Disaggregate Modelling for Estimating Location Choice of Safe and Secure Truck Parking Areas: A Case Study

Abstract

Responding to the increasing need for safety and security in road freight transport, and to targeted legislation specifying the availability of freight drivers’ rest areas, this paper proposes a plan and a model for deployment of safe and secure parking areas for truck drivers. Disaggregate analysis within a stated preference and conjoint analysis framework leads to the modelling of truck parking area selection by each truck driver that registers in the system proposed in this research. The concept builds upon the Cooperative Intelligent Transport Systems (C-ITS) upgrading of the Trans-European Transport Network (TEN-T) infrastructure systems while adapting to novel transport and logistics needs in an operationally safe, secure, and efficient environment for the supply chain. The analysis is applied in the Orient/East-Med Corridor of the TEN-T and is supported by the clustering of available truck parking areas for each truck route in the application subnetwork. The personalised approach is scalable and can be integrated into platforms for safe and secure truck parking areas, thus facilitating their acceptance and increasing awareness by the end-users. From pilot implementation on the Hellenic motorways, functional evaluation of use cases indicates 94.4% estimated choice probability of the most suitable parking area by the pilot drivers.

1. Introduction

Cargo theft in Europe, the Middle East, and Africa has tripled in the past ten years, based on data reported by the Transport Asset Protection Association (TAPA) [1]. High-value products are attractive targets for theft while in transit, requiring extra security to overcome the increased risk [2,3]. Global supply chain security has become increasingly important because of theft incidents, with emphasis on parking lots where the cargo does not move [2,4,5,6,7,8]. The problem of high criminality has been also highlighted in cargo ports [9] which have similar characteristics to truck parking areas. According to a European Parliament’s publication, the road freight transport annual losses owing to theft amount to EUR 8.2 billion per year: around 40% of thefts occur while driving, 40% in parking lots, and 20% in roadside parking stops [10]. Most freight vehicle operators park over 24 h in undesignated spaces and their activities affect the safety, health, and environmental conditions [11].

Recent research revealed the need for secure parking areas in strategic locations to address the need for transport security [12,13], while there is a growing need for supply chain risk prediction [14]—more specifically, cargo theft risk analysis [15]. Apart from the increased criminality in freight transport, in particular in parking areas where the driver and the heavy goods vehicle remain stationary, the issue of lack of truck parking areas has been highlighted [16,17,18,19]. The ever-increasing shortage of truck parking results in illegal parking or fatigued driving with hazardous consequences for traffic safety [17].

To avoid traffic accidents that are due to driver fatigue in long-haul trucking, worldwide laws and provisions regulate breaks and rest periods of truck drivers [18]. An expanding legislative framework underlines the need for safe and secure parking areas for trucks, and information provision for their availability and the rules for staying safe. Relevant European legislation directives and regulations include the following: Directive 2008/96/ΕC on road infrastructure safety management stating that sufficient safe parking areas should become an integral part of road infrastructure safety management [20]; Directive 2010/40/EU on the framework for deployment of Intelligent Transport Systems (ITS) in road transport, setting as priority the provision of information services and of reservation services for safe and secure parking places for trucks and commercial vehicles [21]; Regulation (EU) No. 165/2014 on tachographs in road transport, repealing Council Regulation (EEC) No. 3821/85 on recording equipment in road transport and amending Reg. (EC) No. 561/2006 of the European Parliament and of the Council on harmonisation of social legislation relating to road transport [22]; and Commission Delegated Regulation (EU) No. 885/2013 on the provision of information services for safe and secure parking places for trucks and commercial vehicles [23]. The last one is supplementary to ITS Dir. 2010/40/EU and highlights the importance of safe and secure truck parking areas in combating and preventing road freight crime. Commission Delegated Reg. (EC) No. 885/2013 clarifies the data collection for safe and secure truck parking areas and defines the exact naming of the related data and the type of information, according to Datex II [23].

Directive (EU) 2020/1057 of the European Parliament and of the Council introduces specific rules on Directive 96/71/EC and Directive 2014/67/EU for posting drivers in the road transport sector, amending Directive 2006/22/EC on enforcement requirements and Regulation (EU) No 1024/2012; it defines the new rules for truck drivers within the scope of ending distortion of competition in the sector while providing better working conditions for drivers. The new regulation package is comprised of three key elements, i.e., better enforcement of cabotage rules, posting of drivers, and drivers’ rest times. It also defines that breaks of at least 45 min (separable into 15 min followed by 30 min) should be taken after 4 ½ hours at the latest [24].

Considering the diversity of businesses and goods carried, and the need of transport operators and drivers for parking areas at varying levels of security, depending on the goods they carry, the Union standardized these levels [25] by Commission Delegated Regulation (EU) 2022/1012 of 7 April 2022 supplementing Regulation (EC) 561/2006 of the European Parliament and of the Council on the establishment of standards detailing the level of service and security of safe and secure parking areas (SSTPAs) and the procedures for their certification. The standardization procedure lasted for 3 years and was based on a study on safe and secure parking places for trucks [26].

The European Commission adopted four security levels for parking facilities: bronze, silver, gold, and platinum [26]. According to the proposed certification procedure, security is assessed through the establishment of security features and measures at the perimeter, the parking area, the entry/exit, and through staff and management procedures. The security levels build on one another, so that, for example, the silver standard includes all the requirements for bronze, and so on [25]. Further to the security requirements, a basic service level must always be reached (e.g., there are toilets, showers, and washing facilities that are clean and checked regularly, there are water taps, waste bins, and clear signs for safe traffic movement, emergency contacts are displayed, snacks and drinks are available for purchase, there is Internet connection and electricity, it operates 24/7) [25].

Having set the framework for the safe and secure truck parking areas (SSTPAs), the importance of information provision to truck drivers on the location and availability of parking is being investigated. The European Commission laid the groundwork for offering consolidated information for safe and secure parking places for trucks and commercial vehicles [23] supporting drivers who might otherwise have to choose between parking illegally and risking noncompliance [27]. The use of a common data structure (e.g., DATEX II) supports the development of a complex information provision system, especially in cross-border operation [6]. In particular, DATEX II common profiles for truck parking systems can consider a range of user needs, focusing on what is strictly required or what provides useful information about truck parking places [28].

