS (intelligent on this information, transportation the driver system) can way decide or the whether reverse they parking choose way. the ITSAn (intelligentexample of transportationthis parking management system) way is or as the follows: reverse Vehicle parking 1 way. knows An examplewhen it ofplans this to parking leave managementthe car park, isand as follows:therefore Vehicle ranks straight 1 knows on when a branch it plans with to a leave compac thet car parking park, andsystem, therefore where ranks it also straight parks according on a branch to withthe selected a compact time. parking Figure system, 6 shows where that itit alsois obvious parksaccording that Vehicles to the 2 and selected 3 dotime. not know Figure when6 shows to leave that itthe is car obvious park, that so they Vehicles will decide 2 and 3 according do not know to the when sign toal leave at the the entrance car park, where so they they will will decide park according toto thethe signalnumber at of the available entrance free where places. they will park according to the number of available free places.

Figure 6. A car park using intelligent transportation system (ITS).

This carcar parkpark design,design, inin combinationcombination with the compact parking and reversing parking system, increasesincreases thethe capacitycapacity ofof thethe carcar parkpark withinwithin thethe samesame built-upbuilt-up area.area. The proposed car park with the possibilitypossibility of returnreturn increasesincreases thethe comfortcomfort ofof parkingparking andand thethe availabilityavailability ofof thethe petrolpetrol station.station. For a given sample area (the illustration doesdoes notnot feature allall 118 parking spaces for simplicity), the car park has aa capacitycapacity ofof 118118 trucktruck parkingparking places.places. A car parkpark using ITS has a capacitycapacity ofof 147147 trucktruck parkingparking placesplaces inin aa smallersmaller areaarea onon thethe samesame carcar parkpark length,length, butbut withwith narrowednarrowed widthwidth (for(for unusedunused places).places).

Sustainability 2020, 12, 9430 14 of 16

4. Discussion The issue of truck parking is relevant worldwide, not just in the EU. Vehicles park in unauthorized places due to the full capacity of the legal car parks and also because the driver is subject to a fine in case the prescribed rest is not drawn. This situation is not sustainable in the long term, especially because of the expected growth of road freight transport output. Based on our research, we found that drivers, because of the fear of not finding a suitable parking place, park vehicles earlier before the set rules, earlier than they need to recover. Alternatively, they park vehicles during the day and drive at night when they cannot find a parking place. Such a situation decreases the safety of road transport. Our research also highlights insufficient equipment for existing car parks. Some theoretical and practical implications are obvious in the study. If the equation is used for calculating parking spaces for trucks, the characteristics such as the intensity of traffic, length of driver’s rest, average driving time, length of the solved section, and the average speed of trucks are not considered. In this paper, two practical proposals for freight transport parking areas were discussed. If the parking area with ITS is used, it will be space-efficient and thus lower costs. It is necessary to build new parking areas with accommodation. We have proven that on three selected routes there are only 1.10 to 1.43 parking places with accommodation for drivers per 100 km. This study had a few limitations. The results of the questionnaire may not be accurate, and the sample size was 825 drivers. The equation for calculating parking spaces uses theoretical data. Sometimes, other facts affect the demand for parking spaces, and these are not included in the equation. Another limitation is that the proposed solution using ITS depends on a reliable and efficient information system. Based on our research, the research hypothesis that there is insufficient parking capacity for trucks was confirmed. We highlight the method of calculating the necessary car park capacity for a specified traffic intensity on the road. By applying this method to the superior road network in Slovakia, we found that there is not a sufficient number of car parks for freight transport in any section. We are aware that the establishment of new car parks is economically demanding, and as such, we offered two possibilities that increase the capacity of freight transport car parks without further demands on the car park area. The costs associated with each proposal are different. In general, the biggest are costs necessary for the construction of parking infrastructure, which are location, roads, asphalt surface, road equipment, etc. For parking areas with ITS, it is possible to save parking space. It is also important to take into account the cost of the information system itself.

5. Conclusions During our extensive survey, we have found many important information form truck drivers. The survey showed that 92% of drivers adjust the driving time and their own working time to the situation in car parks. With our research, we have proved that the analyzed car parks do not achieve the demanded capacity. Additionally, the results of the survey confirm that it is possible to increase the capacity of existing car places by effective management. Our first proposal of parking area allows the return of the vehicle. Our second proposal is using the ITS, which increases the capacity of the car park within the same built-up area. We have also created a methodology that can determine the necessary number of parking spaces that comply with the requirements of social law.

