Model for Planning and Sizing Curbside Parking Lanes in Urban Networks

Abstract

Curbside parking is associated with various adverse impacts on urban traffic networks and is rarely recommended. However, there are cases where parking demand dictates the establishment of on-street parking lanes. Proper planning of the number and type of curbside parking lanes to be located is essential for maximizing roadway capacity and minimizing the resulting impacts of parking operations on the network’s performance. This paper develops a bi-level mathematical programming model for planning and sizing curbside parking lanes in an urban network. The model is solved using a genetic algorithm and demonstrated for a medium-sized urban network.

Intelligent Management of On-street Parking Provision for the Autonomous Vehicles Era

“…Previous research concerning the on-street parking problem predominantly concentrates on three areas: the demand, supply and pricing for parking [15], [16]; safety and delay impacts of curb parking behaviours [17], [18]; the impact of on-street parking on traffic operations [19], [20]. A subset of studies from the third group has investigated how onstreet parking patterns can have an impact on such traffic operations [21]- [23].…”

“…To address this issue, these studies used cellular automata models [8], queuing models including the M/M/∞ model [24], M/M/C model [25] and agent-based models [26] to estimate the additional travel cost and traffic congestion caused by on-street parking manoeuvres. Some studies utilised microscopic traffic simulation software, including VISSIM and SUMO (Simulation of Urban Mobility) [19], [27]. We have identified the following research gaps from the reviewed studies.…”

“…A similar approach was used by Wang et al [28], who minimised cruising distances, walking distance and coverage of amenities to balance on-street and off-street parking supply. Besides these variables, road capacity [19], [21], cruising time [29] and parking service rate [26] are all objective variables options according to previous studies. However, few studies have minimised traffic delay to obtain the optimal distribution of curb parking.…”

“…Studies adopting the simulation methods can directly model the complicated operations of traffic flow and parking manoeuvres [19], [25], [27], [29]. For instance, Polycarpou et al [15] deployed a SUMO-based optimisation model to find the optimal matching solutions between parking slots and drivers [29].…”

Demonstrative Case of a Pedestrian Network Design Model Considering Effects on Motorized Traffic

“…In the basic scenario, equal importance was attributed to each objective. Following a calibration process, a population value of 50 and a crossover rate of 0.4 were selected (29). Mutation probabilities were assumed as 0.02 (1/50).…”