Advanced intelligent truck parking management systems that can provide real-time information and navigation with automatic parking reservation offer the preferred solution to exploiting the truck parking facilities [6]. Mapping technologies provide users with information on alternative routes and stops [5,6]. Revealed information on factors influencing truck parking choice determined that the experience of parking space use is a key choice parameter, so information from drivers who have stayed in a space will also help the decision of future drivers [29]; user feedback through specific evaluation tools could lead to more applications [30]. Regarding the user acceptance and taking advantage of the information provision, computational experiments have been made to compare the cost of solutions that use parking availability information with ones that do not, suggesting that illegal parking cost may exceed cost increases caused by parking constraints [31].

Responding to the increasing need for higher safety and security in road freight transport, and to targeted legislation requiring freight drivers’ rest areas, this paper proposes a plan for deployment of safe and secure truck parking areas (SSTPAs) using disaggregate information from truck drivers. For facilitating parking choice, beyond information provision through databases, this research considers the key factors that influence truck drivers’ choice. The research also suggests a way for a truck driver to select a suitable parking area based on his/her characteristics.

It is worth noting that highway parking is a key Cooperative Intelligent Transport Systems (C-ITS) service that includes four main use cases, i.e., information on parking location, availability, and services via Internet; information on parking location, availability, and services via infrastructure-to-vehicle (I2V) communications; information about a truck parking space released by a user; and reservation of a truck parking space released by a user. This service is included in the Day 1.5 C-ITS Services on parking information [32]. It is also considered that the engagement of the end-users will facilitate acceptance of the suggested solutions. Notably, in a representative qualitative study of users’ acceptance of connected vehicle technology, after nine months of experience with the technology, the participants expressed their desire for increased personalisation of system settings [33].

2. Method and Approach

This paper develops a methodology that integrates the parking data from truck parking areas operators and truck drivers and supports provision of the related Day 1.5 C-ITS Services to logistics users. Initially, data are collected on the registration of the parking managers/owners and the truck drivers through two different user forms that were developed in this work. More specifically, the users insert the information on their parking areas into the user form developed in Excel with Visual Basic. This research also proposes a model to estimate the utility of a truck parking area based on truck driver individual information. The new system is based on information from the parking managers/owners and the truck drivers, and is expandable with additional parameters.

2.1. Truck Parking Area Choice Model with Conjoint Analysis

Drawing on conclusions from earlier research [34], the most significant parking choice factors were considered for the new model for estimating truck parking choice, indicatively distance, cost, time, type of transported cargo, security, and comfort of the parking area. Prior to selection of main factors to be used for the analysis, a questionnaire was distributed to truck drivers to identify the most important parking features on a 5-point scale. Based on the participation of 24 truck drivers from Greece, the 4 most important characteristics (distance from the truck parking area, cost of the parking lot, information provision for the truck parking area, and security level of the truck parking area) were identified. Indicatively, 50% of truck drivers answered that distance is very important for selecting a parking area, and 33% stated that this parameter is important. In total, 20% of the truck drivers are implementing international routes for 1 to 5 years, 40% of them for 6 to 10 years, 32% of them for 11 to 20 years, and 8% of them for more than 20 years.

Conjoint analysis is widely used in transportation research [35,36,37,38]. The theory of conjoint analysis was introduced in 1964 and laid the foundation for the applied use of the method [39]. Later, four types of analysis were suggested, i.e., Conjoint Analysis—CA, Choice-Based Conjoint Analysis—CBCA, Ranking or Rating-Based Conjoint Analysis—RBCA, and Adaptive Conjoint Analysis—ACA [40]. Although CBC has conceptual advantages, a weakness is that analysing choices generates limited information, i.e., on which alternative was chosen, and the differences in the attractiveness of the alternatives remain unclear. In this respect, ranking or rating-based conjoint methods provide more information, because the respondents evaluate each alternative explicitly [41]. To our knowledge, conjoint analysis is being applied for the first time to the SSTPA selection problem through this research.

A rating-based Conjoint Analysis [42] was performed to gain insights on the preferred levels and attributes of truck parking areas. Each respondent evaluated potential profiles, each including levels of parking attributes linked together conjointly [37]. Based on the experience gained, the new conjoint model included 4 attributes and their levels, depending on the specific characteristics of the attribute (

Table 1. Rating-Based Conjoint model.

Levels		Attributes
No.	Distance (km)	Cost for Overnight Parking (€)	Information Provision	Security Level
1	D ≤50 km	C ≤ 20 €	Below standards	Non-certified
2	50 km < D ≤ 100 km	20 €< C ≤ 30 €	Meets standards	Bronze
3	100 km < D ≤ 200 km	30 € < C	Above standards	Silver
4	200 km < D ≤ 300 km			Gold
5	300 km < D			Platinum

). In total, 2 attributes consisted of 3 levels, and 2 consisted of 5 levels. In an effort not to exclude the existing parking areas in Greece, as no parking area has been certified as SSTPA yet, the survey included the “non-certified” truck parking areas level in the security attribute. The security levels for a certified SSTPA are based on the following rating system: bronze, silver, gold, and platinum [25].

From a full factorial design of 225 profiles on all attribute levels, the orthogonal main effects of fractional factorial design with desirable properties were implemented [42] on SPSS Statistics Data Editor; 25 profiles were displayed (

Table 2. Orthogonal main effects.

Profile	Attribute Combinations
No.	Distance (km)	Cost for Overnight Parking (€)	Information Provision	Security Level
1	300 km < D	C ≤ 20 €	Below standards	Silver
2 a	50 km < D ≤ 100 km	20 € < C ≤ 30 €	Above standards	Non-certified
3	D ≤ 50 km	30 € < C	Below standards	Platinum
4	D ≤ 50 km	20 € < C ≤ 30 €	Meets standards	Gold
5	100 km < D ≤ 200 km	20 € < C ≤ 30 €	Above standards	Non-certified
6	50 km < D ≤ 100 km	C ≤ 20 €	Meets standards	Platinum
7	300 km < D	20 € < C ≤ 30 €	Above standards	Platinum
8 a	D ≤ 50 km	20 € < C ≤ 30 €	Meets standards	Platinum
9	300 km < D	C ≤ 20 €	Meets standards	Bronze
10	50 km < D ≤ 100 km	20 € < C ≤ 30 €	Below standards	Bronze
11	100 km < D ≤ 200 km	30 € < C	Meets standards	Silver
12	200 km < D ≤ 300 km	20 € < C ≤ 30 €	Meets standards	Platinum
13	D ≤ 50 km	C ≤ 20 €	Above standards	Bronze
14 a	50 km < D ≤ 100 km	C ≤ 20 €	Below standards	Non-certified
15	50 km < D ≤ 100 km	30 € < C	Above standards	Gold
16	200 km < D ≤300 km	C ≤20 €	Above standards	Silver
17	300 km < D	30 € < C	Meets standards	Non-certified
18	50 km < D ≤ 100 km	C ≤ 20 €	Meets standards	Non-certified
19	D ≤ 50 km	20 €< C ≤ 30 €	Meets standards	Silver
20	200 km < D ≤ 300 km	C ≤ 20 €	Meets standards	Gold
21 a	100 km < D ≤ 200 km	30 € < C	Below standards	Gold
22	200 km < D ≤ 300 km	20 €< C ≤ 30 €	Below standards	Non-certified
23	100 km < D ≤ 200 km	C ≤ 20 €	Below standards	Gold
24	300 km < D	20 €< C ≤ 30 €	Below standards	Gold
25	100 km < D ≤ 200 km	C ≤ 20 €	Below standards	Platinum
26	D ≤ 50 km	C ≤ 20 €	Below standards	Non-certified
27	50 km < D ≤ 100 km	20 €< C ≤ 30 €	Below standards	Silver
28 a	200 km < D ≤ 300 km	30 € < C	Above standards	Bronze
29	100 km < D ≤ 200 km	20 €< C ≤ 30 €	Meets standards	Bronze
30	200 km < D ≤ 300 km	30 € < C	Below standards	Bronze