Author Contributions: Conceptualization, M.P. and A.P.; methodology, M.P. and A.P.; validation, M.P., A.P., and K.C.;ˇ formal analysis, M.P., A.P., and K.C.;ˇ investigation, M.P. and A.P.; resources, M.P., A.P., and K.C.;ˇ data curation, M.P., A.P., and K.C.;ˇ writing—original draft preparation, M.P. and A.P.; writing—review and editing, M.P., A.P., and K.C.;ˇ visualization, A.P. and K.C.;ˇ supervision, M.P.; project administration, K.C.;ˇ funding acquisition, K.C.ˇ All authors have read and agreed to the published version of the manuscript. Funding: This paper has been developed under support of the project: MŠVVŠ SR VEGA No. 1/0566/18 KONECNˇ Ý, V.: Research on the impact of supply and quality of transport services on the competitiveness and sustainability of demand for public transport. Sustainability 2020, 12, 9430 15 of 16

Conﬂicts of Interest: The authors declare no conﬂict of interest.

References

1. European Union. Eur-Lex: Access to European Union Law; Directive 2000/53/EC of the European Parliament and of the Council of 18 September 2000 on end-of Life Vehicles—Commission Statements; European Union: Brussels, Belgium, 2017. 2. Chatterjee, A.; Wegmann, F.J. Overnight truck parking along Tennessee’s Interstate highways and rest areas. Transp. Res. Rec. 2000, 1734, 64–68. [CrossRef] 3. Al-Kaisy, A.; Veneziano, D.; Kirkemo, Z.; Dorrington, C. Practical guidelines for estimation of rest area use on rural interstates and arterial highways. Transp. Res. Rec. 2012, 2303, 117–124. [CrossRef] 4. Boris, C.; Brewster, R. A comparative analysis of truck parking travel diary data. Transp. Res. Rec. 2018, 2672, 242–248. [CrossRef] 5. Kay, J.; Gates, T.J.; Savolainen, P.T.; McArthur, A.; Russo, B.J. Empirical models of demand levels and turn-in rates at roadside rest areas. Transp. Res. Rec. 2014, 2430, 200–206. [CrossRef] 6. Muramatsu, T.; Oguchi, T. Methodology to measure the parking area performance of inter-city expressways. Transp. Res. Procedia 2017, 25, 639–651. [CrossRef] 7. Jung, S.; Joo, S.; Oh, C. Evaluating the effects of supplemental rest areas on freeway crashes caused by drowsy driving. Accid. Anal. Prev. 2017, 99, 356–363. [CrossRef][PubMed] 8. Matsushita, T.; Kumagai, T.; Nonaka, Y.; Ishida, T. A basic study on rest spot choice behavior on expressway. In Research Meeting on Civil Engineering Planning; CD-ROM: Atlanta, GA, USA, 2011. 9. Seya, H.; Zhang, J.; Chikaraishi, M.; Jiang, Y. Decisions on truck parking place and time on expressways: An analysis using digital tachograph data. Transportation 2020, 47, 555–583. [CrossRef] 10. Garber, N.J.; Teng, H.; Lu, Y. A Proposed Methodology for Implementing and Evaluating a Truck Parking Information System; Research Report No. UVACTS-15-5-86; University of Virginia: Charlottesville, VA, USA, May 2004. 11. Cook, D.J.; Morris, T.; Morellas, V.; Papanikolopoulos, N. An automated system for persistent real-time truck parking detection and information dissemination. In Proceedings of the 2014 IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China, 31 May–5 June 2014; pp. 3989–3994. [CrossRef] 12. Haghani, A.; Farzinfard, S.; Hamedi, M.; Ahdi, F.; Khandani, M.K. Automated Low-Cost and Real-Time Truck Parking Information System; State Highway Administration, Office of Policy & Research: Baltimore, MD, USA, 2013. 13. Srivastava, P.; Bruce, X.W.; Adams, T.M. Geo-spatial analysis of truck parking needs. J. Transp. Syst. Eng. Inf. Technol. 2012, 12, 93–105. [CrossRef] 14. Levy, N.; Benenson, I. GIS-based method for assessing city parking patterns. J. Transp. Geogr. 2015, 46, 220–231. [CrossRef] 15. Mitteldeutscher Rundfung—Homepage. Available online: https://www.mdr.de/sachsen/politik/ueberfuellte- lkw-stellplaetze-autobahn-antrag-cdu-spd-100.html?fbclid=IwAR0J6XI-1VfpztQTgCnpPcDQZfpcS9bJB 77zgDge98LYGPFL6VjKZqYo6ec (accessed on 16 September 2020). 16. WAZ—Homepage. Available online: https://www.waz.de/politik/tausende-lkw-parkplaetze-fehlen-in-nrw- id215413615.html (accessed on 16 September 2020). 17. Bababeik, M.; Zerguini, S.; Farjad-Amin, M.; Khademi, N.; Bagheri, M. Developing a train timetable according to track maintenance plans: A stochastic optimization of buffer time schedules. Transp. Res. Procedia 2019, 37, 27–34. [CrossRef] 18. FMCSA—Homepage. Available online: https://csa.fmcsa.dot.gov/SafetyPlanner/MyFiles/SubSections.aspx?c h=23&sec=69&sub=176 (accessed on 16 September 2020). 19. Duke, J.; Guest, M.; Boggess, M. Age-related safety in professional heavy vehicle drivers: A literature review. Accid. Anal. Prev. 2010, 42, 364–371. [CrossRef][PubMed] 20. New Zealand Transport Agency—Homepage. Available online: https://www.nzta.govt.nz/commercial-driv ing/commercial-safety/work-time-and-logbook-requirements/ (accessed on 16 September 2020). 21. EUR-Lex—Homepage. Available online: https://eur-lex.europa.eu/legal-content/sk/TXT/?uri=CELEX:3200 6R0561 (accessed on 16 September 2020). 22. Ministry of Transport of Canada—Homepage. Available online: http://www.mto.gov.on.ca/english/trucks/h andbook/section1-7-4.shtml (accessed on 16 September 2020). Sustainability 2020, 12, 9430 16 of 16