^a Holdout.

), and 5 more profiles were used for evaluation of results. These additional profiles were randomly placed in the orthogonal plan, as shown in Table 2. Initially, the respondents were called to carefully read the table with the specific characteristics of each security level [25], and then were called to rate each of the 30 profiles on an 11-point Likert scale (0: definitely not acceptable, 10: definitely acceptable). The profiles were described in detail and a user-friendly format facilitated the collection of reliable answers from 40 truck drivers. Apart from profiles rating, a set of general questions were asked for completeness.

Indicatively, for 39 out of 40 drivers (97.5%), the most important parameter for choosing a parking space is the distance between the parking area and their vehicle. On the question, “do you know about safe and protected parking spaces?”, 87% of the drivers who took part in the survey already knew about safe and protected parking spaces. After rating the profiles, the answers were input in IBM SPSS Statistics Data Editor for Conjoint Analysis. The value of the attribute follows its level, e.g., for D ≤ 50 km, the attribute value is 1, for 50 km < D ≤100 km, the attribute value is 2, for “Below standards” information provision, the attribute value is 1, and so on.

The partworth utility for each attribute is the product of the weight of the attribute and the attribute-level desirability rating given by the respondents [42] in the results of the analysis, i.e., the values of the partworth utilities for each level of each attribute are included in

Table 3. Partworth utilities for each level of each attribute.

Attribute	Level	Weight	Utility Estimate	Rating	S.E.	Rating/SE
Distance	D ≤ 50 km	0.63778	−1.158	−1.81567	0.185	−9.81
	50 km < D ≤ 100 km	0.63778	−2.316	−3.63135	0.370	−9.81
	100 km < D ≤ 200 km	0.63778	−3.474	−5.44702	0.556	−9.80
	200 km < D ≤ 300 km	0.63778	−4.632	−7.26269	0.741	−9.80
	300 km < D	0.63778	−5.790	−9.07837	0.926	−9.80
Cost	C ≤ 20 €	0.16092	−0.585	−3.63535	0.350	−10.4
	20 € < C ≤ 30 €	0.16092	−1.171	−7.27691	0.700	−10.4
	30 € < C	0.16092	−1.756	−10.9123	1.050	−10.4
Information	Below standards	0.03553	0.011	0.309598	0.350	0.88
	Meets standards	0.03553	0.022	0.619195	0.700	0.88
	Above standards	0.03553	0.033	0.928793	1.050	0.88
Security	Non-certified	0.16578	0.306	1.84582	0.185	9.98
	Bronze Level	0.16578	0.611	3.68561	0.370	9.96
	Silver Level	0.16578	0.917	5.53143	0.556	9.95
	Gold Level	0.16578	1.222	7.37122	0.741	9.95
	Platinum Level	0.16578	1.528	9.21704	0.926	9.95
Constant			8.607		1.217

. Indicatively, for the distance attribute, negative partworth values are observed; the longer the distance, the less probable for the truck parking area to be selected by a driver.

The analysis also revealed the relative weight (%) of the attributes, which was 63.778 for the distance, 16.092 for the cost, 3.553 for the information, and 16.578 for the security attribute. Therefore, the information provision attribute is the lowest-weight parameter when compared to the other 3 attributes. The correlation coefficient between revealed preferences and estimated preferences was calculated with Pearson’s R (0.831 with p value < 0.001) and Kendall’s Tau (0.631 with p value < 0.001).

Conjoint Analysis results could be used for the simulation of new cases/profiles. Further, utilities can be summed to estimate the summed utility of any combination of attributes. For example, the total utility of a parking area that is 50 km < D ≤ 100 km away from the driver, has a cost C ≤ 20 €, provides information that meets the standards, and is of gold security level is Equation (1):

Partworth utility (50 km < D ≤ 100 km) + Parworth utility (C ≤ 20 €) +
Parworth utility (Meets standards) + Partworth utility (Gold Level) + Constant = −2.316 − 0.585 + 0.022 + 1.222 + 8.607 = 7.150

(1)

2.2. Data Collection with User Forms

The scope of this research is to suggest to heavy goods vehicles drivers a suitable truck parking area during their route. To achieve this, data are collected on the registration of the parking managers/owners and the truck drivers through two different user forms that were developed in this work in Excel with Visual Basic. Regarding the driver user form, an extensive study of the section of the Eastern/Eastern Mediterranean transport corridor of the Trans-European Transport Network [TEN-T] that passes through Greece has been made to define the routes in Hellenic motorways that can be implemented by the drivers.

2.2.1. Field of Study: Analysis, Routes Definition and Truck Parking

Greece is located at the southeastern end of the continental Orient/East-Mediterranean Corridor of TEN-T. With completion of major motorway projects (Olympia Odos, Ionia Odos), the Greek road section has been fully compatible with the motorway status since 2017. This study specifically concerns the section of the Eastern/Eastern Mediterranean transport corridor of TEN-T that passes through Greece. The selection of the study field was made in accordance with Directive 2010/40/EU of the European Parliament and of the Council, which defines that there should be a safe and secure truck parking area (SSTPA) at every 100 km of TEN-T [21]. First, the main road axes of Greece were recorded in detail, past the corresponding TEN-T corridor [43], leading to inclusion of all the motorways of the corridor, i.e., A1: Athens—Thessaloniki—Evzonoi (A.TH.E), A2: Egnatia Odos, A4: Trikkala—Larissa (only 4 km of this motorway were delivered), A5: Ionia Odos, A6: Attiki Odos, A8: Olympia Odos, and A25: Thessaloniki—Serres—Promachonas [44].