23. Koneˇcný, V.; Gnap, J.; Šimková, I. Impact of fiscal decentralization on motor vehicle taxation in the Slovak republic. Transp. Telecommun. J. 2016, 17, 28–39. [CrossRef] 24. McCartt, A.T.; Hellinga, L.A.; Solomon, M.G. Work schedules of long-distance truck drivers before and after 2004 hours-of-service rule change. Traffic Inj. Prev. 2008, 9, 201–210. [CrossRef][PubMed] 25. Sobczak, P.; Stawiarska, E.; Oláh, J.; Popp, J.; Kliestik, T. Logistics management of the rail connections using graph theory: The case of a public transportation company on the example of Koleje Dolno´sl˛askieSA. Eng. Manag. Prod. Serv. 2018, 10, 7–22. [CrossRef] 26. Poliak, M.; Poliaková, A. Relation of social legislation in road transport on driver’s work quality. In Proceedings of the 2015 International Conference on Transport Systems Telematics, Wrocław, Poland, 15–17 April 2015; Springer: Cham, Switzerland, 2015; pp. 300–310. [CrossRef] 27. Poliak, M.; Šimurková, P.; Ja´skiewicz,M.; Posuniak, P.; Stokłosa, J. The impact of the ban on spending weekly rest in the vehicle on transport planning in the EU. New Trends Prod. Eng. 2018, 1, 27–33. [CrossRef] 28. Ayala, D.; Wolfson, O.; Xu, B.; DasGupta, B.; Lin, J. Pricing of parking for congestion reduction. In Proceedings of the 20th International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA, 6–9 November 2012; pp. 43–51. [CrossRef] 29. Kenworthy, J.; Newman, P. Sustainability and Cities: Overcoming Automobile Dependence; Island Press: Washington, DC, USA, 2013. 30. Rotondo, E. The legal effect of EU regulations. Comput. Law Secur. Rev. 2013, 29, 437–445. [CrossRef] 31. Domonkos, T.; Ostrihoˇn,F.; Šikulová, I.; Širaˇnová, M. Analysing the Relevance and Predictive Power of the MIP Scoreboard’s Indicators; Firstrun Working Paper; Slovak Economic Library of the UE in Bratislava: Bratislava, Slovakia, 2017. 32. Drozdziel, P.; Piasecki, S. Study of the method of assessing the economic efficiency of exploitation cars in a transport company. Folia Soc. Sci. Lub. 1995, 60–66. 33. Gašparík, J.; Abramović,B.; Zitrický, V.Research on dependences of railway infrastructure capacity. Teh. Vjesn. 2018, 25, 1190–1195. [CrossRef] 34. Davis, G.A. Accident reduction factors and causal inference in traffic safety studies: A review. Accid. Anal. Prev. 2000, 32, 95–109. [CrossRef] 35. Kalašová, A.; Mikulski, J.; Kubíková, S. The impact of intelligent transport systems on an accident rate of the chosen part of road communication network in the Slovak Republic. In Proceedings of the International Conference on Transport Systems Telematics, Katowice-Ustroń,Poland, 16–19 March 2016; pp. 47–58. [CrossRef]

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional aﬃliations.

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).