After defining the motorways of interest, all Motorist Service Stations (MSS) and Safe and Secure Truck Parking Areas (SSTPAs) to be delivered within 2023 were listed (see

Table 4. Motorist Service Stations and SSTPAs in Greek sections of Orient/East-Med Corridor.

Motorway Code	Motorists Service Stations (MSSs) and SSTPAs
A1	1. Aerino (2 SSTPAs), 2. MMS Korinos (2 MMSs), 3. Nikaia (2 MSSs), 4. Skotinas (2 MSSs), 5. Evangelismos (2 MSSs), 6. Almyros (2 MSSs), 7. Atalanti (2 SSTPAs), 8. Schimatari (2 MSSs), 9. Malakasa (2 MSSs), 10. Kapandriti (1 MSS), 11. MSS Varimpombi (1 MSS)
A2	1. Platanos (2 MSSs), 2. Analipsi (2 SSTPAs)
A5	1. Episkopiko (2 SSTPAs), 2. Ambrakia (1 MSS), 3. Filippiada (2 MSSs), 4. Evinochori (2 MSSs), 5. Amfilochia (1 MSS).
A6	1. Aspropyrgos (2 MSSs), 2. Mesogeion (2 MSSs)
A8	1. Psathopyrgos (2 MSSs), 2. Aigio (2 MSSs), 3. Akrata (1 MSS & 1 SSTPA) 4. Velo (2 MSSs), 5. Zevgolatio (1 MSS), 6. Megara (2 MSSs)

). Regarding the recognized undersupply of parking areas in Greece, the main needs for secure HGVs parking lots were observed in locations where the greatest demand is located, i.e., in Athens and Katerini, and then Serres (which borders Bulgaria), Kythira and the islands of Poros, Methana, Aegina, and Salamis, while some uncertified but sufficient parking lots exist in Athens, Ioannina, Katerini, and north of Chalkis [45].

Although no certified SSTPA is currently placed on Hellenic motorways, the research considered also the 9 SSTPAs that will be certified in 2023 with Connecting Europe Facility (CEF)—Transport Sector [46]. The action includes the development of nine SSTPAs for truck drivers, certified at ‘Silver’ level, for a total of 182 truck parking places. The nine SSTPAs will be new construction or combined extension and upgrade of existing service stations, and should be located in five different sites on the Core network along the Orient /East-Med Core Network corridor: in Aerino, located at km 306 + 000 of the A.TH.E motorway, two ‘Silver’ level SSTPAs will be constructed (one in each direction) with a capacity of 36 parking places per SSTPA; in Akrata, located at km 152 + 500 of the Olympia Odos motorway (direction to Patras), an existing non-secure truck parking area will be extended and upgraded with a capacity of 45 truck parking places; in Atalanti, located at km 144 + 150 of the A.TH.E motorway, two ‘Silver’ SSTPAs will be constructed (one in each direction) with a capacity of 12 truck parking places per SSTPA; in Episkopiko, at km 194 + 900 of Ionia Odos motorway, two ‘Silver’ SSTPAs will be constructed (one in each direction) with a capacity of 12 (North direction) and 9 (South direction) parking places (i.e., 21 in total); in Analipsi, at km 349 + 700 of Egnatia Odos motorway, two existing non-secure truck parking areas should be extended and upgraded with a capacity of 10 parking places per SSTPA.

The supply data were collected for the existing service stations on the Greek Motorway Network, and the SSTPAs to be certified within 2023. These data were mapped and represent the existing parking areas for HGVs in Greece.

The motorist service stations and the SSTPAs in the Greek sections of Orient/East-Med Corridor of TEN-T are summarized in Table 4. The details of the motorist service stations and the SSTPAs in the Greek sections of Orient/East-Med Corridor of TEN-T are shown in

Table A1. Motorist Service Stations and SSTPAs in Greek sections of Orient/East-Med Corridor.

Motorway Code	Motorists Service Station (MSS) & SSTPA Name, Position and Direction
A1	1. Aerino 1 (SSTPA 1)—306 + 000 km A1 (P1) (To Athens), 2. Aerino 2 (SSTPA 2)—306 + 000 km A1 (P2) (To Thessaloniki), 3. MSS Korinos 1—447 km A1 (P3) (To Athens), 4. MSS Korinos 2—447 km A1 (P4) (To Thessaloniki), 5. MSS Nikaia 1—345 km A1 (P5) (To Athens), 6. MSS Nikaia 2—345 km A1 (P6) (To Thessaloniki), 7. MSS Skotinas—410 km A1 (P7) (To Athens), 8. MSS Skotinas—410 km A1 (P8) (To Thessaloniki), 9. MSS Evangelismos 1—373.6 km A1 (P9) (To Athens), 10. MSS Evangelismos 2—373.6 km A1 (P10) (To Athens), 11. MSS Almyros 1—373.6 km A1 (P11) (To Athens), 12. MSS Almyros 2—373.6 km A1 (P12) (To Thessaloniki), 13. MSS Almyros 2—373.6 km A1 (P12) (To Thessaloniki), 13. Atalanti 1 (SSTPA 3)—144 + 200 (kilometric position) A1 (P13) (To Athens), 14. Atalanti 2 (SSTPA 4)—144 + 200 (kilometric position) A1 (P14) (To Thessaloniki), 15. MSS Schimatari 1 (Tanagra)—70 + 700 (kilometric position) A1 (P15) (To Athens), 16. MSS Schimatari 2 (Tanagra)—70 + 700 (kilometric position) A1 (P16) (To Thessaloniki), 17. MSS Malakasa (Seirios) 1—47 + 875 (kilometric position) A1 (P17) (To Athens), 18. MSS Malakasa (Seirios) 2—47 + 875 (kilometric position) A1 (P18) (To Thessaloniki), 19. MSS Kapandriti (in one direction to Lamia)—36 + 455 (kilometric position) A1 (P19) (To Thessaloniki), 20. MSS Varimpombi (Agiou Stefanou) (in one direction to Athens)—24 + 535 (kilometric position) A1 (P20) (To Athens).
A2	1. MSS Platanos 1—283.5 km A2 (P21) (To Ioannina), 2. MSS Platanos 2- 283.5 km A2 (P22) (To Thessaloniki), 3. Analipsi 1 (SSTPA 5)—283.5 km A2 (P23) (To Alexandroupoli), 4. Analipsi 2 (SSTPA 6)—283.5 km A2 (P24) (To Thessaloniki).
A5	1. Episkopiko 1 (SSTPA 7)—194 + 870 (kilometric position) A5 (P25) (To Patras), 2. Episkopiko 2 (SSTPA 8)—194 + 870 (kilometric position) A5 (P26) (To Ioannina), 3. MSS Ambrakia (in one direction to Ioannina)—154 + 130 (kilometric position) A5 (P27) (To Ioannina), 4. MSS Filippiada 1—86 + 215 (kilometric position) A5 (P28) (To Patras), 5. MSS Filippiada 2—86 + 215 (kilometric position) A5 (P29) (To Ioannina), 6. MSS Evinochori 1—27 + 182 (kilometric position) A5 (P30) (To Patras), 7. MSS Evinochori 2—27 + 182 (kilometric position) A5 (P31) (To Ioannina), 8. MSS Amfilochia—100 + 560 (kilometric position) A5 (P32) (To Patras).
A6	1. MSS Aspropyrgos 1—10.2 km A6 (P33) (To Athens International Airport), 2. MSS Aspropyrgos 2—10.2 km A6 (P34) (To Elefsina), 3. MSS Mesogeion 1—40.2 km A6 (P35) (To Athens International Airport), 4. MSS Mesogeion 2—40.2 km A6 (P36) (To Elefsina).
A8	1. MSS Psathopyrgos 1—198 km A8 (P37) (To Athens), 2. MSS Psathopyrgos 2—198 km A8 (P38) (To Patras), 3. MSS Aigio 1—175 km A8 (P39) (To Athens), 4. MSS Aigio 2—175 km A8 (P40) (To Patras), 5. MSS Akrata 1—152.5 km A8 (P41) (To Athens), 5. Akrata 2—(SSTPA 9) 152.5 km A8 (P42) (To Patras), 6. MSS Velo 1—101.9 km A8 (P43) (To Athens),7. MSS Velo 2—101.9 km A8 (P44) (To Patras), 8. MSS Zevgolatio (in one direction to Athens)—92.6 km A8 (P45) (To Athens), 9. MSS Megara 1—40.5 km A8 (P46) (To Athens), 10. MSS Megara 2—40.5 km A8 (P47) (To Patras).

. Included for each is the name, the motorway position, the direction in the motorway, and a code. Code letter “P” refers to “parking”, thus giving a unified sort-numbering to be used for the description of truck parking selection by truck drivers. Code “SSTPA” was used additionally to define the truck parking areas which will soon be certified. In total, 47 truck parking areas were listed in the Greek sections of Orient/East-Med Corridor of TEN-T. The coordinates of all MMSs and SSTPAs record the specific position of these areas and will be used to calculate the distance between a truck driver and the available truck parking areas.

Table 5. Potential routes in the Greek sections of Orient/East-Med Corridor.

North (N)–South (S) Routes (N–S)
Route ID	Origin Motorway Code; Origin Motorway Name; Direction; Destination	Via Motorway; Direction	Parking to be Considered
N-S1	A2; Egnatia Odos; To Thessaloniki; Thessaloniki	-	A2 (To Thessaloniki)
N-S2	A2; Egnatia Odos; To Ioannina; Ioannina	-	A2 (To Ioannina)
N-S3	A2; Egnatia Odos; To Thessaloniki; Athens	A1; To Athens	A2 (To Thessaloniki) + A1 (To Athens)
N-S4	A1; A.TH.E; To Athens; Athens		A1 (To Athens)
N-S5	A1; A.TH.E; To Athens; Athens International Airport	A6; To Athens International Airport	A1 (To Athens) + A6 (To International Airport)
N-S6	A2; Egnatia Odos; To Ioannina; Patra	A5; To Patras	A2 (To Ioannina) + A5 (To Patras)
N-S7	A5; Ionia Odos; To Patras; Patra		A5 (To Patras)
N-S8	A5; Ionia Odos; To Patras; Athens	A8; To Athens	A5 (To Patras) + A8 (To Athens)
N-S9	A6; Attiki Odos; To Athens International Airport; Athens International Airport	-	A6 (To Athens International Airport)
N-S10	A8; Olympia Odos; To Athens; Athens	-	A8 (To Athens)
N-S11	A8; Olympia Odos; To Athens; Athens International Airport	A6; To Athens International Airport	A8 (To Athens) + A6 (To Athens International Airport)
South (S)–North (N) Routes (S–N)
Route ID	Origin Motorway Code; Origin Motorway Name; Direction; Destination	Via Motorway; Direction	Parking to be considered
S-N1	A2; Egnatia Odos; To Alexandroupoli; Alexandroupoli	-	A2 (To Alexandroupoli)
S-N2	A1; A.TH.E; To Thessaloniki; Thessaloniki	-	A1 (To Thessaloniki)
S-N3	A1; A.TH.E; To Thessaloniki; Alexandroupoli	A2; To Alexandroupoli	A1 (To Thessaloniki) + A2 (To Alexandroupoli)
S-N4	A1; A.TH.E; To Thessaloniki; Ioannina	A2; To Ioannina	A1 (To Thessaloniki) + A2 (To Ioannina)
S-N5	A8; Olympia Odos; To Patras; Patra	-	A8 (To Patras)
S-N6	A8; Olympia Odos; To Patras; Ioannina	A5; To Ioannina	A8 (To Patras) + A5 (To Ioannina)
S-N7	A5; Ionia Odos; To Ioannina; Ioannina	-	A5 (To Ioannina)
S-N8	A5; Ionia Odos; To Ioannina; Thessaloniki	A2; To Thessaloniki	A5 (To Patras) + A2 (To Thessaloniki)
S-N9	A6; Attiki Odos; Το Elefsina; Thessaloniki	A1; To Thessaloniki	A6 (To Elefsina) + A1 (To Thessaloniki)
S-N10	A6; Attiki Odos; Το Elefsina; Patra	A8; To Patras	A6 (To Elefsina) + A8 (To Patras)
S-N11	A6; Attiki Odos; Το Elefsina; Elefsina	- -	A6 (To Elefsina)

summarizes the routes of a truck moving on a Greek road, in the section of Eastern Corridor/Eastern Mediterranean Corridor from North to South (N–S) and South to North (S–N). This research considered all routes that can be selected by a truck driver. Since the scope is to find a suitable truck parking area for a truck driver in his route and considering that longer distances are not preferable according to the conjoint analysis results, this research includes the routes that cross one or at most two different motorways. Table 5 includes the origin of the route, the name of the origin motorway, the direction on the origin motorway, the destination, the intermediate motorway required to reach the destination, the direction on the intermediate motorway, and the parking areas to be considered per route.

2.2.2. Driver User Form

For the truck drivers, information on their position would act to avoid diverting them from their route and could reduce solution processing time by focusing on a subset of the 47 parking areas, i.e., on the ones located in the driver’s route and meeting driver’s needs. In the drivers’ user form, eight labels, three text boxes, and five combo boxes are connected to each other. The form includes two command buttons (Submit, Cancel) and consists of a 4-level drop-down list based on the pre-defined routes (Table 5). The driver responds to the following questions: “Are you travelling to North or South?”; “Ιn which highway are you now?”; “Choose your direction in the highway:”; and “Choose your final destination; but the driver can only see the available options based on his previous statement. Indicatively, if the driver states that he is moving from North to South on Egnatia Odos, only the directions “To Thessaloniki” and “To Ioannina” will be available in the third level. Additionally, the driver declares his full name, the country, and his coordinates. The user form is initiated with the “Drivers” button (see Figure 1).

2.2.3. Truck Parking User Form

For the truck parking areas, information collected on driver’s position and the characteristics of the truck parking areas supports the suggestion for a truck parking area from the current and potential future SSTPAs. In the user form, eight labels, three text boxes, and five combo boxes are connected to the corresponding cells in which the lists of possible answers are included. The parking areas user form includes two command buttons (Submit, Cancel). In addition, the form initially includes two basic items, the country and name in which the parking area is located. The parking area administrator is then asked for the highway on which the parking area is located, its direction, and the coordinates of the parking area. The form also includes the attributes described in the conjoint analysis (cost, information provision, and security level) which correspond to the characteristics of the parking area; the levels of attributes are the same as those discussed in conjoint analysis. The user form is initiated with a command button.

2.3. Driving Distance

For calculating the driving distance between two addresses, an Excel function was used using the Bing Maps directions API. The format of the function was: = Driving Distance (origin, destination, API key). The origin and destination were introduced as coordinates (e.g., 39.54920746, 22.49688553).

2.4. Major Use Case Provided

The driver searches for a parking space from the set of parking spaces available on the Greek sections of Orient/East-Med Corridor of TEN-T. To initiate the procedure, the parking managers (secondary actors) have completed the registration of the spaces in the system; the driver who is looking for a parking space (primary actor) registers through the user form of truck drivers. The alternative parking search scenarios are derived from the alternative routes defined in the possible route records (Table 5). Therefore, through the user form, the driver indicates his route among the 22 routes defined.

The main use case of the system is shown in Figure 2. It is launched when the driver presses “submit” on the registration form (user form), and no provision has been made for users who only partially respond to the route data requested. The driver has an equal chance of choosing any of the 22 routes (4.55%). The system stores the input data. Static data are based on a geographic reference state. The system uses geographic coordinates, a 2-dimensional system (latitude and longitude). Each user, driver, or parking area manager inserts the geographic coordinates. The stored location data are used by the system to calculate the distance between the available parking areas and the registered truck driver. Then, the characteristics of the parking space (security, cost, service provision) allow calculating the most suitable parking space. Finally, the system maintains the historical data.

2.5. Pilot Tests for 9 Drivers

The characteristics of the drivers and their itineraries for pilot testing are given in

Table 6. Pilot test data for 9 truck drivers.

North (N)–South (S) Routes (N–S)
Driver	Country; Category; Highway	Direction	Destination	Coordinates
Driver 1	Greece; North to South; Olympia Odos	To Athens	Athens International Airport	38.3233631, 21.8790617
Driver 2	Greece; South to North; Olympia Odos	To Patras	Ioannina	38.0394954, 22.70842715
Driver 3	Greece; South to North; Attiki Odos	To Elefsina	Patras	37.9400445, 23.88659090
Driver 4	Greece; North to South; Attiki Odos	To Athens International Airport	Athens International Airport	38.0528111, 23.77916772
Driver 5	Greece; North to South; A.TH.E	To Athens	Athens	38.77407197, 22.7735063
Driver 6	Greece; South to North; Ionia Odos	To Ioannina	Ioannina	39.52466131, 20.8797599
Driver 7	Greece; South to North; Ionia Odos	To Ioannina	Thessaloniki	39.4316466, 20.9053163
Driver 8	Greece; South to North; Egnatia Odos	To Alexandroupoli	To Alexandroupoli	40.7246485, 23.1062853
Driver 9	Greece; South to North; A.TH.E	To Thessaloniki	Thessaloniki	39.3122619, 22.74998011

.

For example, the 1st driver drives a route from the North of Greece to the South. When looking for a parking area, he is on Olympia Odos towards Athens and his destination is Athens International Airport. His location coordinates are 38.32336318, 21.879061702.

At first glance, taking into account drivers routes and available truck parking areas, there are: 8 parking areas to be considered for Driver 1; 9 parking areas to be considered for Driver 2; 7 parking areas, for Driver 3; 2 parking areas, for Driver 4; 10 parking areas, for Driver 5; 4 parking areas, for Driver 6; 6 parking areas, for Driver 7; 1 parking area, for Driver 8; and 10 parking areas for Driver 9. Not all these parking areas are in the route of the truck driver. The system calculates the distances between truck driver and parking areas, positively for the parking areas that are in the route of truck drivers and with negative values when the truck driver has already crossed the truck parking area.

Table 7. Truck parking areas for Driver 1.

Motorist Service Stations (MSS) and SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
MSS PSATHOPYRGOS 1	1.609	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−1.158	−0.585	0.011	0.306	−1.426
MSS AIGIO 1	35.398	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−1.158	−0.585	0.011	0.306	−1.426
MSS AKRATA 1	59.533	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−2.316	−0.585	0.011	0.306	−2.584
MSS VELO 1	114.239	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS ZEVGOLATIO	122.284	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS MEGARA 1	160.9	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS ASPROPYRGOS 1	189.862	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS MESOGEION 1	217.215	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−4.632	−0.585	0.011	0.306	−4.9

shows the parking areas that correspond to driver’s needs and the partworth utilities that represent parking characteristics and the distance between the driver and the parking areas. The total utility of each parking area is included in the final column of Table 7, representing the sum of partworth utilities.

Table A2. Truck parking areas for Driver 2.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
MSS PSATHOPYRGOS 2	99.758	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−2.316	−0.585	0.011	0.306	−2.584
MSS AIGIO 2	80.45	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−2.316	−0.585	0.011	0.306	−2.584
AKRATA 2 (SSTPA 9)	62.751	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−2.316	−1.171	0.033	0.917	−2.537
EPISKOPIKO 2 (SSTPA 8)	313.755	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−5.79	−1.171	0.033	0.917	−6.011
MSS AMVRAKIA	197.907	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS FILIPPIADA 2	268.703	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−4.632	−0.585	0.011	0.306	−4.9
MSS EVINOCHORI 2	141.592	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742

,

Table A3. Truck parking areas for Driver 3.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
MSS ASPROPYRGOS 2	57.924	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−2.316	−0.585	0.011	0.306	−2.584
MSS MESOGEION 2	12.872	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−1.158	−0.585	0.011	0.306	−1.426
MSS PSATHOPYRGOS 2	228.478	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−4.632	−0.585	0.011	0.306	−4.9
MSS AIGIO 2	210.779	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−4.632	−0.585	0.011	0.306	−4.9
AKRATA 2 (SSTPA 9)	191.471	2: 20 €< C ≤ 30 €; 3: Above standards; 3: Silver Level	−3.474	−1.171	0.033	0.917	−3.695
MSS VELO 2	139.983	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS MEGARA 2	72.405	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−2.316	−0.585	0.011	0.306	−2.584

,

Table A4. Truck parking areas for Driver 4.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
MSS MESOGEION 1	16.09	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−1.158	−0.585	0.011	0.306	−1.426

,

Table A5. Truck parking areas for Driver 5.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
ATALANTI 1 (SSTPA 3)	74.014	2: 20 €< C ≤ 30 €; 3: Above standards; 3: Silver Level	−2.316	−1.171	0.033	0.917	−2.537
MSS MALAKASA 1	165.727	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS VARYBOMPI	183.426	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742

,

Table A6. Truck parking areas for Driver 6.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
EPISKOPIKO 2 (SSTPA 8)	38.616	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−1.158	−1.171	0.033	0.917	−1.379

,

Table A7. Truck parking areas for Driver 7.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
EPISKOPIKO 2 (SSTPA 8)	28.962	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−1.158	−1.171	0.033	0.917	−1.379
MSS PLATANOS 2	249.395	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−4.632	−0.585	0.011	0.306	−4.9
ANALIPSI 2 (SSTPA 6)	305.71	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−5.79	−1.171	0.033	0.917	−6.011

,

Table A8. Truck parking areas for Driver 8.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
ANALIPSI 1 (SSTPA 5)	40.225	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−1.158	−1.171	0.033	0.917	−1.379

and

Table A9. Truck parking areas for Driver 9.

Motorist Service Stations (MSS) & SSTPAs	Distance (km)	Cost (C); Information Provision; Security Level	Partworth Utility Distance	Partworth Utility Cost	Partworth Utility Information	Partworth Utility Security	Total Utility
AERINO 2 (SSTPA 2)	16.09	2: 20 € < C ≤ 30 €; 3: Above standards; 3: Silver Level	−1.158	−1.171	0.033	0.917	−1.379
MSS KORINOS 2	175.381	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS NIKAIA 2	62.751	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−2.316	−0.585	0.011	0.306	−2.584
MSS SKOTINA 2	122.284	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742
MSS EVANGELISMOS 2	88.495	1: C ≤ 20 €; 1: Below standards; 1: Non-certified	−2.316	−0.585	0.011	0.306	−2.584
MSS SCHIMATARI 2	175.381	1: C ≤ 20; 1: Below standards; 1: Non-certified	−3.474	−0.585	0.011	0.306	−3.742

show the results of utilities calculations for the other 8 drivers. Maximum utility indicates the preferable truck parking area for the truck driver, thus the highest- scored truck parking areas have been covered.

3. Results

Following utility estimation for all available parking areas, the position of the ones that are relevant for each driver are depicted as in Figure 3 with the use of Bing Maps in Excel. In this quick assessment that precedes the presentation of the results, the mapping of parking areas indicates their proximity to the driver’s route.

Figure 3a indicates the location of Driver 1 (red dot on map) and the location of available parking areas for the route declared by the driver (blue dots on map). From the map, the driver is on Olympia Odos, near Psathopyrgos, and has stated that he is heading to Athens International Airport. The driver has overtaken MSS Psathopyrgos by 1.609 km, as the blue dot is located just before the driver, thus the 1st parking area would divert Driver 1 from his route. The analysis continues with identifying the position of the other drivers relative to the parking spaces.

Figure 3b similarly indicates the location of Driver 2 and that of the available parking areas for the route declared by the driver. From the map, the driver is on Olympia Odos and has stated that he is heading towards Ioannina. Considering the driver’s position, the system suggested all parking areas that are in driver’s route.

In Figure 4a, the location of Driver 3 and that of the relevant available parking areas for the route are depicted. The driver is on Attiki Odos and heading towards Patras, with seven parking options available along his route. The system has responded correctly, as it does not suggest parking areas that would divert Driver 3 from his route. From all maps, it was ascertained that, for all drivers in this application, the system proposed the proper truck parking areas along the driver’s route (Figure 4b–f and Figure 5).

In conjoint analysis, for any participant and any scenario, the demand estimation function provides the probability of choice as a function of the estimated utility and conversion rule. For instance, in the maximum utility rule, choice probability of 1 is assigned to the highest utility, and 0 to all others in the choice set. Any tie in the estimated utilities is either broken randomly or by assigning equal probabilities (e.g., p = 0.5) to the corresponding choices [42].

The maximum utility rule, adopted in this research, indicates the preferable truck parking area for each truck driver, as summarized in

Table 8. Characteristics for highest scored truck parking areas.

Driver (Nr.)	Parking Code	Motorist Service Stations (MSS) and SSTPAs	Distance (D) in km	Cost (C)	Information Provision	Security Level	Utility
Driver 1	P37	MSS PSATHOPYRGOS 1	1.609	C ≤ 20 €	Below standards	Non-certified	−1.43
	P39	MSS AIGIO 1	35.398	C ≤ 20 €	Below standards	Non-certified	−1.43
Driver 2	P42	AKRATA 2 (SSTPA 9)	62.751	20 € < C ≤ 30 €	Above standards	Silver	−2.54
Driver 3	P36	MSS MESOGEION 2	12.872	C ≤ 20 €	Below standards	Non-certified	−1.43
Driver 4	P35	MSS MESOGEION 1	16.09	C ≤ 20 €	Below standards	Non-certified	−1.43
Driver 5	P13	ATALANTI 1 (SSTPA 3)	74.014	20 € < C ≤ 30 €	Above standards	Silver	−2.54
Driver 6	P26	EPISKOPIKO 2 (SSTPA 8)	38.616	20 € < C ≤ 30 €	Above standards	Silver	−1.38
Driver 7	P39	EPISKOPIKO 2 (SSTPA 8)	28.962	20 € < C ≤ 30 €	Above standards	Silver	−1.38
Driver 8	P23	ANALIPSI 1 (SSTPA 5)	40.225	20 € < C ≤ 30 €	Above standards	Silver	−1.38
Driver 9	P2	AERINO 2 (SSTPA 2)	16.09	20 € < C ≤ 30 €	Above standards	Silver	−1.38

which shows only the parking areas with the maximum utility where the utility represents the sum of partworth utilities (Table 7, Table A2, Table A3, Table A4, Table A5, Table A6, Table A7, Table A8 and Table A9). Based on the utility values, MSS PSATHOPYRGOS 1 and MSS AIGIO 1 are the most suitable parking areas according to the stated preferences of Driver 1 on this route. Based on the adopted rule, we can assume that each of these two parking areas could be equally selected by this driver.

In all other cases, a parking area is selected with no ties. For instance, AKRATA 2 (SSTPA 9) appears to be the most suitable parking area of Driver 2 based on his stated preferences. SSTPA gathered the highest rating amongst the six offered truck parking areas in his route, since it is located near the driver’s position, exhibits a high level of security, and provides information above standards (Table A1). From the results, 6 out of 10 selected parking areas are certified at “Silver Level” of security—which is encouraging since the security aspect is found to be of high importance.

4. Discussion

This research developed and tested a method and model for estimating location choice of safe and secure truck parking areas. The proposed method can be used to facilitate the selection of a truck parking area by considering its safety and security aspects in the context of the C-ITS motorway services being developed in TEN-T.

Safe and secure truck parking areas in Greece will represent the 19.15% of the total parking of the Greek sections of the Orient/East-Med Corridor of the TEN-T by the end of 2023. Although no certified SSTPA is placed on Hellenic motorways, the research considered also the nine SSTPAs that will be certified in 2023 as part of Connecting Europe Facility (CEF)—Transport Sector (Agreement INEA/CEF/TRAN/M2019/2099687). The research seeks to guide truck drivers to either a certified truck parking area (SSTPA) or at least to a motorist service station, thus addressing the issue of illegal parking of trucks as well.

In line with the Commission Delegated Regulation (EU) No 885/2013 and within the scope of the above agreement, an e-Service platform will be developed for truck drivers. The platform will provide all necessary information on the location of SSTPAs, their certification level, and available services. It will also enable pre-booking and pre-payment options for parking places. In view of this development, the proposed system could also be considered to offer personalized information to truck drivers and allow the interaction between the end-users and the infrastructure.

The capabilities of this research for personalized assistance to drivers are founded on disaggregate modelling and conjoint analysis. This work can offer added value in supporting the upgrading of the TEN-T infrastructure systems within novel transport and logistics in an operationally safe, secure, and efficient environment for the supply chain. Owing to its new capabilities for information provision, the method could be integrated with infrastructure systems and on-board truck drivers’ units.

Considering the stated preference of users for personalized services such as the capabilities offered by the new model and method, it is expected that this work, developed in the framework of Cooperative Intelligent Transport Systems (C-ITS) will contribute to the readiness and robustness of truck drivers’ acceptance of the upcoming safe and secure truck parking areas in the Hellenic motorways. The added value of this approach lies in enabling interaction between the truck driver and the existing and upcoming electronic platforms, contributing to the increased safety, security, and sustainability of freight road transport.

The developed methodology can be used to integrate parking data from truck parking operators and truck drivers for estimating the utility of each parking area, reflecting the probability of selecting a truck parking area from a set of available areas. The novelty of this research includes the use of conjoint analysis for developing the utility function for parking space selection [41], and the in-depth analysis of the choice amongst potential routes of the Greek sections of the Orient/East-Med Corridor of TEN-T. More specifically, 47 parking areas and nine truck driver registrations were used for testing the new method. The 47 parking areas were included in the 38 Motorist Service Stations in all directions in the Hellenic highways and nine safe and secure truck parking areas.

The method and model of this research can be transferable to similar applications, so this system could be adapted to serve the whole European TEN-T. Future work is expected to include drivers from across Europe and expand this system in the European area. Since the share of road freight transport in Europe is increasing with its share reaching 24.6% (1863 billion ton-km) in 2021 [47], the method and its personalized features would be useful for all truck drivers. In addition, with the development of more safe and secure truck parking areas, it is proposed to enrich the method databases and limit them only to certified secure truck parking areas [25]. This system could also connect with existing smartphones and platform applications, expanding its availability to all truck drivers and truck parking managers. It would be very important for the evaluation of the system to gather the feedback from truck drivers after the proposed truck parking area has been selected.

5. Conclusions

Drawing on concepts from the literature and the statutes, this research provides a novel contribution to enriching existing platforms for safe and secure truck parking areas. In the context of C-ITS motorway services in TEN-T, the personalized services of the new method could support the increase in acceptance of the new technologies. Integrating parking data from truck parking operators and truck drivers to estimate the utility of each parking area and the probability of selecting a truck parking area from a set of available areas will facilitate truck drivers’ parking selection while increasing freight safety and security.

The proposed personalized choice system takes into account the most significant parking choice parameters within a disaggregate model for estimating the most suitable truck parking area for each driver. In order to receive data from drivers, a registration form was developed. A database for truck parking areas was created for facilitating the introduction of new parking areas, ideally safe and secure truck parking areas, based on the potential truck route choices in the Greek sections of Orient/East-Med Corridor of TEN-T.

For all nine truck driver registrations used for testing the new model and method of this research, the system proposed a truck parking area to meet their needs. In only one case, the system proposed a truck parking area that diverted the driver from his route, probably because of the short distance (1.609 km) between the driver and the closest motorist service station. In total, the functional evaluation indicated 94.4% efficiency in finding the most suitable parking space for the nine truck drivers since the system managed to identify the best truck parking areas for the other eight drivers. It is worth highlighting that although the distance from the truck parking area was a dominant factor for the truck parking area selection, 6 out of the 10 selected parking areas was certified in the “Silver” level of the safe and secure truck parking areas. It is expected that in a motorway network with SSTPAs of all levels, namely bronze, silver, gold, and platinum, the security part worth utility will emerge, especially when all the conventional parking areas will be replaced or upgraded to certified. This novel approach can be integrated into e-service platforms for safe and secure truck parking areas.